Computer

COMPUTER-AIDED

PROCESS PLANNING (CAPP)

SECOND EDITION

SEPTEMBER 1991

ARCHITECTURE TECHNOLOGY CORPORATION SPECIALISTS IN COMPUTER ARCHITECTURE

P.O. BOX 24344 · MINNEAPOLIS. MINNESOTA 55424 · (612) 935-2035

E L S E V I E R A D V A N C E D TECHNOLOGY

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® Copyright 1991 Architecture Technology Corporation. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a retrieval system, or transmitted without the express prior written consent of the publisher.

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Architecture Technology Corporat ion makes no representations or warranties with respect to the contents hereof and specifically disclaims any implied warranties of merchantability of fitness for any particular purpose.

Further, reasonable care has been taken to ensure the accuracy of this report, but errors and omissions could have occurred. Architecture Technology assumes no responsibility for any incidental or consequen-tial damages caused thereby.

Further, Architecture Technology Corporation reserves the right to revise this guide and to make changes from time to time in the content thereof without obligation to notify any person or organization of such revision or changes.

This disclaimer applies to all parts of this document.

FOREWORD

Process planning involves creating detailed plans of the manufacturing steps and equipment necessary to produce a finished part.

Workpiece requirements call for detailed analyses and accurate descriptions prior to the actual manufacturing process. A large assortment of machines and operations, as well as many different workers with a variety of skills, may be involved in the production of a specific part.

The computer is a vital part of the process planning function, which includes two different approaches. One is called the variant (similar part) method of process planning and the other is generative (expert system-based). Both will produce similar process plans. Most computer applications, however, are of the variant type, because the software is easier to develop and new process plans are based on previous ones.

The variant method had its beginnings with the G T concept, along with parts classification and coding systems. G T is a manufacturing philosophy based on the idea that similarities occur in the design and manufacture of component parts. These parts can be classified into groups, or families, if the basic configurations and attributes are identified. A reduction in expenses can be achieved through the structured classification and grouping of parts into families based upon engineering design and manufacturing similarities.

Using the variant method, CAPP groups families of parts by a structured classification and coding plan. All previously processed parts are coded using this method. The parts are then divided into part families, such as cylindrical or prismatic, based on general configuration. A standard order of operations or sequences is stored on the computer for each part family. When a new part is ready for planning, the classification or G T code for the new part is used to compare and retrieve the standard process plan for that part family. Editing capabilities further enable the process planner to alter the standard order of operat ions for final refinement. The completed process plan is then stored on the computer database by part number.

In generative process planning, the parts are again broken into part families, and a detailed analysis is made for each part family to determine individual part operations. This type of system develops the actual operation sequence based on the part geometry, usage requirements, material size and configuration, and available equipment. The generative approach creates process planning logic for the part family groupings. The logic is then stored internally as a decision model. As new workpieces require process planning, analyses must be conducted to determine and compare the features incorporated in the decision model with those on the actual part. The family part decision model is then retrieved, and a routing sheet is generated by processing the decision model with the new workpiece attributes.

A generative system must be driven by much more elaborate and powerful software than a variant system. Development and optimization work continues on the variant and generative approaches to process planning. Both systems, however, build the needed decision-making logic and planning ability into the computer rather than rely on a decreasing experience level in the process planning work force.

Computer-Aided Process Planning (CAPP)

Figure List

Figure 1: Production of a Simple Part 2

Figure 2: Operat ions Overview 5 5

Figure 3: Part Family Matrix File 5

Figure 4: Process Plan 6

Figure 5: Standard Plan Structure 6

Figure 6: Basic System Menu and Sub-program Menu 8

Figure 7: Outl ine of an In-house Classification and Coding System 10

Figure 8: Structure of Variant Module 12

Figure 9: Structure of the Semi-generative Module 14

Figure 10: System Structure of the Proposed G T Based CAPP System 15

Figure 11: Architectural Overview 31

Figure 12: Process Planning External Architecture 36

Figure 13: ICAPPS System 38

Figure 14: Extracting Generated Surfaces 40

Figure 15: Flow Chart of Process Planning 42

Figure 16: Functional View of CMPP 46

Figure 17: Major CMPP Components 46

Figure 18: Data Base System 47

Figure 19: Part Input System 48

Figure 20: Process Planning System 48

Figure 21: Typical Steps in the Assembly of a P/CB 51

Figure 22: A CIM Architecture for the Production of Electronic Systems 54

Figure 23: The CAPP-Postprocessor Relationship 56

Figure 24: Sample Product Rou te List 60

Figure 25: Master R o u t e Flow 60

Figure 26: M R P View of the Master Rou te 61

Figure 27: W F C View of the Master Rou te 61

Figure 28: F D C View of the Rou te Master Flow 62

Figure 29: Data Relationship Between the Process Master and the Rou te View 64

Figure 30: Physical Operat ions, Typical Manufacturing Facility 68

Figure 31 : Traditional Building Control Focus 69

Figure 32: Integrated Manufacturing Facility 71

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1. Introduction

1.1 System Organization

Given the engineering design of an item which has to be manufactured, process planning is the act of generating an ordered sequence of the manufacturing operations necessary to produce that part within the available manufacturing facility.

For maximum efficiency, the developed process plan should produce the part at the lowest cost consistent with acceptable quality standards and using established procedures. In achieving these aims, it is essential that process plans for parts which are basically similar should be standardized.

Traditionally, process planning has been regarded as a manual operation, usually carried out by a manufacturing engineer (process planner, process engineer, etc.) who is often a qualified and experienced machinist or tool maker. The success rate achieved by an individual planner is largely dependent upon individual skill and apti tude for the planning task, knowledge of manufacturing processes, equipment, materials and methods in general, and those available in a production facility in particular.

The rapid evolution of increasingly sophisticated production methods, the ever increasing trend towards the use of flexible manufacturing systems, and the need for improved manufacturing efficiency has necessitated a requirement for improved process planning. The use of computers to achieve this is now well established, and new computerized methods are continually being sought.

1.1.1 Traditional Process Planning

Traditional process planning methods usually allocate planning jobs to the next available planner. Each task is therefore treated as a new process plan with usually limited attention being given to process plans for similar parts already in existence. As a result, each process plan will reflect primarily the skills and experience of the individual planner concerned; hence, it is extremely difficult to maintain consistency and discipline in the planning process. Process planning also requires the use of many complex disciplines including sequencing, machine selection, t ime and motion study, programming, and material flow to name some of the most common. All of these skills are needed in an increasingly complex manufacturing environment and are making it even more difficult to produce efficient process plans.

Several studies have been conducted to investigate the efficiency of manual process planning methods. One, conducted by Cincinnati Milacron, reports the results of a study into the process planning for the production of a family of spur gears. For a sample of 425 relatively simple spur gears, there were 377 different process plans (operation sequence and machine groups), 54 different types of machines required, and 15 different materials utilized. The plans gave 252 unique combinations of machine tools for successive operations. The inefficiency arising from this situation must be obvious to anybody with manufacturing experience.

A perfect example of the problem concerns the production of the simple part shown in Figure 1, together with the processes proposed by four different process planners. The four different methods of producing the 18 mm hole are readily apparent and obviously reflect the past experience of the individual planners concerned.

Attempts to standardize and rationalize the process planning task revolve around the maintenance of card index systems which relate to previous plans. Such systems quickly become outdated or are, at best, very cumbersome to use. The use of a computer for storing such data was an obvious first step and the first

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CAPP systems were basically just computerized card index systems.

1 Drill 15° Face Cut Turn 30 Face Cut 2 Drill 18° Turn 30 Countersink Turn 30 3 Turn 30 Thread Cut Drill 17.5° Countersink 4 Thread Cut Drill 16° Bore 18° Drill 16° 5 Face Cut Bore 18° Thread Cut Bore 18° 6 CutOff CutOff Face Cut Chamfer 7 Second Face Cut Second Face Cut CutOff CutOff 8 Second Face Cut Second Face 9 CutChamfer 10 Thread Cut

Figure 1: Production of a Simple Part

1.1.2 Classification and Coding

The number of different part numbers which flowed through most manufacturing facilities were such that they made the initial card index approach only a very marginal improvement on the manual systems which they superseded. The development of standardized process plans required the identification of part families where such families can be distinguished by the sequence of manufacturing operations required. Several part families may share common machine tool routings but a unique production part family has the same, or nearly the same, list of operations. To define part families, it is necessary to have some form of parts classification and coding system.

Classification and coding systems are often considered to be a part of the Group Technology (GT) production concept. However, classification and coding systems have advantages quite separate and distinct from their use with GT. For example, a well designed classification and coding system can provide significant advantages in the basic engineering design process by reducing the number of drawings and different part numbers which commonly occur over a period of time through the duplication of part designs which perform the same or similar function.

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When used with GT, the benefits of classification and coding can be summarized thusly:

• The formation of part families and machine groups

• Quick retrieval of designs, drawings and production plans

• Design rationalization and reduction of design costs

• Secure reliable workpiece statistics

• Accurate estimation of machine tool requirements, rationalized machine loading, and optimized capital expenditure

• Rationalization of tooling setups and the reduction of set-up times and overall production times

• Rationalization and improvement of tool design and the reduction of tool design time and cost as well as tool fabrication time and cost

• Rationalization of production planning procedures and scheduling

• Accurate cost accounting and cost estimating

• Better utilization of machine tools, work holding devices, and manpower

• Improvement of Numerical Control (N/C) programming and the more effective use of N/C machines.

Many of these benefits can be achieved without using them in conjunction with the G T cell concept.

There are a large number of proprietary classification and coding systems available ranging from the "look and see" approach to large numerically coded systems. The most well known systems include among others, the O P I T Z system developed in Germany, the MICLASS system developed in Holland, and the BRISCH BIRN system developed in Sweden. In practice, most proprietary systems have been found to be inadequate for particular company applications and most successful classification and coding systems have been developed by adapting a basic proprietary system to suit the needs of the particular facility concerned.

A basic problem in using any classification and coding system is the human problem of applying it to particular parts; i.e., different people using the same coding system will arrive at different codes for the same part. Most applications nowadays therefore, use computer assistance in order to obtain standardized coding. O n e such aid is the DCLASS system developed at Brigham Young University, which can be utilized in conjunction with any classification and coding system to obtain consistent results. This system is an interactive system which enables a planner seated at a C R T to obtain a classification code by responding to a series of system produced queries.

The basic starting point of a CAPP system is the implementation of a good classification and coding system. However, work put into classification and coding has many other useful applications in the manufacturing and design environments, such that implementation costs can be easily recouped from efficiency improvements.

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1.1.3 CAM-I CAPP

One of the earliest CAPP systems was developed under contract to Computer Aided Manufacturing-International, Inc. (CAM-I) in the USA. CAM-I is a not-for-profit organization, formed in the U.S. in the early 1970s by a number of major American manufacturing companies, to provide leadership in the development of computer aids to manufacturing industry. CAM-I is now an internationally recognized body with member companies in the U.S., Europe, and the Pacific Rim. The CAPP program has since been used and adapted by CAM-I member companies for their own use and thus forms the basis for many of the well-known company sponsored systems. Two versions of CAPP are now available for 16 bit and 32 bit computers, respectively. Both versions are identical in operation and effect.

CAPP is based on the use of a classification and coding system to group parts into part families. Each part family has a common, or nearly common, process plan, which is stored in the computer as a standard plan for that part family. Each standard plan is a sequential set of instructions that includes general processing requirements, jig and tool data, machine data, and detailed operating instructions. In the CAPP system, these standard plan details are called work elements and work element parameters. The system allows for these items to be referred to in any format which will suit the normal facility terminology. In addition, the CAPP system permits the use of any classification and coding system up to a maximum of 36 digits.

CAPP is an interactive system which permits a planner to sit at a terminal and locate process plans, modify existing plans, or carry out any other normal process planning operations without any need to know computer programming. CAPP is written in standard ANSI FORTRAN-77 ; however, two or three of the sub-routines involved are machine or terminal dependent and may require modification to suit particular installations. In general, however, the use of FORTRAN-77 does mean that user modifications can easily be built into the basic CAPP program. CAM-I only aims to produce prototype software and a particular implementation of CAPP requires some debugging effort on the part of the user.

1.1.4 The CAPP System

Basically CAPP requires a data structure of six main files: part family matrix file, standard sequence file, operation code table, operat ion plan file, part family code table, operat ion plan file, part family set-up file and a process plan store file. The flow diagram in Figure 2 gives an overview of the sequence of operations.

System operation is menu-driven. The particular operation to be carried out can be called by invoking the particular menu concerned and responding with coded commands to carry out the operation required. Process plan data, process plan header data, part numbering, and other data are all inserted using normal facility nomenclature and formats. Although this data is specified during system setup, it can easily be altered later as facility requirements dictate. The part family matrix file contains the part family codes in the form of a matrix as shown in Figure 3.

The CAPP system allows for a 35 digit coding format with up to 16 permissible characters for each digit. The system also allows for part attributes to use up to four digits for coding and for multiple characters to be used in each digit. The part family matrix file, therefore, allows great flexibility for the user to select a classification and coding system which gives him the greatest possible benefits.

The CAPP system requires the user to develop and store a standard process plan for each family. Each process plan contains header data which can be initialized by the user for the types of information needed on the printed process plan and for any language desired. Approximately 100 items are available as shown in Figure 4. A user specified header menu is built up when the system is initialized and appropriate data is inserted into the menu when a new process plan is generated.

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Part Family Matrix

Part Family Search

( Part *\ Classification

V Code J

Standard Sequence

File

Header Input Data

Standard Sequence

Retrieve/Edit

Process Plan

Operation Ran File

Operation Plan

Retrieve/Edit

Process Plan

Process Plan

Formatter Process

Plan Store

Application Programs

Work Element

Processor

Figure 2: Operat ions Overview

Code Classification Code Length

Char. Set

Γ 1 2 3 4 5 6 7 8 9 10 11 12 13 14

I 15 16

0 X X X

1 X X X X

2 X X X

3 X X X X X X

4 X X X X

5 X X X

6 X X X

7 X X

8 X

9 X X X

A X X X

Β X X

1 2 , 3 1 4 5 . 6 „ 7 I 8 1 9

I 10 , 11 ,

I I

Part Attributes

Figure 3: Part Family Matrix File

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Header Data Elements

Identification

Part No. Part Name Part Family No. Plan Type Issue No. Etc.

Reference

Part Type Source Standard Cost Lead Times Project Etc.

Usage

ι Next Assy. Effectivity Quantity Units/Prod. Etc.

Material

I Material Code Material Size Material Spec Weight Supplier Etc.

Planning Change

Change Letter Change Planner Change Date Etc.

I 1 Miscellaneous

Work Standards Standard Times Q.A. Class Order No. Mfg. Source

Figure 4: Process Plan

Each process plan is built by invoking a set of operation codes (op codes), each of which identifies a unique operation. The op codes are set up during initialization in the op code file and operation descriptions can be in the standard facility format. Each process is numbered and cross referenced to the part family number to which it refers. The standard plan structure is shown in Figure 5.

Operation Plan (OP Plan/OP Codes)

Dept • M / C Number Work Center IM/C Reference M/C Code 1 Location

Set Up Data Time Stds Data

Work Elements or Work Instructions

Work Element Parameters

Figure 5: Standard Plan Structure

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The basic CAPP system requires the user to insert his own time standards, but several companies have found it a fairly straight forward operation to link a computerized standard t ime program to the system. The CAPP system also allows for unique part process plans to be stored separately for parts which do not reasonably fit into any commonly used part family.

The operation of the system requires the user to feed in the classification code for the part concerned. The system searches the part family matrix file and attempts to fit the part into a part family for all the digits in the code. If unsuccessful in matching all digits, the system will find the part family which matches the earlier digits in the code and will tell the user how many digits can be matched. Once a part family has been found, the process plan for that family can be called up on the screen. The process plan can be used as is or can be modified where necessary for a particular part, and header data can be altered. If a standard plan is used as is, the part number concerned is added to the list of the part numbers which form a part family. If a standard plan has to be modified, it can be stored as a separate part plan, printed out and then deleted, or stored as a revised process plan for the appropriate part family. The basic system menu and one of the sub-program menus are shown in Figure 6, as examples of the system in operation.

CAPP is comparatively simple to use, once it is set up, and requires no special computer skills from the process planner. The system has been operated successfully by many companies in its basic form. However, it was first used in 1976 and some of the major companies who started with the system have made modifications to enhance its usefulness and to make it more compatible with their own operations.

1.1.5 CAPP Developments

CAM-I CAPP is known as a variant process planning system; i.e., it operates by taking an existing process plan and changing it to suit the new part. There are, however, obvious advantages in being able to create a brand-new process plan for each part as required. Systems which operate in this way are known as generative process planning systems and development work on such systems has been the subject of much research over the last decade or so.

A generative process planning system must be capable of applying a set of rules and massive amounts of data to the construction of a process plan in much the same way as a human planner reasons when he constructs such a plan. Hence, the development of a generative process planning computer system requires the use of computer systems termed artificial intelligence (AI) systems. More specifically, current research is based around a subset of AI technology called knowledge-based expert systems. Expert systems consist of a factual database and a set of inferential or heuristic (rule of thumb) rules which use the factual database to solve problems.

Investigations into heuristic methods of process planning define process as a problem which is only defined by its target (finished part) , starting point (raw material), and a set of constraints (available processes and equipment and technological relationships). In addition, it is probably necessary to introduce time/cost criteria to choose an optimal solution. The conclusions from such studies tend to agree that the use of expert systems or AI are probably the most promising way to tackle the complex relationships involved in the planning process.

1.1.6 CAPP and CAD/CAM

CAD/CAM systems have been developed to the point where a design engineer and a manufacturing engineer seated at graphics terminals connected to a common computer database can produce parts from computer designs without benefit of paperwork at any point. Thus, engineering drawings, process planning documents, and other manufacturing paperwork are all stored in the computer. If the computer is connected directly to the appropriate Computer Numerical Control (CNC) machines as in a flexible

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FS FP

CAPP SYSTEM MAIN MENU

DP HD OS OP PP LO

Part Family Search Format Plan Delete Plan Create New Plan Retrieve Header Retrieve OP Code Sequence Retrieve OP Plan Process Plan Review Logoff

FS FP DP HD HD/ (Part No, Plan Type, Status) OS/ (Part No, Plan Type, Status) OP/ (Part No, Plan Type, Status) PP/ (Part No, Plan Type, Status) LO

Space for inserting code for menu item required, e.g. FS

MS SP

Part Family Search

DS SA CS MM LO

Matrix Search Retrieve Standard Plan Display Plan No's Search Attribute Continue Search Return to Main Menu MM Logoff

NS/ (Classification Code) SP/ (Part Family No.) DS/ (Part Family No.) SA/ (Attribute No., Value) CS MM LO

Space for inserting code for menu item required, e.g. DS/26

Figure 6: Basic System Menu and Sub-program Menu

manufacturing system, the process plan can be followed without the need for human intervention. Current CAPP systems make this possible, the newer CAPP systems will obviously enable it to be done even more efficiently.

L 2 CAPP and GT

Current industrial applications indicate that the combining approach of variant and generative CAPP methods is suitable for practical usage. A variant model is found most applicable for those products which the company produces regularly, and a generative model is useful for the parts for which engineering designs and manufacturing requirements vary. Since the current state of the art of the generative method requires further development, it is more practical to develop a semi-generative method which combines the specific features of variant and generative approaches.

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1.2.1 Group Technology

As noted above, G T is a manufacturing philosophy which identifies and exploits the underlying sameness of parts and manufacturing processes. In conventional piece-part manufacturing, each part is treated uniquely from design to manufacture. However, by grouping similar parts into part families based on design or process information, it is possible to reduce manufacturing costs.

G T classification and coding and part family concepts have been used as the key elements for most variant CAPP systems, which obtain the process plan by retrieving and modifying the part family-related standard process plan. The application of G T classification and coding and part family concepts are used, not only for classifying the parts, but also as the foundation for constructing logic and rules for generating process plans. The system provides a highly automated CAPP process which generates the applicable process plans. The system is relatively easier to develop and program, and needs less computat ion time and storage space than most of currently available generative CAPP systems.

The implementation of an in-house G T oriented CAPP system is a multi-phased procedure and must be introduced in steps. The proposed method makes the maximum usages of the G T concept. The entire process includes developing an in-house G T classification and coding system, forming part families, building an effective manufacturing information retrieval system, and developing the in-house semi-generative CAPP system.

1.2.2 GT Classification

The first and the most important step for implementation of G T is developing a suitable classification and coding system. Many generic classification and coding systems and schemes have been developed in various forms. They are readily available but not directly applicable in their original form, without being properly modified and tailor-fitted to meet the specific needs of a particular application.

A tailor-fitted process contains three steps. First, a random sample of parts for a fixed production period is collected. The sample is used as representative of the whole population of parts that is produced. Second, a suitable publicly available system is used for sample coding of selected sample parts. Third, the statistical data of the sample part population is evaluated using the coding results. The trial system is modified, based on the sample coded results and also to meet the specific needs of the application.

Following these exercises, an in-house classification and coding system with 13 digits is developed. The system contains such information as part type, general shape, material, operat ion and surface finishing requirements, and heat-treatment. Figure 7 shows the outline of the classification and coding system. An effective, user-friendly, menu-driven computer program can be developed on a personal computer.

1.2.3 Pa r t Families

Since most of the benefits obtained from applying G T are based on the underlying sameness of parts and their manufacturing processes, the method used to form the proper part family is a very critical element. The methods of forming G T part families have been improved using appropriate mathematical programming techniques and suitable computer programs. The simple ocular observation method and the manual production flow analysis method have been replaced by computerized methods using suitable algorithms. Recently, many advanced methods including cluster analysis and pattern recognition techniques have been proposed to form the G T part-families.

Most of the existing cluster analysis algorithms for forming G T part families use production flow data as the input. The part families formed by these methods are operation-sequence dependent and do not reflect the design aspect. However, from the computer integrated manufacturing implementation point of

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DIGITS DESCRIPTIONS

1 & 2 Product Type

3 & 4 Material

5 Size Parameter 1

6 Size Parameter 2

7 Size Parameter 3

8 Shipping Weight

9 General Shape

10 Operation and Accuracy (Outside)

11 Operation and Accuracy (Inside)

12 Operation and Accuracy (Ends)

13 Heat Treatment

Figure 7: Outl ine of an In-house Classification and Coding System

view for standardization of design, process planning, and other implementations of the G T concepts, part families should reflect both design and manufacturing characteristics. Since a well-designed G T classification and coding system should reflect correctly both manufacturing and design characteristics, part families reflecting both design and production processes can be obtained. The actual industrial applications using G T codes and multi-objective cluster analysis provides a method that can form the G T part families and retrieve similar parts and related part families properly.

1.2.4 Information Retrieval System

An important task in large manufacturing concerns is identifying and analyzing the numbers, types, and characteristics of parts being produced. All manufacturing, planning, and control functions are dependent on the understanding of the part population and its manufacturing requirements. With an interactive computer program, this information retrieval system easily finds the required production features, the material types, and operation requirements based on the specific priorities required.

It is always the desire of management that, at any given time, the part population of the factory is precisely known in terms of part specifications, production requirements, and part features, so that an information base exists for use in design rationalization, manufacturing planning, production control, marketing, and purchasing decisions. Under a G T environment, this includes the ability to retrieve and group part families for use in various manufacturing functions. Without a well-designed classification and coding system, retrieval of required manufacturing information is difficult.

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1.2.5 Variant CAPP Module

The first step in building a relatively proficient CAPP system is to use the variant approach. As in most variant CAPP systems, a standard process plan can be automatically retrieved for a new order, using its G T classification code and the part family number. The built-in standard process plans are entered for each part family, and the final process plan for a particular part can be obtained by editing the standard process plan.

The unique feature of this particular variant CAPP module is that it uses a multi-objective clustering algorithm as the part family searching mechanism instead of using the part family matrix matching or G T classification codes matching method like most GT-based variant CAPP systems. The advantage of using this method is that if the new part cannot be grouped into an existing part family, a number of similar parts and their part families can be reached according to different searching requirements. In this way, the user can develop the new standard process plan based on some other similar parts and their part family related standard process plan.

The structure of the variant module is shown in Figure 8. In order to obtain the process plan for a new part, the part must first be coded. Using the interactive coding program, a G T code can be assigned to the new part. After the part is coded, the user needs to input the priority for the part family searching. For instance, if a new part has the particular requirement on operations, the user can put the digits of operation requirements as higher priority digits. If, however, a part is made of special material and needs special heat treatment, then the user can specify the digits which describe the material and heat treatment as more important features. A similar part and part family can be retrieved and the standard process plans of these retrieved part families can be obtained from the standard process plan data file. The final process plan for the new part is obtained by modifying the retrieved standard process plan. A practical industrial application shows that the multi-objective clustering algorithm-based variant CAPP system can classify a part into a part family or find the proper part families more accurately for the new part than other variant-type CAPP systems. Using the relational database management technique, the computat ion time for searching similar parts and part families can be reduced tremendously.

1.2.6 Semi-Generative CAPP System

Using the variant process plan, the final process plan for a particular part can be obtained by editing the standard plan. Nevertheless, it requires the process planner to make decisions at the editing stage. In order to improve the performance of the CAPP system further, an application-oriented, rule-based semi-generative CAPP system can be developed to enhance the proposed variant system.

1.2.6.1 Variant and Generative CAPP Module

Although a variant process planning system can help the process planner to make the process plan efficiently, the person using the variant CAPP system must be an experienced process planner, so as to be competent in making decisions during editing the standard plans. Therefore, the variant process plan system is usually suitable for preparing process plans for those parts which have relatively stable process routes.

When there are many differences between the process plans of the similar parts, it is more suitable to use a generative process plan system. Instead of using existing standard process plans, a generative process plan system utilizes built-in logic to select and sequence necessary operations. All of the decisions in the process planning procedure are made by the system, and the operator need not be an experienced process planner.

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Coding

Part Family Searching

Semi-Generative Main Logic Tree

Editing

Process Plan

Figure 8: Structure of Variant Module

Developing a generative process planning system, however, is really an enormous task. A truly generative CAPP system is hard to construct. Enormous activities are involved in developing such things as general process planning logic sets and constructing a suitable database structure.

Since most so-called generative CAPP systems require that the user key-in part features, generated process plans are therefore dependent on how the part features are interpreted. In addition, a completely generative CAPP system makes every decision in the process planning procedure from scratch. This requires t remendous computer memory and computation time.

1.2.6.2 Semi-generative CAPP Module

The activity of process planning is a company-oriented task. This means that even a manufacturing process which has been successfully used in one company might not be suitable for producing the same part in another company, because of different manufacturing conditions, machine tools, skill of the workers, corporate culture, and unions. Therefore, it is hard to build a generic generative CAPP system which can be adapted for different manufacturing systems. However, when applying specific manufacturing applications, the task of developing the generative logic for process planning is greatly simplified.

Based on the above considerations, a semi-generative CAPP system holds promise for many applications. The reason that the system is termed "semi-generative" is that both a variant retrieving method and a generative decision logic approach are used. Some decisions are generated by the built-in, process

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planning generating logic, while some other process plan decisions are retrieved in the form of tables and decision sets.

The G T part family concept is applied as the key element for constructing the rule-based CAPP expert system. Instead of developing the process planning logic based on part features like most other generative CAPP systems did, the process planning logic or decision rules are divided into two types; part family related decisions and operat ion related decisions.

The part family related logic is the set of logic using the part family as the driven machine. Since different parts require a different process plan which is generated by a different logic set, similar parts can share the same process plan logic set. Therefore, the logic used for generating the process plan can be simplified by using the part family concept. In the part family oriented logic set, the decisions are made step by step according to the part family number. In each node of the logic tree, the operat ion or operations, division number and machine number will be defined. The detail operation instructions can be further retrieved by the operation number. Detailed operation instructions, like operation sequences, machine selections, machining parameters, and t ime standards can be generated with very few computations.

The other type of decisions are operation related. They are the rule sets which are related to operations rather than part families. For instance, some parts have auxiliary holes which should be drilled or drilled and tapped. However, there exist various combinations on radial or axial holes, the location of the holes, and the diameters of the holes. This is a set of decisions which is independent from the part families; e.g., a rule set called drilling. Depending on the size, location, and type of hole, parameters such as operation, operation sequences, and machine station can be obtained.

The method of developing the generative process planning logic using G T part family concepts simplifies the procedure of constructing the process planning logic. Because of this simple and clear logic tree, the computation t ime is reduced.

1.2.6.3 System Structure

The system structure of the semi-generative CAPP module is shown in Figure 9. The part to be planned is coded first, using the in-house classification and coding system.

After coding, the part will be automatically classified into one of the existing part families, if one is found. The main process plan logic calls the part family oriented rule sets and operat ion oriented rule sets, the machining and operat ion data bank, and time standard data bank and generates the process plan. Figure 10 shows the flow diagram of the entire system.

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Figure 9: Structure of the Semi-generative Module

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^ Start

MOCA PF Searching

CED Figure 10: System Structure of the Proposed G T Based CAPP System

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2. System Implementation

2.1 Developing the Process P lan

The basic information which links quote/order processing data with process planning data includes the part number, part description, and stock number. The part master identifies all of the resources which the company builds or uses in serving its customers. With data from quote/order processing, delivery requirements are established by date and quantity. With this information in place, automating the process planning function can proceed.

2.1.1 Basic Considerations

The first step in automating the process planning function is selecting a few jobs and defining procedures for developing formal process plans and defined a series of operations. A less formal plan consists of simply a "build to print" instruction. Most major manufacturers require a format which spells out all of the manufacturing requirements, including material, operations, tools, fixtures, gauges, and inspection data. It also provides details about setup and fixturing, speeds and feeds, workpiece orientation, dimensions and tolerances, and step-by-step process descriptions, including QC.

Process engineers develop these plans on sheets summarizing the manufacturing process, which usually accompanies the workpiece as it travels through the shop. These summary sheets are called travelers or routers and are a necessary part of process planning.

2.1.2 Database Contents

Every workpiece, tool and fixture must have a manufacturing plan or set of plans. These plans must be stored in an easily accessible manner. There can be more than one plan for manufacturing a particular item, because different machines may be used or a special rework plan may be needed.

Each computer record should identify tools, fixtures, N/C programs, machines, setup times, piece times (labor and machine), and detailed operation instructions. Vendor operations and inspections must also be identified.

Materials, tools, fixtures, and other elements required for an operation should be specified and tracked to be sure that they are in inventory, scheduled to be made, or ordered in t ime to meet production requirements.

Routers , travelers, and other work control documents must accompany single workpieces or sets of workpieces in production. The paperwork must list the operations in summary form in a manner consistent with the plan. Workpieces for a particular job must be grouped in lots. Lot size can vary from one to the total order quantity.

Information defined in the process planning module serves as a basis for estimates and quotes. Labor vouchers are validated against the plan. Based on what the labor voucher shows, the production control department can estimate how the job is progressing and where trouble spots or bottlenecks might be. The plan helps production schedulers estimate the load on each workstation and foresee contention.

Standard times help job costing by establishing a baseline against which actual costs can be measured. Work performance can be measured on an equivalent unit basis, a frequent requirement for large contracts with progress payments.

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2.1.3 Start-Up Methods

There are several ways to begin orienting process planning toward computer augmentation:

• Produce a highly detailed process plan for every workpiece. These plans are prepared manually, then copied and updated as needed. To start, select several jobs and use a process planning method to prepare the paperwork for the master plan and the travelers. This approach has little impact on production and allows the shop to experiment with the software. It also facilitates training.

• Use the existing process planning system. Develop data conversion programs to move the data from the existing system to the new system. Data is moved all at once and everyone uses the new system immediately. Although this immediate conversion can put pressure on users, they have the advantage of moving from one automated system to another. This prior experience eases the transition from the manual system to the automated one.

• Develop a prototype process planning module, designed to gradually introduce the idea of automated process planning to the engineering department and to establish a standard method of defining plans and releasing work to the shop floor. This prototype is simpler than the finished system, but all of the basic information can be captured and transferred to the new system. An internal data processing department provides resources to support this kind of independent effort.

• Introduce automated process planning to the shop gradually. Keep a skeleton plan on the system, but develop detailed process sheets with word processing software on PCs. Thus, the most labor intensive aspects are handled off the system. Copies of the master plan, with all of the operat ion sheets, are kept in a master file and backup copies of the PC files are kept for security.

2.1.4 Educating the User

Process plans are the heart of any good system, but creating good plans is very difficult. Sharing information is the major challenge. For example, engineering departments do not always have the best information. Engineers must stay in touch with production control and shop floor foremen. Separate departments have a tendency to isolate themselves and to make decisions based on incomplete information. Access to a central database helps solve this problem.

Process planning requires identifying the best technical as well as the most economically feasible means of producing a part. Sequencing operations, selecting the right machine, and estimating the duration of each operation are among the most difficult pieces of information to collect or define. Rush or non-standard jobs are particularly difficult to handle.

Establishing standard times for operations sparks the greatest controversy. Engineers feel that, without actual timings or shop floor data, they are guessing. Operators feel threatened by the standards, which can create the impression of poor performance if set unrealistically high. Managers worry that some employees will slack off if standards are too low.

Most of these problems can be solved by education. As planning is implemented and work release controlled, shops begin to collect shop floor data against the plans. The original estimates are replaced with standards based on actual data collected. This relieves the burden on the engineering staff for collecting and analyzing data. Publishing standard times and explaining their use eases the concerns of operators as well as managers. Operators are able to evaluate goals and judge whether or not they are

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realistic. In some cases, managers are surprised to find that operators are eager to recommend improvements and identify problems once they understand what is expected of them.

Shops must accept the basic premise that the definition of the plan becomes the standard against which performance is measured. Therefore, it is extremely important to create plans carefully and follow them closely.

A major area of difficulty is the process of work release and determining manageable lot sizes. Introducing formal work release procedures requires each production run to have its own original traveler. Those in charge of work release have to learn to assign jobs to specific plans and create individual travelers for each lot of workpieces. Several problems typically occur:

• Some production control personnel create single lots for the entire order quantity, even when a large number of parts are to be delivered over a long period of time. These lots are obviously too large and impossible to schedule or track effectively.

• Some individuals create lots based on container size; e.g., if a tub holds eight pieces, a lot of eight pieces is created.

• Lots are created using the wrong process plans. Often, multiple plans for the same part exist, depending on what has to be done to the part. This situation creates the danger that the wrong traveler might be used and released to the shop floor.

Education provides the solution to these problems; e.g., a lot is defined as a quantity of parts in production that can be tracked and scheduled in some near term capacity. The concept involves determining lot sizes based on delivery requirements. One or more sets for shipping can be combined to make a single lot. Likewise, production control personnel can determine lot sizes based on the most economical quantity to produce according to delivery dates.

Customer orders with "as required" delivery dates can be a problem. Scheduling these orders is difficult because the quantities and delivery dates are not known. These orders are handled "on demand" and worked into the schedule as time permits.

2.1.5 Procedures

Establishing standard procedures and creating automated tools to support them is a lot of hard work but ultimately streamlines the process. In addition, keeping plans in a central place helps to meet the demand for documentation, planning, and traceability. Online displays allow users to view plans and travelers as they are being created.

The bill of materials lists resources for every operation. These resources can be other workpieces, various materials, tools, fixtures, or anything that is required to perform the operation. If the resource has to be made, a plan is developed and a resource-traveler created. In this way, a tree of plans can be constructed to correspond to the production requirements of a particular assembly.

Split lots are always a problem. The most common reason for splitting is to meet schedule demands of customers. The procedure to solve this problem provides traceability of lots as they split. When a lot is split, the last successful operat ion of the original lot is identified. Then one or more parts can be separated to form a second lot for additional processing. This method provides a history of the job through production.

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2.2 Selecting and Implementing a CAPP System

2.2.1 Approaches

Two of the most difficult questions confronting the selection of a CAPP system are:

• What system best suits my company's needs

• What steps are required to successfully install the system or systems chosen

The probability of one system's fulfilling all of a company's needs is relatively small. As one might expect, no single system performs every function required by a company. For example, some systems interface to design, through the ability to translate IGES (Initial Graphics Exchange Specification) files. These systems are able to communicate with C A D systems more readily than systems without this capability. However, companies manufacturing products to customer's designs have little control of design. They may not be as interested in the ability to perform design retrieval for productibility analysis and standardization. On the other hand, those same companies might be very concerned with the ability to transmit CAD data, CAPP instructions, and machine language instructions to the customer's plant or to distribute customer information throughout their factory or among plants in geographically diverse locations.

Moreover, the product manufactured might lend itself to either variant or generative CAPP systems. In generative environments, companies may wish to consider a rule base for design producibility as well as a rule base for manufacturing instructions. In variant environments the ability to direct process planners or design engineers to preferred practices is desirable. If left uncontrolled, variant systems may direct users to a number of similar designs or processes, but unless steps are taken to prevent it, the user may select a poor design or process on which to base the variant.

The mix of products manufactured may be an issue. In metal working environments in which G T and process planning originated, traditional G T codes perform satisfactorily. However, in companies producing printed circuit boards (P/CBs) or complex electromechanical devices, classification by shape may be unimportant , or perhaps useless, while the classification of other features, such as the components contained on a P/CB, will require the classification power of a relational database to perform effectively. Further, in these instances, ANSI SQL or other relational database application languages are often required to make use of the data classified. For example, it is not always the case that a design or manufacturing rule may be based solely on the presence or absence of data in a single classification field. In most instances, manufacturing rules are contingent on a variety of characteristics. So, for example, when planning the manufacture of a P/CB, one might wish to know whether the components mounted on the board may be inserted automatically by machines. A component that is normally machine insertable, however, may not be machine insertable, if it is located in close proximity to a larger component that interferes with the insertion head. Because many large components are not adaptable for insertion by machines, they must be inserted by hand. In this case, the application language rules would call for the insertion, if the larger component were absent or located at a distance sufficient to safely insert the other component . In the absence of these conditions, the process instructions would direct the individual along a different course.

Work measurement is an issue at some companies because of union agreements, compliance with military specifications, or incentive payment systems based on piecework or other forms of measured output. In these environments, the ability to standardize production methods and easily revise labor standards is essential. The situations exist in competitive markets typified by repetitive production, such as that found in consumer products.

In other environments, one-of-a-kind or custom designs produced infrequently make labor standards a

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relatively low-priority item required only for project control. In these very different environments, the automated capability to measure human or machine-paced work will be weighted differently.

Another factor compounding the selection decision is the difficulty involved with assessing the strengths and weaknesses of competing systems whenever they approach the problem from different directions. Many potential CAPP users, for instance, have situations in which both variant, generative, or semigenerative approaches are appropriate. In these instances, evaluating a purely generative system against a purely variant system can be quite difficult. Likewise, the differences between systems' capabilities to interface with other business systems, such as Manufacturing Resource Planning (MRP), also vary considerably, further complicating at tempts to make a solid evaluation.

An alternative approach, then, is to identify the business needs to be addressed by the systems under consideration and assess the degree to which competing systems meet business needs. This approach avoids fruitless a t tempts at comparisons between systems that approach the problem differently and also identifies areas in which perhaps more than one system will be required in order to meet all important business needs.

2.2.2 Identifying Business Needs

An approach to identifying business needs utilized by major consulting, systems, or engineering firms involves flow charting the business systems to which the CAPP system must interface. The procedure involves a system "walk-through" from point of origin to completion, while, at each stop, interviewing the system users, collecting the documents and other information requirements used by the system, and finally, flow-charting the information processing and distribution of documents and information throughout the system.

2.2.2.1 System Walkthrough

O n e manufacturing engineering manager trained in systems design was amazed at the system interface required to replace paper, pencil, and file cabinet process planning systems with a computerized one. Even though his objectives were limited to automating the manual work, the information interface to other business systems proved much larger than one might anticipate for so modest a goal. As pointed out earlier, this is because the process plan contains information that permeates the business operation. Accountants use it to value inventory and as the basis for standard costs. Standard costs, in turn, affect pricing in the market. The difference between the market price and standard cost establishes profit from the sales. Usually, estimating or quoting activities for new orders and delivery lead times are based on manufacturing methods.

As these systems are automated, the cooperation with data-processing elements of the business must grow. Communication of the information contained on the process plan must switch from paper to electronic media. Now, communication protocols and the timing of information transmissions become important. Because other data-processing users may now access the system, activities that previously lacked a time dimension may now be constrained by one. For example, electronic process plans may all be required to be up to date and complete during the evaluation of a year-end inventory, or routing files may be absent or out of date when an M R P run is under way. In paper and pencil systems, the most recent copy on file always served this purpose. In electronic systems where only one image exists, it cannot be "locked out for update" when required by other elements of the business system.

Many departments within the company rely on data contained in the process plan. Production scheduling and control systems rely heavily on information within the process plan for lead time calculations and capacity requirements for personnel and productive equipment. Make-buy decisions affect the purchasing department, engineering bills of material, and process instructions. On the manufacturing floor, routings

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may be used to report direct labor and material applied, trigger vendor operations, procure outside services, and record quality transactions such as scrap, rework, or acceptance into finished inventory. In some companies the process plan is used to report personnel-related information such as attendance or tardiness. In incentive or piecework environments, it plays a direct role in the calculation of employee earnings.

The raw materials from which products are made, the perishable tooling of materials used in its production, and the capital equipment upon which it is produced constitute the largest source of investment for most manufacturing companies. When this information is compiled and distilled by management, strategic decisions affecting the company's course and position in the market are made.

The accuracy of the process planning database is crucial for sound business decisions, and the interface to other business systems is important even when CAPP's immediate goal is limited to automating the functions of paper, pencil, and file cabinet.

2.2.2.2 User Interviews

The most important step at each stage of the process consists of interviewing the users of the system. These interviews are a source of invaluable information on the many small ways that improvements to the system can be made. One should not be surprised to find that much of the data collected can be eliminated because it is no longer utilized by any downstream process, many things currently being done manually might be better done electronically, and the throughput time required to sequentially process through a paper system compared to that required for processing with an electronic system can be dramatically reduced.

An objective of the system designer should be to provide each user of the system with only the information required. No information should be collected that is not utilized elsewhere in the processing system. Likewise, no useful piece of information should be omitted from the formal system design and accomplished through informal methods. At this state of the system design, interviews with users are important to gather information and understand how the system works so that the CAPP system can be successfully interfaced. Later, when the design of the new system nears completion, the system installer will once again return to these users to review the proposed design and verify that the planned system meets their needs.

2.2.2.3 System Flow Chart

It is good practice to start at the origin of the information system. For most process planning systems this will be at the point of quotation or order entry. From that point, one should follow the processing steps through to the final system transaction and output.

At each stop, it is important to record the information input to the process step, the method by which the information is processed, and the output of that process. Flowcharts may be used to document the channels through which the processed output is forwarded. This is accomplished by interviewing the users at each step in the process and collecting completed forms used to capture, process, or transmit information. Where electronic systems are involved, the same steps take place; however, the information is captured in the form of software documentation for the electronic systems employed. Often, however, electronic systems are not documented or are incompletely documented. In these instances, flowcharts which identify each piece of information and the way in which it is dispositioned must be constructed by the systems analyst.

This step, while time consuming, is very important. When the new CAPP system is installed, users of

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every business system to which it interfaces must receive the information required to perform their job or function. These flowcharts, forms, and software documentation assure that their information needs are met by the new CAPP system.

O n e of the ways in which this assurance is provided comes from the forms collected. As the manufacturing engineering manager, mentioned earlier, progressed through sales order entry and the various downstream departments , he noticed that many of the forms in use no longer fit the information processing system. In some cases, personnel simply used old forms because a supply of several hundred still existed. These older forms often lacked a formal method for capturing important information and, conversely, often provided blocks for information that was no longer useful.

The reason for taking examples of completed forms at each step in the business system is to identify instances in which useless information is captured and not subsequently processed. Conversely, whenever annotations are made on the reverse of forms, the margins of forms, or through informal channels not provided in the formal business system, one can take steps to ensure that these deficiencies are corrected and formally addressed in the revised system.

New business forms are very cheap when compared to the risk of processing incomplete information, missing a customer delivery, or incorrectly pricing a major job. Do not succumb to the temptation to use old, inappropriate forms simply because several hundred or several thousand exist in the office supply's storeroom. Throw them out and design forms appropriate to the business needs of the system. Take advantage of opportunit ies to install better controls through the use of serially prenumbered forms with controlled distributions, whenever the importance of the activity being controlled, such as purchase orders or manufacturing orders, so warrants.

After the information is collected, it must be distilled and digested so that the business system is understood. This is accomplished through the use of flowcharts. Flowcharts record the activity that takes place at each step, documenting the information input to the activity, the processing that takes place, and the information content of the output distributed from the activity. Flowcharts explain both the processing of paper and the electronic-based business systems. As our manufacturing engineering manager proceeded through the various departments, he documented the information that was received by each user of the system, what he or she did with that information, collected examples of the completed forms used in processing the information, and noted where the information was sent.

2.2.2.4 System Design

With the systems "walkthrough" completed, the system installer is in a position to construct a preliminary system design based on the information requirements that must be met by the CAPP system. Understanding of the information requirements that the CAPP system must provide to other business systems and the timing and controls necessary for each process step at which that information must be exchanged is a necessary function of this process. This understanding helps the installer to specify the minimum capabilities of the CAPP system as well as other timing and execution issues that must be addressed prior to installation of the system.

To complete the preliminary system design, the system installer will require the assistance and participation of a number of other professionals. For example, expertise in the data processing, accounting, and materials area is often required in order to assure that the redesigned system performs adequately. With input from these personnel, a detailed system specification can be written and implementation activities coordinated among several departments. The preparat ion of this specification may be expected to touch most, if not all, of the company's business systems.

In addition to capturing and providing a processing system and destination for all the information, system

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design tradeoffs must also be evaluated. System architecture is often an area in which many alternatives are available. In single-product systems, access may be controlled by the system manager through the assignment of various file, field, or device privileges appropriate to a variety of users. In multi-product operations, however, coordination is much more difficult. Decisions must be made to determine what data is to be shared among various products, what is to be product specific, and how all the data within the system is to be secured, maintained, and recovered if lost.

The transition from paper to paperless systems operation adds another dimension to the system design effort. Sensitive or classified data must be protected. Since such data is most vulnerable during transmission, one may expect to be required to secure the entire area in which transmission takes place in order to satisfy the requirements of government security officers. Transmission on unsecured media is not likely to be permitted regardless of password security or encryption techniques employed.

2.2.2.5 Specification Review

The last and most important step is to review the proposed system specification with all users. Once again, begin at the point of origin and trace the system through to the end of processing. At each step, identify for each user where the information required for the performance of the task will come, how processing will take place, and how the information will be distributed subsequent to that processing step. While time consuming, this second iteration through the system is essential. It is rare that even the most talented, experienced system designers complete a workable system specification in one pass. By reviewing the detailed system design, insight can be obtained into the design, the alternative selected, and the advantages and disadvantages of the tradeoffs made enroute to the final design. Most importantly, the users provide a valuable check on the design assumptions around which the successful design of the system will depend.

2.2.3 System Selection

2.2.3.1 Survey Market

Several means exist by which a survey of commercially available CAPP systems can be made. A variety of seminars sponsored by professional societies dealing with CAPP, GT, and related subjects are scheduled annually and often provide an afternoon or evening in which attendees can view and discuss systems from various suppliers. Also, tool shows and expositions often provide the opportunity to see and evaluate various CAPP systems.

2.2.3.2 Identify Candidates

When the vendors who seem most likely to meet the needs of the business have been identified, a second screening may be made on the basis of literature provided by each vendor. On the basis of this review the three or four suppliers most likely to meet the needs of the business can be identified and examined more closely.

In order to make the final determination, the field is narrowed to the two CAPP systems that most closely meet the business needs identified in the preliminary design effort. Then the finalists are put through a number of steps, including site surveys, sales presentations, systems analyses, technical demonstrations, and formal proposals.

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2 3 Cost Justification

Although current CAPP systems are not intelligent enough to capture all the seemingly infinite number of variables that are associated with process planning, they are maturing and becoming more of an economically useful tool. As these systems grow in power and sophistication, they are becoming recognized as a "necessity" for those companies who wish to stay competitive in the future. Many large companies have delved into CAPP and found it to be economical in spite of some limitations and costs. As an increasing number of larger companies use CAPP systems from a growing number of vendors, a trend takes place that drives the cost and availability of such systems down within the grasp of medium and small size companies.

Regardless of size, there comes a time when a company in the market for a CAPP system needs to justify the cost of such a system. Before management commits significant dollars or resources in obtaining and implementing a CAPP system, they want to know if the benefits will outweigh costs. For this reason two questions need to be answered. How much is it going to cost, and what savings can be expected?

Questions pertaining to such things as acquisition costs of hardware, software, maintenance, training are straight forward. These can be readily obtained from a vendor. If the CAPP system is to be developed by the user, then software development cost, dedicated human resources, and implementation lead time are less concrete. Capturing cost of an in-house developed system is even more elusive. Some form of a project management system is usually employed. The scope of work is drawn up and the resources needed to support the work are estimated. From these estimated resources a ball park figure can be arrived at for the total system cost.

However, the question of savings becomes even more elusive than defining the cost of an in-house developed system. Some fortunate companies have a cost tracking system that is well developed and supported. This makes the job of estimating and tracking savings much easier. A good cost tracking system is used as a solid standard on which savings can be based and projected. A number of companies however, are not as advanced in their accounting methods and do not break out as many cost categories. Thus, they struggle to find an exact cost in their existing system.

A real problem with projecting savings is to determine how much work a piece of software as complex as a CAPP system will save in an area as all encompassing as process planning. After installation, system performance can be measured and compared with historical data, if that data exists. In this case foresight is needed first to justify the system.

2.3.1 System Analysis

A gas turbine engine manufacturer produces a wide variety of parts most generally characterized by complex shapes and tight tolerances. Due to the inherent quality and reliability requirements for aircraft propulsion engines and the complexity of design, process plans are very lengthy, complex and meticulous. A typical process plan ranges between 30 to 50 operations. Each operation contains machine tool used, perishable tooling, jig and fixture tool numbers, operation description, machining dimensions and tolerances, caution notes, specifications in a condensed form, speeds, feeds, depth of cut, and graphics.

The engine builder uses G T techniques. All parts are produced in one of four shops, namely, wheels, gears, cases, and sheet metal. Though this is not a complete breakdown of parts into "families of parts" as pertaining to G T it does significantly reduce the magnitude of searching needed to develop the complete process plan as well as benefit the shop floor in facilitating production.

The company examined the detailed requirements for a CAPP system and defined the modules needed to satisfy its design. Because of the interest aroused by this study, it became necessary to provide to management as soon as possible a complete project analysis with associated costs and benefits.

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A single engineer handled the analysis. The only other human resources dedicated were a few hours each week of an experienced process planner.

This in-house CAPP system development was labeled CAPE (computer-aided production engineering). Parts of the system were purchased from outside vendors, but for the most part, it is an in-house design. C A P E is an enhanced variant process planning system, which interfaces with the existing company database and integrates with all other departments and functions concerned with process planning.

2.3.2 Process Plan Analysis

The strategy used for cost analysis was simple: select a representative family of parts and develop a standard routing for that family. Next, compare and contrast the standard routing with the existing routings and carefully note all differences. This would be followed by an analysis of those differences to see what, if any, the cost impact would be. Lastly, the findings of the analysis would be applied to actual cost data for a projected cost savings.

Due to t ime constraints, only one part family was chosen for analysis. The family chosen was that of spur gears with a trepan configuration. This choice was made for two reasons. First, there was an existing classification and coding scheme in the gear shop with a significant number of the parts coded. Second, it was felt that spur gears would be as representative a part family as the shop could offer, considering the wide variety of part types. Seven parts fell within this spur gear family and were used for the analysis.

After the process plans were gathered, a production flow analysis was performed on the seven parts of this family. A matrix was constructed consisting of a vertical listing of the routing; i.e., a list in descending order of each machine tool used in the routing of the part. The horizontal axis of the matrix consisted of the respective part numbers of the spur gear family. The matrix had to be built one column at a time. Each operation for a part had to be as closely fitted and aligned to the previous part routing as possible. This was made fairly simple, due to the great number of common operations that are a natural outcome of G T families. The operat ion number was placed at the intersection of each part number and machine tool. Operat ion numbers are assigned sequentially, regardless of machine type or process. The load center number which appears beside each operat ion takes the place of what many companies call an operation number.

Following the matrix construction another vertical column was added. This column was a machine class or process type column. An example of this would be calling out an operation as using a medium horizontal N/C lathe as opposed to a specific company name and model type N/C lathe. This column was added for use in generating a graphics flow chart of the production flow on a higher level to avoid a chart with too much detail and clutter.

At this point, the experienced process planner was called upon to go through each routing in detail to create a standard routing. This was a time consuming task taking one of the three weeks allotted to this project. A process planner makes hundreds of calculations, judgments, and decisions to create a standard routing. Although the seven parts of the spur gear family were nearly identical in geometry and material, their routings differed considerably. The differences were because of a number of reasons, among which were obsolete machinery, changes in methods, new equipment, different approaches and preferences of the planner who created the routing, changes in tooling, and changes in company policy. From this careful examination of each routing, a standard process plan was created that would cover all seven spur gears.

The standard routing was then compared with the matrix created earlier, and the matrix was adjusted to reflect the standard routing. Operat ions were deleted, combined, and, in some cases, added to the matrix. The outcome of all the changes was a decrease in the number of operations. Before the analysis, there had been a total of 221 operations among the seven parts studied. After the standard routing was

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produced and compared, there were 201 operations among the seven parts. N/C operations were reduced from 14 operations to nine.

For demonstrat ion purposes and as a visual aid a flow chart was made of the spur gear family routing flow through the shop. This simple line and circle flow diagram was used to visualize the magnitude of changes that had taken place on the matrix. It is easier to verify a standard routing when all possible paths are laid out for easy visual access. In addition, this chart was also used in presenting the CAPP system to management. A network, if not too complex visually, is more easily understood in a meeting atmosphere than volumes of tabular data such as the matrix.

After the standard routing was created, the changes were transferred to the matrix. This resulted in moving, deleting, and adding operation numbers at the intersections of the part number and the machine or operation description. When this process was finished, all vacant lines were removed. The analysis discovered that a number of operations were performed in the same sequence from part to part with the only difference being the brand name of the machine to which it was routed, which led to further condensation of the matrix; e.g., four lines of medium horizontal N/C lathes with different manufacture names being combined into one line.

2.3.3 Cost Analysis

After the estimated percentage savings were calculated, costs were gathered. Baseline cost data in this case was from the previous calendar year for each task area. Cost data was gathered from a number of individuals and reports. In most cases, the information was present and accurate. Only in a few instances was a "best guess" made by an experienced person who had a good handle on the situation of that department.

The collected cost information was formatted on a PC using a spreadsheet software package. The format used was to group each major section; e.g., run-time, N/C, scrap. The percent of impact was calculated by the amount that each shop spent for a particular area compared with the total for four shops.

A phasing factor was added, which took into consideration the time each shop would require to move from the manual system to the CAPP system. The phasing was linear and reached 97 percent at its highest point in anticipation that a full implementation would not be realized due to various unforeseen conditions and circumstances. Savings for each shop were totaled as well as saving by each column or quarter for the different areas. This pattern was repeated for each of the areas.

Implementation costs included a combination of purchased software, hardware requirements, and personnel needed to design, implement, and maintain the total system over a period of five years. Wages and salaries were adjusted using a six percent per year inflation factor. Net savings per quarter were derived from the total savings less total costs. These net savings were then summed to a total net savings over five years.

2.3.4 Savings

Substantial savings were projected from this study. A rate of return was calculated at greater than 50 percent, with the pay back occurring in the eleventh quarter. With these figures it was deemed a worthwhile project to undertake. A presentation was made to management using these figures as well as the graphical flow chart of the spur gear routing as mentioned earlier. The outcome was a general approval of the C A P E system with further deliberation on the technical requirements of the software.

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3. Manufacturing Interfaces

3.1 A Distributed, Hierarchical Architecture

3.1.1 Process Planning

Manufacturing personnel are generally familiar with the organizational distinction between manufacturing engineering and production control. Manufacturing engineering has responsibility to generate the process plan. Production control has responsibility to manage the production activities, hereafter referred to as process control. Process control is the domain where product is fabricated, assembled, tested, and transported. It is also where the process plan is interpreted, optimized, executed, and monitored according to specification. It is the domain of process planning to specify the manufacturing process requirements in terms of sequence and content, and to arrange this data in a format acceptable to multiple process control subsystems.

Process planning is positioned between product design engineering and process control of the factory floor systems. Because the two domains share product and producibility data requirements in common, it is compelling to merge the product design with process design. Traditionally, this has not been the case. There is, however, a need to recognize the necessity for strong two-way integration between the two domains to support new product startup and producibility goals. While it ultimately is a goal to completely automate the generation of the process plan, this architecture does not require it. In fact, with the wide variety and increasing introduction pace of new manufacturing process technology, the practicality of one package meeting the data needs of all process control systems could likely become impossible. The architecture lays the foundation upon which process planning applications can plug in or out or be imple-mented or replaced, as required in an integrated environment.

Currently there is little integration of shared data across factory systems. Routes and bills of material are paramount to the integrity and proper revision control of the manufacturing process. When a revision is made to a process, this change should be automatically communicated to all affected systems. Currently, manually maintained, standalone systems requiring people to run around to keep them operating is the glue. For the future, manufacturing strategies must insist on integrating this reference data so that data changed at the proper source is appropriately communicated to all affected systems automatically.

3.1.2 Architectural Fundamenta ls

One of the most fundamental elements of complex system design is the architecture upon which it is built. Architecture can be defined as many things by many people, but at the very least it describes the system components, their interfaces, and their relationship to one another. Just as an architect designs the structure before it is physically built, so does the software architect design the system architecture prior to application development.

3.1.2.1 Interface Protocol Standards

In designing a building, the architect must adhere to certain standards, the purpose of which is to guarantee a level of compatibility between independently designed functions that have to interface with one another. An example of two independently designed components that ultimately interface is a wall socket and a lamp plug. Although the socket and plug perform different functions, they both have been designed to meet the same interface standard. Because a standard exists, a radio may be plugged in instead of a lamp without impact on the system.

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Because of standards, applications may be switched in and out, and as long as they do not violate their interface standard, the other system components are not impacted. This approach allows for flexibility in the implementation of a system where competing modules can be selectively implemented based upon requirements. A given application module may be replaced by another, but if the interface remains constant, the rest of the system should not have to change.

3.1.2.2 Data Server/Database

The architecture is data server rather than database oriented. In a database oriented architecture, the knowledge of the data structures have to be coded into the application. In a data server approach, applications obtain this reference data via data management interface calls. By doing so, one database product can be modified or replaced by another database product. As long as the interface call does not change, the application will not have to change. This also can open the way to a database machine whose sole role is to provide data storage/retrieval to any number of requesting client applications.

3.1.2.3 Function/Form

A house design is based upon the function that each room accommodates. "Kitchen" conjures a mental picture of a cooking facility. The basic function of cooking will remain the same regardless of the size or number of kitchens in the system. Whether a large stove or a small stove is requested, users know that it goes in the kitchen and not somewhere else.

This analogous approach provides great insight into how a complex system is designed. Within process planning, there are four basic categories of data: workflow (route), bill of material, quality, and equipment. These categories should be as distinct and well defined as a kitchen is from the rest of the house and understood as to their role in the process plan.

3.1.2.4 Common Support Tools

Within most systems, a common set of tools can be identified that are used throughout the system. These tools include networking, human interface, and data management. One such tool used extensively within the architecture is called the message bus. The use of this tool sets the stage for distributed processing and removes the knowledge of where on the local area network the cooperating application resides. This transparency is critical to the ability to move application modules to other computer hardware without having to make changes to the applications making the calls.

For an application to request service, all it has to do is call the message bus and pass the list of arguments using a predefined interface call. This would be analogous to our writing a letter (the list of arguments) and addressing an envelope. We do not care what the postal system does in delivering the letter, only that it reaches its destination in a timely manner. The message bus takes care of physically routing the packet of data to the appropriate destination.

3.1.2.5 Hierarchical Approach

The architecture assumes a hierarchical approach in positioning the process planning functions to minimize redundancy. Plant levels such as workstation, cell, and shop can be arranged in a manner similar to that of a traditional top-down organization chart. That is, a shop has any number of cells reporting to it; each cell has any number of workstations reporting to it, and so on.

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The above considerations are fundamental to the architecture discussed below. The architecture has made extensive use of a protocol standards, modularity of functions, and data servers, all based on the use of a distributed network message bus system.

3.1.3 Architectural Overview

There are three major subsystems within the process planning architecture. They are 1) the bill of description (BOD), 2) the process planning development hierarchy that is made up of functions used to generate the process plan, and 3) the bill of process (BOP). Data management interfaces are shown as horizontal lines between these subsystems. Figure 11 shows this relationship. Not shown are the command level interfaces connecting the subsystems within themselves as well as with external entities, such as process control and product design engineering.

Bill of

Description

Data Management System

Factory Level Generator

Shop/Center Level Generator

Cell/Line Level Generator

Workstation Generator

Instruction Set Generator

Bill of Process

Data Management System

Business Factory

Managerial > Shop/Cednter

Functional ^Cell/Line

Operation^ -Workstation

Recipe -^Automation

Module

PROCESS PLANNING DEVELOPMENT

HIERARCHY

Data Input | ^ Off Line Process Development • On Line PD _Process "Controllers"

Figure 11: Architectural Overview

3.1.3.1 Bill of Description

The B O D is a data management system focused on management of data that is independent of any specific process plan but may be referenced by any number of process plans. It manages relatively static data that describes product/parts, plant resources, and general process knowledge requirements.

G T coding and classification approaches would fall within this domain. Notice that this data remains constant and does not change unless there is a change in product design, plant resource, or manufacturing strategy.

3.1.3.1.1 Part

Product data must be provided by design engineering in a state acceptable to manufacturing. This requires an interface to the C A D systems, commonly referred to as the CAD/CAM interface. This includes part master and manufacturing bill of material (BOM).

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3.1.3.1.2 Plant

Plant data is owned primarily by manufacturing. It describes the resource capabilities, capacities, configuration, and control hierarchy of each plant entity. Data owned by finance systems, but considered to be plant data, are master data tables such as operation codes and employee identification numbers. Plant data is used by a number of systems including process modeling/simulation, short interval scheduling, capacity resource planning in M R P II, as well as other process control systems.

3.1.3.1.3 Process Knowledge

Process knowledge is a grouping that represents the rules, knowledge, and strategies that are used to generate/develop a process plan. The process rules are general in nature in that they may apply to any number of process plans and are therefore specific to a process in a global sense as opposed to a specific process plan. Only as the manufacturing process strategy changes do the process rules have to be modified.

3.1.3.1.4 Data Management Interfaces

Referring to the B O D in Figure 11, are two sets of data management interfaces. The interface diagrammed to the left is used to maintain the B O D data. This interface set supports a full range of database manipulation capabilities including creation, modification, and deletion of data. The functions responsible for maintaining this data can be either front-end terminal screen-based programs that retrieve and modify the data, or some other on-line data management system that uses this interface set to load the data into the BOD. However, the most desirable option when dealing with another on-line system is to place data servers on that data source thereby effectively integrating that system into the larger B O D data management system environment.

Regardless of the source of the data, any application can make data management queries conform to the protocol interface specification. This is the set of interfaces extending out of the B O D and into the process planning functions. As denoted by the one way flow of data, these support read-only data access. This guarantees that the data can only be changed by the originating source of that data. Therefore, the modify and delete interface calls are not allowed for use by the process planning function.

3.1.3.2 The Development Hierarchy

The primary responsibility of this subsystem is to generate a cost effective process plan that meets the product and process specifications as defined in the BOD. In a traditional sense, the process engineer has to interpret the product specifications, understand the process resources available, and, drawing from previous experience and process knowledge, generate the process plan.

Before the plan can be released, it must be verified and approved. To verify a plan may involve process simulations against a specific o r average product load using varying resource allocations. Verification may also take place to assure that all recipe programs are syntactically correct and that the data is of the correct format and meets the data requirements of the various process control systems.

3.1.3.2.1 Hierarchy

Different types of data requirements can be seen in Figure 11, depicting five levels of a production facility. Business data refers to the level of process plan data that plant wide systems such as M R P II would require. Managerial data refers to the level of data that is required by shop level subsystems to optimize,

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execute, and monitor production tasks across a process line. Functional data refers to the process plan requirements of the cell/line controller to specify the activities to be executed by its workstations. Operational data describes the coordination activities within the workstation. The recipe data provides the predefined sequence of activities required by an automation module.

The difference between on-line and off-line underscores the distinction between creation of the process plan and the access of this reference data by process control. The process planning components that create the process plan data are commonly referred to as generators; e.g. instruction set, workstation, cell/line, shop/center, or factory generators.

The automation module level is the level in process control that the instruction set generation addresses. The instruction set generator is probably the best understood component in the hierarchy. The output of instruction set generators are known as N/C programs, patterns, scripts, pick and place programs, automa-ted test programs, vision programs, and instruction sets for human operators. The major responsibility of the instruction set generator is to arrange the automation module program instructions into an optimal order, given the input limitations provided from its workstation generator.

For an instruction set generator to generate a program, it requires a data management interface to the B O D for product and standard set up information; and a data management interface to the BOP for contextual process plan development information such as setup requirements/restrictions and the specific component parts involved in the step. It also requires a command via the command level interface from its higher level workstation generator to initiate the data management interface calls and begin the instruction set development activity.

The responsibility of the workstation generator is to manage the instruction sets generated by its instruction set generators as well as provide operating data such as state tables, which the workstation controller requires. The workstation generator understands the relationships that exist between the workstations and their automation modules.

Each of the cell/line, shop/center, and factory generators perform the same type of responsibilities that the workstation generator performs. However, each generator addresses the data requirements appropriate at its own level. Each level has the capability of receiving and responding to high level commands, making decisions within the command limits allowed, and assigning and monitoring process planning tasks at its lower level.

The exchange of data between any two generators is termed as the command interface protocol. The generator that originates the command is the source and is at a higher level in the hierarchy than the commanded generator. Commands travel downwards and command responses are returned upwards. Therefore, commands travel vertically within the hierarchy whereas data management interface protocols travel horizontally. The types of data addressed by the command interface are:

• the part number of the part being built

• the material/components involved in the activity

• the equipment configuration (set-up) requirements

• a unique tag identifying the specific output process plan data so that subsequent communication between any two generators is guaranteed

Efforts continue on standardizing process control command level interfaces. The manufacturing message specification (MMS) is one such standard that, although targeted for relatively unintelligent devices, provides the command interface protocol concepts required for communication between process planning generators.

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3.1.3.2.2 Categories of Data

An analysis of the data needs of the process control system highlights four basic categories of d a t a -workflow (route), material, quality, and equipment. These categories of data are found replicated within the hierarchy as often as the data is required by process control, based to greater or lesser degree upon the need of the corresponding process controller. The process planning functions required to generate this data will exist at the same level that the data is required.

In process control, the workflow controller optimizes the production build schedule through use of short interval scheduling (simulation) techniques. This optimized list becomes input into an execution controller that controls the workflow based on run time status. A monitor controller compares the theoretical optimized schedule against the actual load status and makes a determination of when to take corrective actions including regenerating another opt imum build schedule.

The workflow generator in process planning must take the data needs of each of these workflow subsystems into account when it is generating the process plan. Typically, the data needs of the optimization controller are different from the needs of the execution controller; and the needs of the monitor are vastly different from the needs of the other two subfunctions, even though all three have some of the same data needs in common.

One common data thread across most process control workflow subsystems is the need of routing information. The workflow generator must be able to generate one logically consistent route definition across multiple subsystems, while meeting the independent data needs of each of these workflow subsystems. The route definition should also be able to support the branching logic for rework and other alternate next step scenarios, and arrange this in a hierarchical manner consistent with the way process control expects to assign the process plan to its process control hierarchy of controllers.

Once the workflow is defined, the three other functional categories of data can be developed and associated to a specific point within the workflow definition. The material generator working off of the route definition determines the consumption poin t -somet imes called an operation or s t ep -o f every component part listed on the manufacturing BOM. The quality generator must provide the data necessary for process control to monitor the process and to determine what, if any, action should be taken to resolve an unacceptable quality problem. The equipment generator among other things specifies the number and type of tools required to perform the task, the tool wear characteristics-used by process control to track preventive maintenance criteria, and the recipe data required by the technology dependent automation modules.

3.1.3.3 BOP Data Management Systems

The BOP data management system maintains the process plan data generated by the process planning generator functions. It is a logical data management system in that the data may very well be physically stored closest to its ultimate point of use. The approach taken recognizes that workflow (route) definition provides the framework upon which all other process plan data is associated. When a point in the route is established, one can begin to associate detail data that helps describe the activity at that process point.

As such, the BOP must be capable of modeling a hierarchical route where a route step at one level can explode into a subroute composed of a set of steps describing the lower level route requirements. As shown in Figure 11, each level within the BOP hierarchy addresses its own level of process plan detail data.

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Once a step in a route has been defined, at tr ibute data can be associated to that step by the use of "views." A view defines some amount of data that describes what is to be done by a subsystem at a step. If it were a transport system, then the data associated to the step will be of the content and format useful to the transport controller to execute its requirement. Another subsystem may be involved in the same step but for a different purpose; e.g., the M R P system that is tracking work in process and labor would require a different set of data that would describe the step requirements in the content and format acceptable to M R P .

View data can be of any content and format required by a workflow optimizer, workflow execution module, workflow monitor, material controller, quality controller, or equipment controllers, including route step data, a recipe, a list of tools required, fixtures, graphical/textual work instructions, and data collection requirements. Giving a group of data a view name provides a way to store and retrieve process plan data. It can be stored and accessed by referencing the view name of the step in question.

3.1.3.3.1 Data Management Interface

Because of the need to appropriately model the various subsystem views of data and represent it hierarchically, a general interface to read and write process plan data to and from the BOP data management system has been devised. The BOP has two sets of clients. Internal clients, such as process planning generators, have read/write access because of their role in the generation of the process plan. External clients, such as process control, have read-only access since their role is to execute the process plan.

There are four basic read-only call interfaces used typically by process control subsystems to obtain route and other workflow related data. G E T _ R O U T E is generally used when the route data is batch loaded as a private route copy into another subsystem. This might be done to download a workcell route to a vendor specific FMS subsystem. If this were the case, then "FMS" could be the view name and the group of data required by the FMS could be retrieved by G E T _ R O U T E .

A run time interactive scenario is also supported when process control subsystems request route data on a step by step basis, as each step is completed. Run time requests use GET_FIRST_STEP, GET_ALL_NEXT_STEPS, and GET_NEXT_STEP. This approach frees up the requirement of the subsystem to maintain a local private representation of its routing requirements and puts the data caching back into the hands of the BOP data management system.

The same approach can be taken to define the interface calls that support the process planning generators '

ability to create, modify, and delete BOP data.

3.1.4 Integration to External Architectures

As important as it is to have a well structured process planning architecture, strong integration must also exist with the product design architecture. Figure 12 highlights how this integration can occur by use of the message bus.

At the top of Figure 12 is a series of interfaces to external architectures such as product design engineering, order transaction processing (for job shop/customer order specific requirements), producibility, process control, and other systems/functions external to the process planning architecture. Each of these architectures must be tied into the message bus using an agreed upon set of interfaces, thus achieving a closed loop system. The formats of these interfaces need to be general in nature because they are expected to support a wide variety of data transmission requirements.

Use of the message bus allows for a distributed environment where generators can be scattered throughout

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Product Design

Engineering Producability

Order Transaction Prooessing

Process Control

Process Planning Interface Message Bus

τ τ Annotated

Product Data

Product Data

Product ECO/ECR Change

Process ECO/ECR Change

Notification Notification

Customer Order Rqmts

1

Bill of Description

(BOD)

Process Plan

Detail Data

Process Planning Generators

1 Bill of

Process (BOP)

Figure 12: Process Planning External Architecture

the network. And because this generally means distributed databases, a basic problem involves keeping the system updated to the most current information. That problem is solved in the process planning architec-ture, as data is changed by one subsystem, notification of that change is "broadcast" via the message bus to all affected systems.

The message bus is a utility which guarantees delivery of the broadcasted message to any subsystem which has previously registered itself as an interested party for a particular broadcast message type. The broadcast message can contain all of the data associated with the change, or it can contain pointers that map back to the change data.

In the first scenario, the message is looked upon as a "push" of data to the subsystem. Generally this approach is used when the content of data is minimal. On the other hand, if the content of the data is great, then a "pull" approach may be preferred which gives the individual subsystems the ability to request the changed data at some convenient future moment.

The pull approach is used in the process planning architecture to obtain product description data from design engineering architectures as well as customer order information from order transaction processing systems. A notification of E C O / E C R (engineering order/change) product data is received as a "pull". This means that the detail product data is not passed as part of the notification message but is subsequently pulled into the B O D which manages among other data, the raw product detail data.

Once product data is in the B O D , it is checked for completeness. If the data is found lacking, then a subsequent unacceptable broadcast can be made back to the CAD/CAE source requesting the modifications to be made. If it is extremely critical due to time or cost constraints, then it may be annotated as long as the annotated product data is broadcast back to the true source/owner of that data, the product design engineering community.

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The process planning generators then perform their value added functions by merging the B O D data into a consistent process plan. The process plan data is physically stored and managed by the BOP data management system. Once the process plan is complete, notification that the process plan has been released is broadcast via the message bus. Any interested party can then retrieve the released process plan data via the message bus using the standard data server interface calls supported by the BOP.

3J2 An Integrated Scheduling System

3.2.1 System Overview

An automatic CAPP system based on G T concepts has been developed and combined with a group scheduling algorithm called key machine loading (KML) to form an integrated computer-aided process planning and scheduling system (ICAPPS). New concepts, like part machining surface set (PMSS) and cell machining surface set (CMSS) proved effective in combining the automatic process plan generation with GT. The KML algorithm guarantees no-idle time for key machine tool and minimum lead time for the job. The integration of CAPP and scheduling is accomplished through the use of the cell machine loading and alternatives algorithm (CMLA) and scheduling source file (SSFL). This allows the system to modify the process plan automatically and thus, to avoid possible conflicts when changes in job orders and machine tool allocations occur.

3.2.2 CAPP and the Process Plan

Generally, CAPP and scheduling algorithm are performed separately. And yet such an integration is necessary, if modification of the process plan due to scheduling conflicts is to be carried by the system. This, in turn, would lead to the increased efficiency of those two important functions linking CAD and CAM. The task of integration is a difficult one, judging even from the fact that process planning is concerned with technical requirements, while scheduling is concerned with the time factors.

In practice, modification of the process plan sheet is routinely necessary, because of the need to utilize alternative machine tools. This happens either because of overloading or breaking down of some machines or because of changes occurring in the job orders. An automatic search for the most appropriate alternative machine tool and subsequent modification of the process plan constitutes the rationale for the development of an integrated system. The automatic process planning generation is combined in this system with G T concepts as are some other new approaches.

3.2.3 ICAPPS Subsystems

As can be seen from the block diagram in Figure 13, the ICAPPS system consists of three main

subsystems:

• the process planning generator • the key machine loading algorithm • the operation planner

The CAD database is a common database used by CAD and CAPP. A small database is established to store part geometry data and technical requirements. The boundary representation of the solid geometry model is chosen to describe the parts. In the boundary m o d e l a face is defined by a list of edges, each edge being represented by two vertices. This is a general rule; in a real system, some special faces can be defined by conventional rules.

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Design CAD

I Geometric Technical

Model 1 Files

1

Technical Drawing

Design CAD

I Geometric Technical

Model 1 Files

1

Technical Drawing

PPG f

PPG

PMSS Generator

PPG

ψ CMTT File

— > •

Machining Sequence and

SSFL Generator <

CMSS Files

CDB — > •

Machining Sequence and

SSFL Generator < PAEK Rules — > •

> 1

KML Algorithm

Fixtures

Tool Files

CDB

Operation

Planner

CNC Tape Files

Process Plan Sheet and Job Order

PPG - Process Planning Generator PMSS - Part Machining Surface Set CMSS - Cell Machining Surface Set SSFL - Scheduling Source File PAEK - Production Axioms and Experience Knowledge KML - Key Machine Loading Algorithm CMTT - Cell Machine Tool Table CMLA - Cell Machine Loading & Alternatives CDB - Cutting Data Base

Figure 13: ICAPPS System

Technical requirements can be divided into the index data and technical data. Index data contains indices

of brief information about all faces to be generated, such as shapes and surface roughness. It is easier to

extract all faces by using the index data than by comparing the part geometry data with its blank data.

Therefore, it would be advantageous to use the index data when a part and its blank are complicated.

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3.2.3.1 The Process Planning Generator (PPG)

The functions of the PPG are:

• to extract faces from the boundary model and to integrate them into the PMSS

• to compare the PMSS with the CMSS to find the best group of machine tools

• to generate an approximately opt imum machining sequence based on AI techniques and optimization criteria

• to estimate the machining time for parts on every machine tool and to produce a scheduling source file

The PPG obtains information from the data files, and functions as described below.

3.2.3.1.1 The Part Machining Surface Set (PMSS)

The PMSS is a set of surfaces to be generated through machining in the order which is arranged according to certain rules. Every machining surface or element of the PMSS is expressed by the shape symbol, size, and necessary technical data. The PMSS provides all essential information of a part for process planning. The technical requirements are represented by the accuracy and surface roughness. There can be the accuracy of size, shape, or position. The level of the accuracy-high or economical -depends on the actual situation in the job shop.

There are two rules for arranging the order of PMSSs for rotary parts: from left to right for external surfaces and from right to left for internal ones. For prismatic parts, the rule is from the datum plane to the top plane, with holes and slots included between the planes. Through the extension and combination of these rules more complicated PMSS can be arranged.

3.2.3.1.2 The Cell Machining Surface Set (CMSS)

The CMSS is a set of preselected surfaces which can be machined by a group of machine tools. In a job shop, only a part of the functions of a machine tool is used. The machining operation is related to tools, fixtures, and attachments. It is necessary to consider them when analyzing the shape generation on machine tools in the process of selecting a set of feasible surfaces to be generated by a cell. This set of surfaces forms a CMSS. The main parameters used to represent the CMSS are similar to those used in PMSS.

3.2.3.1.3 Extracting Generated Surfaces

The process of extracting surfaces to be generated is shown in Figure 14. At first, all faces to be generated are extracted from the part geometry model, then they are integrated into the geometry description of machining surfaces (GDMS) according to integration rules. Once G D M S is formed, it will be combined with technical data to form a machining surface. Finally, by repeating this process, the PMSS is generated.

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Extract all faces to be generated according to

the index data

Data file for all faces to be generated

Integr. Rules

technical data to form a machining surface

ι End

Figure 14: Extracting Generated Surfaces

3.2.3.1.4 Finding the Best Cell

Generally, cells can be divided into two kinds: that for machining rotary parts and that for prismatic parts. When a part can be machined in one cell, this cell is the best choice. In order to find the best cell, the PMSS is compared with the CMSS. If the PMSS is included in the CMSSX (X is the cell number), then the CMSSX is the best cell. If none of the CMSS can include the PMSS, the CMSSY, which can include most of the elements of the PMSS and requires the minimum number of additional machine tools to complete this part, is the best cell. The next cell is selected on the basis of a neighbor principle.

3.2.3.1.5 Production Axioms and Experience Knowledge (PAEK)

The production axioms are logical and general concepts and can be used to make logical inference. They are the result of analysis of shape generation process on machine tools and methods implemented to guarantee part requirements. These production axioms are adapted to any job shop manufacturing system except for some special cases. The production axioms concern:

• the shapes of surfaces and corresponding machining methods and machine tools

• some fixed machining sequences for generating surfaces

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The experience knowledge usually deals with a particular manufacturing system and with the performance of an individual machine tool. It can be applied to:

• shapes of surfaces and corresponding individual machine tool

• typical machining sequence for a surface in a particular manufacturing system

• other constraints (tools, fixtures...)

3.2.3.1.6 Cell Machine Tool Table (CMTT) and Cutting Database (CDB)

The C M T T is used for selecting the best machine tool from the point of view of the best manufacturing performance. In order to create this file certain rules and criteria have to be established. The data for CDB comes from industrial practice.

3.2.3.1.7 Machining Sequence Generat ion

The information obtained from the data files is used to generate the machining sequence. For this purpose AI techniques and optimization criteria are applied. AI techniques involve backtrack search strategy and production rules which are based on the production axioms and experience (expert knowledge), which are used to select the machining sequence of some surfaces. After this step, there are generally several surfaces left in the parts, which need to be machined. Optimization criteria is used to minimize machining t ime of the remaining surfaces. This criteria depends on a number of factors, including total length of a part, average diameter, width, cutting length, cutting speed, feed rate, and material.

Some of these factors can be treated as the main factors. In this system, the cutting depth, d, and the cutting length, 1, are considered as the two main factors. According to the variations in d and 1, several machining sequences can be produced, from which the best one can then be selected.

The procedure of process planning can be divided into two steps. The first step deals with the surfaces which require high accuracy and low surface roughness. The second deals with those whose accuracy and roughness are economical to achieve. Every step has many substeps which vary from rotary parts to prismatic parts.

The process planning generator will estimate the machining time on every machine tool on the basis of the similar principle and will produce a data file called scheduling source file (SSFL) for scheduling. The estimation depends mainly on the experimental data in a job shop. An example is shown in Figure 15.

3.2.3.2 Key Machine Loading Algorithm (KML)

Generally, a load unbalance exists among a group of machine tools. A machine tool loaded more than others is called the key machine tool (KMT). The K M T with no idle time might ensure increased productivity in some cases. The KML algorithm is based on this idea and is constructed to guarantee that key machines have no idle t ime and the job can be completed on due date under a minimum lead time when batch jobs are scheduled among a group of machines.

The K M L algorithm uses the C M L A file. This is an important file for integration of CAPP and scheduling. This file gives information regarding job starting time and completion time, machine loading, and alternatives. The modification of the process plan sheet depends on this file.

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CDB

CMTT

Blank Data

i PMSS Files

I Compare PMSS with CMSS Determine The Best Cell

I Select Finishing Methods and corresponding MT Select Allowance

I Determine Optimum MQ Select Economic Methods and Corresponding MT

I Estimate Machining Time on Every MT

I Primary Process Plan Files Scheduling Source File

CMSS Files

MQ - Machinging Sequence MT - Machine Tool

Figure 15: Flow Chart of Process Planning

Jobs can be ordered based on the priorities fixed according to the due date. A batch of jobs is set on the same due date. In the batch job case with K M T as the first machine in a group, the KML algorithm minimizes the total flow time T f, then calculates the minimum lead time T m which is given by

T m = T f - T p,

where Τ is a certain time period.

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If T m is negative, no lead time is necessary.

In cases when K M T is not the first machine, after the algorithm minimizes flow time T f, the minimum operation time T k m which guarantees that K M T has no idle time, is calculated along with the new completion time for all jobs. The new minimum lead time T m is then calculated:

T m = T k m + ( T c - T p) ,

where T c is the last job completion time on the last machine.

When scheduling random jobs among cells, KML uses a dispatch rule called FCFS-A, where A means alternative. In this case, the algorithm deals with two problems:

• scheduling jobs among all cells if some machine have enough idle time

• cancelling some jobs in order to insert some urgent jobs

3.2.3.3 The Operat ion Planner

The Operat ion Planner has the following functions:

• selecting cutting speed and feed rate and calculating machining time

• modifying "machine loading table

• selecting tools and fixtures

• printing the process plan sheet and job orders

• producing CNC tape file

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4. Applications

4.1 Machined Cylindrical Metal Parts

Computer managed process planning (CMPP) is an advanced process planning system for machined cylindrical parts. While CMPP is a partial implementation of CAPP technology, the concept can be extended to other applications.

CAPP typically addresses up to four process planning functions: sequence of operations, tolerance control, reference surface selection, and process plan output . CMPP is a generative system that addresses all four functions. It is unique due to the fact that the software and complete documentat ion are available to U.S. companies and government organizations at no cost.

4.1.1 Characterist ics

The characteristics of CMPP are:

• Genera t ive- I t develops process plans rather than simply recording operator decisions.

• Interactive-Interactive changes to the process plan can be made by a process planner, if desired.

• Manufacturer Independen t - I t is not dependent upon any one manufacturing process philosophy. It can be used by different manufacturers on different type parts.

• Process Decision Models U s e d - U s e r dependent process decision models, written in an English-like language that is understood by the system, provide manufacturing logic for part families.

• Computer Part Modeling U s e d - A process plan is developed, operat ion by operation, to transition the raw material into a finished part based on a detailed description of the part and raw material.

4.1.2 Geometric Coverage

CMPP concentrates on the capability to deal with cylindrical surfaces and features. However, some noncylindrical features are also handled, but less completely than the basic cylindrical geometry.

• Cylindrical Surfaces-The system handles diameters, faces, tapers, and circular arcs

• Cylindrical Fea tures -Fea tures such as grooves, recesses, reliefs, and notches are supported

• Non-cylindrical Fea tu re s -O the r features such as holes, gear teeth, windows, flat slots, and splines are also supported along with functions such as heat treating and surface finishing

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4.1.3 CMPP Major Components

Functionally, CMPP uses four input sources and provides three outputs (Figure 16). The inputs are: part data, process decision models, machine tool data, and user interactive instructions. The system outputs a routing sheet, dimensioned operations sketches, and a tolerance chart.

Process Decision Models!

Part Data"

Machine jData

Computer Managed Process Planning

(CMPP)

User

Routing Sheets

— • Tolerance • Chart

Dimensioned Operation Sketches

Figure 16: Functional View of CMPP

CMPP Software is composed of three major components: database system, part input system, and processing planning system (Figure 17). It performs four functions: generates a summary of operation; selects surfaces for dimensioning references, clamping and locating; calculates machining dimensions and tolerances; and outputs process documentation. The database and part input systems are not strictly process planning components but are necessary in order to plan a process. The components of and functions accomplished by the software are described in the following paragraphs.

Figure 17: Major CMPP Components

4.1.3.1 Database System

The database system provides the manufacturer independence for CMPP. It builds local files of user dependent manufacturing logic and parameters. As shown in Figure 18, it consists of four files.

• The Manufacturing Vocabulary File lists the local manufacturing vocabulary terms that may be used to process decision models. It is composed of the English-like description of each term.

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• The Machine Tool File lists the machine classes and individual machine tools within each machine class of the user's workshop.

• The Cut Parameter File contains data on the machine tools ' metal removal and tolerance holding capabilities.

• The Process Decision Model File contains local manufacturing logic. A process decision model states manufacturing rationale for determining the sequence of operations of a part. An English-like, problem oriented Computer Process Planning Language (COPPL) is used to define manufacturing practice for families of parts. However, the system does not require a specific G T coding system for part families. COPPL process decision models are compiled into CMPP-executable form, stored in the database, and executed for individual parts during process planning. The COPPL language uses an open-ended vocabulary of manufacturing terms. This vocabulary can be extended to include terms required by a particular user. Each vocabulary term has a "definition" which is understood by the process planning system.

Define Vocabulary

Compile Process Decision Models

Build Machine Tool File

^ PROCESS

PLANNING

SYSTEM

ι •

Build Cut Parameter File

Figure 18: Data Base System

4.1.3.2 Part Input System

The part input system (Figure 19) receives part data and constructs computer models for use in process planning. Part data input is a three-step process: initial part data collection, part data editing (data can be completed or changed), and generation of an internal CMPP part model from edited part data.

Each model is a detailed description of a part and the raw material from which it is fabricated. The model describes each surface, feature, dimension, tolerance, and notes. The system is designed for interactive part data input, so that it can be used as a standalone system. However, it can also be interfaced with a C A D engineering database for greater effectiveness.

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Collect Part Data

Edit Part Data

Build Part Model

PROCESS -PLANNING SYSTEM

Figure 19: Part Input System

4.1.3.3 Process Planning System

The process planning system (Figure 20) applies the manufacturing practices and resources defined in CMPP to a part to produce a process plan. The four technical functions are a summary of operations, reference surfaces, stock removal analysis, and process data.

Generate Summary of Operations

Generate Summary of Operations

1 Select

Reference Surfaces

Select Reference Surfaces

Calculate

Dimensions & Tolerances

Output Process

Data

Figure 20: Process Planning System

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• A Summary of Operat ions is generated by executing a process decision model. The model determines the operations in sequence. Operat ion description, machine type, setup orientation, and list of cut surfaces are generated for each operation. A summary of operations can also be produced without a process decision model by interactively specifying each operation. The summary of operations is presented in a matrix format so that each horizontal line describes the operation, machine, and surfaces/features affected. Each vertical line designates the manufacturing steps which produce an individual surface or feature of the part.

• Reference Surfaces are determined after the summary of operations has been generated. Surface selection for dimension reference, clamping, and locating for each machining operat ion is provided by execution of decision models or interactively.

• Dimension, Tolerance, and Stock Removal Analysis is performed as the third step. An initial starting tolerance is assigned to each cut and tolerance accumulations are calculated. When necessary, these tolerances are selectively tightened to meet tolerance requirements. This adjustment is made by a sophisticated algorithm with the objective of optimizing tolerance capabilities of shop equipment. Toleranced stock removals are then calculated, based on raw material tolerances, machining tolerances, and stock removal capabilities of machine tools. Potential problems of insufficient stock removal are diagnosed and flagged for interactive resolution during this step. Finally, nominal stock removals are used to compute nominal machining dimensions for each cut.

• Process Data, the final output , includes a printed routing sheet or sequence of operations and operat ion sketches, and tabular tolerance charts. The sketch is a not-to-scale drawing of the workpiece with cut surfaces highlighted by heavy lines. Surfaces not yet formed are shown as dashed lines inside the workpiece outline. Toleranced machining dimensions for cuts in the operat ion are included on the sketch.

4.1.4 CAD/CMPP/CAM Integration

Although designed to opera te as a standalone system, CMPP achieves maximum advantage when integrated into a CAD/CAM system. Use of part data from an engineering database; output of process documents to a graphics system; and use of output data for tool design, N/C programming, and other manufacturing services maximizes its usefulness. Thus, CMPP offers benefits in process planning, other manufacturing services, and the shop. Case studies and estimates indicate cost savings of 25-45 percent on process planning labor depending on the extent of use. Savings in other manufacturing services depend on the extent of use of the output data. Savings on the shop floor are the result of improved and standardized process plans. Although the percentage of savings is greater for process planning, total dollar savings may be greater in the other areas, due to their greater cost. Savings are especially significant when complex parts fabricated from expensive materials are produced.

4.1.5 Field Testing and Implementation

CMPP was field tested by three aerospace companies during the development process. Benefits verified in process planning include labor savings, lead t ime reduction, and surge capability. Savings of 25-45 percent are indicated, depending on whether it is implemented during low rate production or at full-scale production. This is consistent with surveys and studies of expected savings. No experience data is yet available on savings from manufacturing services on the shop floor. The survey and studies indicate that full integration would result in substantial dollar savings, although the percentage would be smaller than for the process planning function.

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Implementation of CMPP requires the commitment of top management, since it involves a radical change in the way of doing business and a significant investment in funds to develop the local database. CMPP users have found useful applications for portions of the technology, such as the tolerance module. Partial implementation in a variety of industries has been reported, including jet engine, control system components , gears, bearings, electric motors, petroleum, cutting tools, and electro-optical components.

Initially, CMPP was demonstrated on IBM and U N I V A C computers with Tectronix terminal and CalComp plotter. Use of CMPP on any other equipment required modification of the software. The capability to interface with CAD was demonstrated, but was not part of the delivered software; however, ease of implementation has been and is being addressed.

A contract was awarded to modify CMPP for application on Digital Equipment Corporation's (DEC) V A X computers. Additionally, neutral input and output interface will be implemented by the use of DI-3000 graphics software. These enhancements increase the transportability and reduce the implementation cost of CMPP.

4.2 Printed Circuit Board Assembly

CAPP systems today are either highly domain specific; i.e., deal with a specific technology or set of processes, or are shells that become highly domain specific when implemented. This reflects the fact that the underlying theory is inadequate to unify, in a practical manner, the diverse environments that exist in manufacturing. Until this theory is better developed, CAPP systems will remain very domain specific.

Interest in CAPP is also shown by the increasing number of commercially marketed software packages that are designed to assist in manufacturing planning. In addition to helping construct a process plan, some of these systems help in the production of shop aids, postprocessor instruction sets, and test routines. Moreover, several firms in military electronics have constructed rather elaborate CAPP systems to meet, among other things, a need for exhaustive, traceable documentation of the process used on each and every copy of a product produced. Indeed, any firm producing electronics which must be supported in the field over a period of years, needs to know the production process that was used to manufacture individual units so that decisions dealing with recall and modification can be made in the most economical manner.

4.2.1 The P/CB Assembly Task

The specific planning task that occurs in the manufacture of electronic equipment concerns the attachment of components to a P/CB. It is also referred to as P/CB assembly or "populating the board."

In comparison to metalworking and many other manufacturing processes, circuit board assembly is a relatively simple process. O n e begins with a bare P/CB and attaches to it various types of mechanical and electrical components and subassemblies. While some components are mechanically attached, most are first temporarily affixed to the board by inserting the leads of the components into holes drilled in the board or by the use of adhesives. The at tachment is made permanent by a soldering operation that can take various forms depending on the type of component that is to be attached. The soldering operation must also provide the connections required to make the circuits on the board electrically functional. The bare P/CB can be viewed as a component itself.

The process of at tachment can be accomplished manually, by robot, or by a variety of auto-insertion machines that are dedicated to the insertion of particular types of components. The first step in the planning task is the selection of an appropriate at tachment process. This selection is determined by the geometry of the part to be attached, the proximity of the part to other parts on the board, and a variety of thermal, chemical, electrical, and material handling considerations. While machine attachment generally

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produces higher yields than manual attachment, not all components can be economically attached by machine. Moreover, the economics of production require that some components be attached manually, even though they feasibly could be auto-inserted or inserted by robot.

In short, the process starts with a bare P/CB and a collection of electrical and mechanical components. The problem is to specify the manner in which each component will be attached to the circuit board.

4.2.1.1 Order of Operations

The general flow of work is shown in Figure 21 and proceeds as follows:

TEMPORARY ATTACHMENT

Clinching Wax

Flux Adhesive

Manual Robotic Fixed Automata

Manual Robotic Fixed Automata

/ Dip Machine

Pre-attachment Operations

Attach Certain Mechanical

Components

Dip Insertion

Perform] Coat Tin

Leads

TYPICAL COMPONENTS

Latches and other mechanical assemblies Labels Single in-line packages (SIPs) Dual in-line packages (DIPs) Radial components Axial components Cans "J" packs Leaderiess chip carriers (LCCs) Connectors Chips Rat packs Heat sinks Sockets LED and optical displays

SUPPLIED

Bulk or loose Reel Tube Magazine Carrier

VCD Machine

Axial Component

Insertion

Manual/Robotic Insertions of other

Components

Solder

Post-solder Attachments

Have Vapor Phase LR. Laser

Hand Solder

Test

Figure 21: Typical Steps in the Assembly of a P/CB

(1) Preassembly operations on components for purposes of trimming and forming leads and other modifications to vendor supplied components.

(2) Attachment of certain mechanical components by hand, robot, or fixed automation device.

(3) Insertion of dual in-line packages (DIPs) by DIP auto-insertion machines.

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(4) Insertion of axial components by variable center distance (VCD) machines. An axial component is one whose leads pass axially through the normally cylindrically shaped components; e.g., a typical resistor.

(5) Manual or machine insertion of radial and other components as well as axials and DIPs, which for one reason or another could not be machine-inserted during earlier steps. A radial component is one whose leads extend radially out from a circular shaped body such as a disk capacitor.

(6) Soldering.

(7) A final hand or robotic assembly work center for attaching components that cannot be soldered or components that, because of size, shape, or location must be attached and soldered after all others have been attached and soldered.

(8) Test.

In the case of boards that involve surface mount devices (SMDs), the processing steps are slightly modified. Machines exist to automatically place special types of devices and there are other variations that may be employed. However, the process is basically the same as above.

An interesting feature of process planning for electronic assembly is that the assembly operations for any particular board are an ordered subset of operations taken from a technologically, strictly ordered set of operations determined by the machines and processes available in the factory in which the board is being made. The fact that these operations are strictly ordered prevents the type of combinatorial explosion of possible operation sequences that can occur in other technologies.

As noted above, the assembly planning process is one of deciding which components will be inserted at which step in the process or, equivalently, how they will be attached to the P/CB. U p to several hundred components may be attached to a board and, in a typical factory, hundreds of different types of board are produced each year.

Depending on the philosophy of inventory management as well as the degree of automation, production is managed as a variation on one of the two basic approaches:

• Batch Production • Flexible Line Production

4.2.1.1.1 Batch Production

Each work station or machine center on the production line is stocked specifically to meet the needs of a particular board and a relatively large lot size of a particular board is run. Steps are normally taken to balance the line to minimize idle time. When the lot is complete, the line is restocked and perhaps reconfigured to produce a new board.

Under batch production, a process plan is written for the particular board to be produced and the line is stocked and configured according to this production plan.

In some factories, the factory floor is not configured as a production line. Rather , machines and workers are functionally grouped and batches of boards move through the factory floor from work center to work center in typical job-shop fashion. Materials are commonly issued in kits.

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4.2.1.1.2 Flexible Line Production

Taking into account the production schedule for some period of days or weeks into the future, all components needed for assembly of the scheduled boards are assigned to particular work stations. As the boards move through the line, they are automatically identified at each work station and the appropriate component at tachments are completed. Each work center can be viewed as a flexible machine center (FMC) and nearly all the design and scheduling concepts applicable to FMCs can be applied. Lot sizes of one may be accommodated and just-in-time concepts applied. Balancing the line becomes a very difficult task, but substantial amounts of idle time can be tolerated and justified on the basis of reduced setup time, inventory reduction, improved yields, and the other benefits of this type of manufacturing philosophy.

This type of system is relatively intolerant of large amounts of component insertion by humans, because the work task can change from moment to moment . Communicating operator instructions and monitoring the operator 's actions can be difficult. C R T monitors which present the operator instructions are used to reduce the confusion, as are a variety of other machines which mechanically identify, for the human operator, the component to be inserted and its location on the board.

Under the flexible line production philosophy, a process plan must also exist for each board to be produced. However, the plan moves with the board, being accessed, say, by barcode, at each work station. Moreover, the configuration and stocking of the line must at tempt to take into account the requirements of the collective process plans of all boards to be produced during the planning period. Ideally, one would have all of these process plans available in advance in order to at tempt to optimize the location of components in relation to machine center capacity. However, such is rarely the case, and day-to-day modifications are made.

4.2.2 The Planning Task

In order to fully appreciate the planning task, it is helpful to understand how circuit boards are typically designed.

4.2.2.1 Circuit Board Design

Computer-aided circuit board design was one of the first and most successful applications of CAD. Northern Telecom uses the Circuit Board Design System (CBDS) which was developed and is maintained by Bell Northern Research and is marketed by IBM. There are a number of competing systems, but all the principal C A D systems for circuit board designs provide the designer with a highly automated environment for conceptualizing and analyzing the functional properties of the circuit, choosing actual components for implementing the circuit, and laying out the board. In addition, these systems produce a B O M and other files that are used by purchasing and manufacturing for planning, machine programming, and other activities. Figure 22 illustrates the relationship of process planning to CAD, CAE, and other elements of a CIM architecture for the production of electronic systems.

From a manufacturing standpoint, there are two data sets operating the CAD background which are of particular interest. O n e is the component database from which either the designer or the CAD system, itself, automatically selects the actual component to be used on the board. This database may identify preferred components from a purchasing, electronic, and manufacturing standpoint. However, the designer may choose any component in the database, as required, to meet the design objectives and, while corporate approval may be required, may add new components to this database. Because of the rapid changes in electronic technology and the need to remain competitive, the component database is constantly being changed.

The other data set is in the form of sets of rules that either control or influence the selection of

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NEW PRODUCT REQUIREMENTS

NEW PRODUCT REQUIREMENTS

DESIGN ENGINEERING (CAE)

Electrical Silicon Mechanical Software Documentation

MANUFACTURING ENGINEERING (CANENG)

Simulation Standard Cells Finite Element Solids Modeling

DATA STORAGE & ADMINISTRATION PRODUCTION

Test Programs Costing Post Processing Process Dev. & Planning

Product Line Up Change Management Project Support Design Transfer Networks Archive/Retrieve

PRODUCTION PLANNING PROC

Part Assembly System Assembly Functional Test Packaging

»DUCTION CONTROL

Schedules Capacity Planning Resources Material

Τ STS/i

Detail Schedules Customer Configuration

Τ FORECASTS/ORDERS SHIPMENTS

Figure 22: A CIM Architecture for the Production of Electronic Systems

components and the manner in which they are placed on the board. These rules have two modes of application. In the first mode, they are automatically applied by the CAD system to place components and route the electrical paths on the board. In the second mode, these rules act as an advisor to the designer. If a rule is violated, the designer is issued a warning.

Rules concerning manufacturing feasibility or desirability are normally included to one extent or the other in the rule base for board design. For example, most systems will include rules for the placement of manufacturing fixture locating holes on the board. By counting the numbers of and weighting the types of violations, designs can be scored from the standpoint of ease of manufacturing. While the usefulness of these scoring techniques is debatable, it illustrates the manner in which manufacturing concerns can be handled at the design level. Accordingly, the design of circuit boards is performed in an environment that, in theory, can be very supportive of the application of criteria to simplify and reduce the cost of manufacturing.

4.2.2.2 Planning Constraints

The planning task would be relatively straightforward if there were a unique and stable relationship between a component to be attached and a method of attachment, and if the design of the board was in consonance with preferred manufacturing principles. Indeed, one could simply assign an operation code to all the components in one's component database. Then, given a BOM, assign an operation to each component , thereby specifying which components should be available at each work station. However, the realities of circuit board assembly include the following:

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(1) Insertion feasibility is dependent on the specific configuration of the board; e.g., a DIP component which can be auto-inserted by a DIP machine on one board cannot be inserted on another board, because there is insufficient clearance for the insertion tool.

(2) Insertion feasibility and attractiveness is dependent on the specific machine and tooling. This is a problem when one or more design groups are producing designs for boards that may be produced at several different facilities, each with different process capabilities.

(3) The component is unavailable at the preferred insertion work station. Auto-insertion machine, manual, and robotic work stations can only accommodate a limited variety of inventory. While this problem can be overcome with sophisticated, material delivery systems, it will be more economical for many factories to simply pre-stock each work station. Accordingly, a component that could be auto-inserted may end up being inserted by hand due to the physical limitation on the inventory that can be accommodated at the auto-insertion work station.

(4) Due to machine breakdowns, the preferred or normal insertion method is unavailable. If a machine is to be down for any significant period of time, the parts assigned to that machine must be affixed elsewhere and this implies a change in operator and machine instruction sets. If feasible, an alternative to this is to reschedule production, although dynamic production scheduling can be complex and more trouble than it is worth. In any event, one needs to minimize the time needed to respond to unforeseen problems on the line, and this response will most typically be a change in process plan.

4.2.2.3 Shop Aids

The overall planning process involves the development of the shop aids necessary to support these operations. Shop aids include the instruction sets that drive automatic machines, test programs for operating automatic test equipment, and operator instructions that must be issued to the floor in order to execute the assembly of the board. In general, these may be grouped into two broad categories: (1) assembly instructions for human operators and (2) the instruction sets, in the form of punched tape or computer files, to operate automatic equipment and to guide the process controllers that initiate and terminate automatic machine operation, identify products, and control material transfer devices. Most of these shop aids require a precise knowledge of component location and board geometry. This information is provided by the C A D system.

However, a first-cut at assigning components to operations can be accomplished without regard to part or board geometry. Under ideal design conditions, the insertion methods normally associated with the components would all be feasible and preferable. This preliminary assignment of components to operations can produce a tentative list of the operations that will produce the board and a list of parts by each operation. These latter lists, coupled with component location and board geometry are what is needed by the persons and computer programs which produce the shop aids.

Computer postprocessors which produce the instruction set for the operat ion of auto-insertion equipment are of particular interest. The reason for this is that, while the feasibility of part insertion due to specific board geometries can be addressed at a preliminary planning level, it must be addressed at the postprocessor level. It is simpler to let the CAPP initially deliver a candidate list of parts for insertion to the postprocessor, and let the postprocessor determine what it can insert while it is determining how to sequence the insertions. If a part cannot be auto-inserted because of the specific joint configuration of the component, board or tooling, the part is returned to CAPP for reassignment to another operation. The order of choices is normally, first, auto-insertion, second, robotic, and lastly, manual. This process is shown in Figure 23 and implies that the postprocessor must be able to identify insertion feasibility as well as develop the sequence of component insertions and the path of the insertion tool. This does not significantly complicate the algorithms used by the postprocessor.

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Other Shop Aids

Component by

Operation

Machine •Instruction

File

Figure 23: The CAPP-Postprocessor Relationship

Accordingly, CAPP is responsible for producing an initial process plan and for dealing with those initial proposals which were identified as infeasible or unattractive actions by the postprocessors.

4.2.3 Par t s Numbering and Coding

The introduction of a new parts numbering or coding system is normally an expensive and time-consuming task, whose cost is commonly very much underestimated. Accordingly, it should be approached cautiously. CAPP systems seem to imply the need for a part numbering or classification system which provides a one-to-one link between a part and its assembly method. In turn, this means that each new component that is added to the component database must be coded or otherwise linked to an assembly method.

Maintenance of such a system is expensive if the component database is constantly changing, and potentially confusing if different manufacturing facilities view the assembly of the component in different ways.

At Northern Telecom, the C A D file produces a parts list for the board. It contains a descriptive engineering code, a nondescriptive specific part number, and a consistent, short English language description of each part. There is enough information contained in the engineering code and the English phrase to infer a great deal about the way in which each component can be attached. This happens even though neither the engineering code nor the English description of the part were originally designed to designate an assembly method. That is, it is possible to infer an assembly method from existing part descriptions, and it is not necessary to create and maintain a new coding system. This is accomplished by parsing the engineering code and the English phrase for key words and groups of characters in the context of the board that is under consideration.

Alternatively, the parsing routing could be used to automatically create an assembly code file by component. This has not been necessary and would produce no benefits from the standpoint of the CAPP system.

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4.2.4 CAPP Aids CAD

The process plan that is produced at Northern Telecom lists the operations that are involved in the production of a board and shows an estimate of the direct labor and/or process time associated with each of these operations. We are currently interested in assessing the degree to which making this cost information available to the designer will influence the degree to which manufacturing cost and yield are considered by the designer. This design aid could only work with a generative CAPP.

4.2.5 P/CB Production

• A CAPP system reduces the labor cost of preparing a process plan. By itself, this is probably not a strong argument for CAPP in electronic assembly planning. The amount of time spent on process planning, particularly initial process planning, is relatively low in comparison to other technologies.

• A CAPP system reduces the training costs of new process planners and mitigates the impact of losing key personnel. It is not clear that a generative CAPP system for electronic assembly can serve as an effective training aid for new process planners. A variant system is better at this. CAPP may be useful when it comes to acquainting new designers of electronic boards with manufacturing issues. By pointing out costs, the CAPP system might well be an effective device for increasing designer sensitivity to these issues.

• A CAPP system improves the consistency with which plans are produced. While this is true, the issue of consistency is not of as much concern as in other technologies. In part, the reason for this is that there are not the processing options available in electronic assembly that exist in metalworking. However, the process of structuring CAPP uncovers misconceptions regarding assembly feasibility. These misconceptions are uncovered as one assembles the knowledge-base and rules for its application. The elimination of these misconceptions will improve productivity. To some extent, this is the result of pursuing a generative rather than variant strategy.

• A CAPP system provides the response time necessary to run a highly automated CIM system. As electronic assembly moves toward fewer manual insertions, the ability to rapidly change the process plan for a board under a flexible machine center philosophy becomes increasingly important . Under a CIM architecture, there are compelling arguments for a generative CAPP system, which can operate quickly and with as little human intervention as possible.

• A CAPP system provides a useful tool to improve the manufacturability of circuit board designs. The extent to which this is true depends on the organizational and product development philosophies of the firm. In firms which already assign a high priority to ease of manufacturing, attaching the CAPP to the CAD system may not be useful. For others, it may be useful to provide the designer with a CAPP system which gives the designer immediate access to an estimated conversion cost and explains the reason for the conversion cost by showing the cost implications of the design on an operation-by-operation basis.

CAPP should be designed to allow the process planner maximum control over its operat ion, and alternatives should be thoroughly explored before introducing new parts coding or classification schemes. They may not be necessary.

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4 3 The Route Generator

In 1986, D E C was faced with how to integrate M R P II shop floor control, automated material handling, factory data collection at the shop/center hierarchical level, and several cells at the cell/line hierarchical level. With some of these systems having already been implemented, and several others on the drawing board, each system was designed independently of the other. Consequently, each system would have addressed its routing and process data needs independently. If this had been allowed to continue, each system would have had to be implemented alone, in the sense of manually maintaining its own private copy of the route and process data.

The problem with standalone implementations that require much of the same data in common is version control. R o u t e maintenance and version control arises when route-sensitive systems are implemented in the same environment but are not designed for integration. For example, when there is a need to update the route because of an engineering change order, to change the standard route because of a sudden downward shift in quality levels, or to modify the process to take advantage of new technology/ideas, making a change to the manufacturing process can easily spill over into requiring modifications to process definitions on other systems. Thus, redundant, manually maintained route data is undesirable.

4.3.1 The Generator

To resolve this problem, instead of requiring multiple, redundant data maintenance activities to be made on each system, the Rou te Genera tor (RG) was developed as a single point of definition and control for the generation and revision management of routes and related process planning data for all route-sensitive systems.

O n e temptat ion to overcome was to try to build upon the existing process definition data structures within the M R P II system. However, it was soon realized that the M R P architecture was incompatible, that it did not support hierarchical routings, and that, as a business system, it did not support process engineering activities; e.g., it assumes a straight line route flow. In most process flow charts, there are several branch points that a process can take dependent upon any number of constraints.

The R G is an interactive, graphical, video terminal-based work flow generator application compliant with the architecture previously described. It is used to converge the routing needs of each of these systems into lone logical master route. Once defined, routing data is derived from this master route for any system. Because there is one point of control for routing data, the integrity of routes between systems should be insured. The benefit of the R G is its ability to capture and communicate the various route requirements for each of the factory control systems. Each process control system accesses its route data by making BOP data management interface calls. Because this data comes from the same source, routing data is consistent across all systems and is at the proper revision level.

Multiple revisions of a route (process) can co-exist for the same part number at the same time in the manufacturing site. Additionally, the preferred process to be used to build and test a part can change from t ime to time. Therefore, the R G allows for revision control of both part and process. This allows factory systems to phase-in new processes and parts without losing visibility into the requirements for a specific instance of a part and process. Systems that use the R G are truly integrated and have a common reference system (BOP) that can be used to manage any number of system views from same route definition.

4.3.2 Controller Views

Three process control systems, each of which require a route, are referred to as controllers because of their ability to control some aspect of the manufacturing system. Each of these systems potentially requires

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more detail about the route flow, and each has different views and data needs of the same route. They are:

• Manufacturing Resource Planning (MRP II)

• Work Flow Control (WFC) and Material Handling

• Factory Data Collection (FDC)

4.3.2.1 Manufacturing Resource Planning

M R P II requires the most abstract view of the route. M R P IPs view is not for real t ime control purposes and, therefore, does not require extensive route control data. Instead, M R P II is interested in financial and capacity planning data related to the route. The data required is used by M R P II for capacity determination and costing.

4.3.2.2 Work Flow Controller

The W F C takes a material handling point of view, based on a "material drop-off perspective. A W F C needs route data so that it can match route setup requirements to current resource capabilities and machine setup states to achieve optimal work flow.

4.3.2.3 Factory Data Collection

F D C potentially requires the most detailed route flow view. The F D C route flow view can include standard operations, al ternate operations, and various alternate rework operations irrespective of the way an associated material handling system may be configured. Alternate rework operations may be determined by the degree of seriousness of a failure or some other significant set of parameters that are used to determine what operat ion is to be performed.

4.3.3 Combined Route Flow

The R G permits the creation of a single, user-defined logical route, providing multiple views for factory systems in need of route flow data, yet maintains the continuity of one logical route.

Below is an example of how multiple route views can be derived from one logical route flow. The example begins by listing a product route flow, without giving consideration as to how the process steps in the route are eventually executed by the various process control system controllers. The example route flow shown in Figure 24 is based strictly on the product requirements and the logical activities required to build and test the product.

The sample route list is then translated into a logical process flow, as shown in Figure 25. It is at this t ime that the engineer would define the route flow in a way as depicted in Figure 25.

The master route flow is then analyzed with respect to the needs of each route-sensitive system. In effect, the generator for each controller selects certain process steps and ignores others, creating different views of the same master route.

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4.3.3.1 M R P II View of the Master Rou te

The Process Steps required for M R P are depicted in Figure 26. The normal cycle time for the initial assembly process is short enough to not warrant detailed tracking by M R P II. Hence only steps 1, 5, 6, 9 and 12 are "seen" by M R P .

The M R P II view is:

• Process Step 1: Assembly Step 1 • Process Step 5: Assembly Step 5 • Process Step 6: Test Step 1 • Process Step 9: Test Step 2 • Process Step 12: Final Touch-up

Process Step Description

1 Assembly Step 1 2 Assembly Step 2 3 Assembly Step 3 4 Assembly Step 4 5 Assembly Step 5 6 Test Step 1 7 Rework Test Step 1 8 Retest Step 1 9 Test Step 2

10 Rework Test Step 2 11 Retest Step 2 12 Final Touchup

Figure 24: Sample Product Route List

pass pass

Figure 25: Master Route Flow

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pass 1 > - 5 - > 6 > 9 > M 2

Figure 26: M R P View of the Master Route

The activities that M R P II does not see are Process Steps 2, 3, 4, 7, 8, 10 and 11.

4.3.3.2 W F C View of the Master Rou te

The W F C view is a different subset of the master route. The W F C view is affected by the physical layout of the factory floor and the material drop-off points at each of the work stations. Assuming that Assembly Step 4 and Assembly Step 5 share the same physical material drop-off point, the W F C view requires Assembly Steps 1 through 4 but not Assembly Step 5 (see Figure 27). To the WFC, the next standard operation after Assembly Step 4 is Test Step 1 (Process Step 6).

pass 1 > 2 > 3 - > > 4 — ^ 6 > M 2

Figure 27: W F C View of the Master Route

The W F C view is:

• Process Step 1: Assembly Step 1 • Process Step 2: Assembly Step 2 • Process Step 3: Assembly Step 3 • Process Step 4: Assembly Step 4 • Process Step 6: Test Step 1 • Process Step 9: Test Step 2 • Process Step 12: Final Touch-up

Note in this W F C example that Rework and Retest are performed internally to each test step so that the W F C never needs to know about Rework and Retest operations. Of course, if the W F C did need to know about rework loops, then Rework and Retest Steps could be identified as part of its view.

4.3.3.3 F D C View of the Master Route

FDC's view is yet another, more detailed view of the route master flow. F D C needs to view any physical drop-off steps required by a WFC, as well as Rework and Retest Steps. Note , however, that the FDC view does not include Assembly Steps 2 and 3 (see Figure 28). The assumption is that F D C is not involved in these two assembly steps, but a W F C must still deliver the product to these steps.

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F D C s view requires all the Process Steps except Steps 2 and 3:

• Process Step 1: Assembly Step 1 • Process Step 4: Assembly Step 4 • Process Step 5: Assembly Step 5 • Process Step 6: Test Step 1 • Process Step 7: Rework Test Step 1 • Process Step 8: Retest Step 1 • Process Step 9: Test Step 2 • Process Step 10: Rework Test Step 2 • Process Step 11: Retest Step 2 • Process Step 12: Final Touch-up

Note that F D C needs to know that the Rework Step is not the standard Process Step but, rather, is an allowed alternative only if a failure path is required at the completion of either test step.

The R G is table driven such that an engineer wishing to expand the number of system views simply registers the new view name in a master table along with a pointer that maps to the view-specific subroutine that addresses the data requirements of that system view. Later, when that view is indicated to the R G , the customized view-specific subroutine is executed, prompting the user for the view-specific data. Still later, once the route definition has been approved and released, the process controllers make the appropriate BOP data management interface calls referencing the same view name as originally input by the engineer.

pass pass

Figure 28: F D C View of the Route Master R o w

The BOP data management interface calls are very powerful. Generally, controllers have two modes in which they operate. One mode is to pass the status outcome of a previous step and allow the BOP evaluation routines to evaluate the proper next step based upon the view being requested. Referring to Figure 28, in a simple case where Step 6 results in a failure, then the logical next Step is a rework step, Step 7. When F D C requests the next step following Step 6 and supplies a "fail" status, the BOP evaluates this request and returns the rework step, Step 7. If, however, the next step request was made by WFC, the rework Step 7 is not seen and the correct response returned is Step 9. This is because it was determined that the W F C view would not have to be concerned with whether or not a failure was detected at Step 6.

The other mode is for the controller to request all of the next steps for a given step that meet the view specified. In this mode, the controller must be able to evaluate the alternate next steps and make the decision on its own as to which step will be selected.

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4.3.4 Process Mas te r

While the R G supports the traditional file structure of separate routes for each product, it additionally offers a G T capability by combining the otherwise separate routes into one superset route. This master route superset, called the Process Master (PM), is defined as a generic route flow template containing any number of Process Steps (PSs) which can be applied to define the route of a family of similar parts or products.

The P M is well suited to support manufacturing operations of closely related product lines. In fact, the closer the alignment of process similarities within the PM, the more efficient the PM becomes. For example, a D E C video terminal model number VT240 is a monochrome terminal. A VT241 is identical to the VT240, but has color capability added. The VT240 and VT241 terminals would be considered excellent candidates for inclusion in the same family to share a single PM because of their similar route flows.

A PM can have an unlimited number of PSs to support the members in the family of parts, but the most efficient use of the PM occurs with the highest percentage of like PSs. As a point of comparison, the VT100 terminal deviates significantly from the VT240 series and would be considered less likely to effectively share the same PM.

Since the VT100 has fewer PSs in common with the VT240-241 process master, combining these two dissimilar processes into one process master would not be desirable. There are t remendous advantages that can be derived from combining similar processes into one process master, such as a reduction in data maintenance and redundancy, and the ability to apply an integrated G T approach to manufacturing process families.

4.3.4.1 Rou te View of the PM

Using the previous example of the PM family, the VT240 and VT241 would each require a Rou te View (RV) of the PM. Both of the RVs would be mapped to the same PM. Almost all of the PSs would be mapped for each R V due to the similarities between the build processes. Consequently, two part process views have roughly 80 percent of the process steps in common.

However, if the VT100 were added as a member to the same PM family, not only would fewer of the existing PSs be usable by the VT100 route, but additional non-sharable steps would need to be added. It would simply be more efficient to create a separate PM for a family of VTlOOs, rather than minimize the utility of the existing family.

4.3.4.2 Conceptual Approach

The R G uses the P M to define a superset of valid sequential activities for use as a template for each of the individual parts within the PM flow. This PM template consists of the following components :

• PM Header • Process Steps • Controller View

The components of the PM must be created in the order listed above. The PM Header data is created first and identifies the historical information about its creation. The PSs then define the superset route flow for a specific PM. The controller view points to the specific process steps that are viewed by each controller.

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The R V points or "maps" to a subset of the PM by selecting the appropriate PSs from the PM template. The R V consists of:

• Part Master • Rou te View Header • Controller Specific

The R V Header is attached to the PSs of the same PM. The R V inherits all data associated with each PS, as well as any controller views associated to those PSs. Controller specific data is attached to the R V Header.

4.3.4.3 The PM and the R V

The relationship of the two data structures, the PM and the RV, is depicted in Figure 29.

PROCESS MASTER

PART PROCESS VIEW

Process Master Header

Part Master

y Process Steps «<•

y Route View Header

y Controller

Views

y Controller

Specific Views

Figure 29: Data Relationship Between the Process Master and the Route View

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5. Planning Facilities

5.1 The Process Industry Solution Center

Time is the essence of manufacturing competitiveness. For this reason, the focus of the Process Industry Solution Center, a joint partnership between Hewlett-Packard and Fisher Controls, is enterprise-wide information integration; from product development through production, distribution, marketing, and sales.

The Process Industry Solution Center is a meeting and demonstrat ion facility developed around the operations of a simulated chemicals manufacturer. The Process Industry Solution Center debuted in 1988 as the CIM Technology Center.

The Goal of the Process Industry Solution Center is to illustrate to customers as well as help them:

• Balance costs, quality, features and availability

• Shorten development, manufacturing and delivery cycles

The Process Industry Solution Center believes Computer Integrated Manufacturing (CIM) must build on the manufacturing management foundation already established within an organization. The basic strategy of the Process Industry Solution Center is to, as painlessly as possible, migrate to an open, standards-based integrated environment by building on and adding to existing applications.

Because no two process manufacturers are alike, the Center doesn't promote "one-size-fits-all" solutions. Its approach is to analyze operations and information flows, identify strategic opportunit ies for improvement, and quantify the benefits these opportunit ies offer.

5.1.1 The Market

Each of the industries addressed by the Solution Center rely on a combination of batch-oriented processes and discrete manufacturing techniques. Market conditions are forcing these sectors to examine CIM as a business solution. For instance, the rate of new drug introductions in pharmaceuticals requires producers to become more flexible, while tightening F D A and E P A regulations, and consumer expectations, are pressing them to improve quality.

These demands are boosting the market for CIM. According to Frost & Sullivan, the market for integrated batch process control systems serving these sectors will exceed $1 billion by 1994, a 100 percent increase over five years. Over half of the growth will come from foods, fine chemicals, and pharmaceuticals.

5.1.2 The Solution Center Demo

The first part of the presentation focuses in the importance of time-based competitiveness: the ability to get product to market sooner. The next part homes in on modeling both the business and manufacturing process, with the goal of simplification. Various scenarios and control methodologies are explored, informed by the collective experience of the Solution Center 's staff in process applications and CIM.

The final part of the program focuses on implementation. Here , a 30-minute comprehensive

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demonstrat ion shows how a batch-oriented process manufac turer - the Mighty Fine Chemical Co., a producer of specialty chemicals-would use integrated Open Systems to cut product lead times.

As the demo begins, the Mighty Fine plant is already running with a predetermined master schedule and a short-term production schedule, extending four or five days. The process itself mixes and reacts up to four ingredients into four different end-products, simulating the type of flexibility characteristic of today's specialty chemical producers.

In the demo, the M R P II system (CIMPRO, from Datalogix International) has already downloaded the current work order backlog for the week, which the finite scheduling system (Schedulex from Numetrix, Ltd.) converts into round-the-clock daily schedules. Those schedules are then downloaded to the supervisory control system. A choice of the following supervisory systems are featured:

• Monitrol from Hilco Technologies

• PMIS from Bradley-Ward

• CIM 21 from Industrial Systems Inc.

Within the plant, the supervisory system sends orders to the Fisher PROVOXplus plant floor distributed control system (DCS) to make various batches, one at a time. The DCS in turn is linked to a Fisher Controls U N I V O X line operator station.

Once the DCS reports that the batch has been made, the supervisory system schedules a quality control test from the plant production laboratory by notifying the laboratory information management system (LIMS), based on HP's Lab/UX software. The plant is also equipped with a maintenance management system (MCS-II from Diagonal Data) that schedules and tracks routine and emergency repairs. Provision is made for the operat ion of a PLC-controlled line for packaging the finished chemicals into drums.

To demonstrate the flexibility of the system, a breakdown is staged on the production line. The main reactor, a 2,000-gallon tank, suddenly malfunctions, requiring a rerouting of production to a larger, less efficient 3,000-gallon tank; the issuance of a repair work order; the scheduling of extra production lab tests to determine the quality of the batches produced both before and after the breakdown; and the adjustment of plant schedules to account for the less efficient production capability.

The adjustments start with notification by the DCS to the supervisory system. This in turn prompts the issuance of repair work orders from the MCS-II maintenance management system, extra quality tests from the H P Lab/UX LIMS system, and a rerunning of production schedules on the finite scheduler.

5.1.3 New Tactical Demo Added

The Tenafly center has long provided an executive-level system demonstrat ion aimed at corporate management and MIS staff. It has now added a hands-on tactical version for technical users, such as plant engineers, to actually operate all systems except for the M R P master scheduling.

For instance, in the H P Lab/UX LIMS system, the operator can override the system and perform historical trending or sample tracking, adjust automatic specification testing procedures, or change automatic test schedules for out-of-spec samples. In the DCS, he or she can change both the formulations, process trains (routings), and the operating parameters of the reactor tanks.

The computer systems are all H P 9000 workstations running HP/UX. They are networked via TCP/IP Ethernet . Applications are integrated using the Network File System (NFS) and H P Sockets, an applications and communications interface. The supervisory and plant management functions are managed

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by the H P computers. They link to the Fisher control environment via Fisher's CHIP/UX (Computer Highway Interface Program/Unix).

The changes to the Solution Center 's programs-from awareness to service and implementa t ion-a re the result of customer input. For instance, though both H P and Control Associates will provide implementation and strategic consulting services, the Center will also work with third-party service partners designated by the customer.

The demos at the Process Industry Solution Center will continue to evolve. According to process industry consultant Henry Fas t en of HP , who organized much of the computer hardware and software portion of the demo, additional applications are being added, including MANBASE from MAI Manufacturing Systems Inc. The demo will in many cases offer choices of multiple packages for any given application, such as the three already offered-Monitrol , PMIS and CIM 2 1 - a t the supervisory level.

Currently three days a month are reserved for visits by area companies to the Solution Center. A short list of previous visitors include American Cyanamid, Ciba Geigy, Hoescht Celanese, Hoffman LaRoche, Lederle Labs, Lever Brothers, and Union Camp. An estimated $7 million in sales were attributed to the CIM Technology Center between 1988 and 1991, a level of success that will continue at its successor, the Process Industry Solution Center.

5.1.4 Conclusion

Endeavors such as the P.I. Solution Center provide users, and vendors an opportunity to view an operational system-even if only hypothetical. This opportunity fosters further development and activity in CIM. This will, one hopes, provide for more efficient manufacturing processes.

5.2 Honeywell's Integrated Manufacturing Facility

Many manufacturers have already studied the feasibility of integrating building control with manufacturing control in a single, integrated system, in an effort to increase manufacturing competitiveness.

Building-control functions usually include monitoring and controlling environmental applications in a facility, such as heating/ventilating/air conditioning (HVAC) , humidity, air pressure, lighting, fire alarm systems, utilities systems, plant security systems, safety interlocks, and energy management and conservation.

Manufacturing control functions typically include monitoring and controlling such manufacturing applications as data acquisition, regulatory control functions, discrete/logic functions, batch functions, sequencing, event-initiated processing, analysis and report generation, historization, and interfacing to plant-wide communications systems.

5.2.1 Sample Configuration, Typical Manufacturing Facility

The physical operations of typical manufacturing facilities usually include several areas, such as receiving, manufacturing, packaging, storage, and shipping. Other physical operations in an industrial facility may include utilities (such as boilers, refrigeration units, and cogeneration units) and environmental process units (such as wastewater system, thermal oxidizers, and scrubbers). Other manufacturing occurs in extremely sensitive, controlled environments, such as clean rooms and laboratories.

Figure 30 shows all physical operations within a typical manufacturing facility (manufacturing process areas, utilities, and environmental process units).

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Manufacturing Facility

Laboratory

a

Receiving Area

—• Mfg. Area

—• Packaging Area

—• Storage and

Shipping

V

Clean Room

Utilities: • Boilers • Refrigeration

Units • Cogeneration

Units

Environmental Process Units: • Wastewater • Thermal

Oxidizers • Scrubbers

Laboratories/ Cleanrooms

Figure 30: Physical Operations, Typical Manufacturing Facility

Historically, building-control and manufacturing-control networks were designed separately, with overlapping capabilities. Since the two types of networks were seldom integrated, they almost always had:

• Different system architectures • Incompatible hardware and software platforms • Inconsistent data bases • Lack of communication between manufacturing control and building control

Redundant , costly, cumbersome communication networks still exist in many industrial facilities.

Figure 31 illustrates the traditional building control focus.

Leading manufacturers are now gaining a competitive advantage by analyzing the interrelationships of their building control network, their manufacturing control network, and their business goals. The Honeywell approach to creating an Integrated Manufacturing Facility provides manufacturers with two types of plant-wide data communications:

• Bidirectional horizontal communicat ion-from the receiving dock to the shipping dock: this type of communication links work areas and utilities with the entire manufacturing process

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Building Control Focus

Security


Laboratory

Receiving Area

— • Mfg. Area

— » Packaging Area

— » Storage

and Shipping

·. t Clean Room



Units




Figure 31: Traditional Building Control Focus

• Bidirectional vertical communication-from sensors to the boardroom: plant floor information flows upward to the administrative/management network, and strategic/tactical information and operating strategies flow down to the shop floor

Building and manufacturing information is made available to those who need it: operators, engineers, maintenance and support personnel, and plant management.

These bidirectional horizontal and vertical communications capabilities are designed to help manufacturers make more informed, timely decisions concerning their operations.

5.2.2 Challenges Facing Today's Manufacturing Facilities

"Under-rooP industrial facilities that house all their manufacturing equipment in an enclosed environment face many control challenges. These challenges result from the lack of integration with a building control system and include:

• Inconsistent product quality • Inflexible control and automation systems • Excessive downtime (often caused by a safety system fault)

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• Inefficient analysis and reporting capabilities from using separate systems • Inconsistent measurement, control, and management of facilities costs-particularly utilities

These shortcomings can be addressed individually, as follows:

• Inconsistent Product Qual i ty - Indoor humidity, temperature, air pressure, and air quality must be measured and controlled. The internal building environment often has a direct impact on product quality and plant profitability in many manufacturing processes.

• Inflexible Control and Automation Sys tems-Many manufacturers are unable to quickly and flexibly change the environmental conditions of their facility as quickly as they change recipes for product manufacturing. This inflexibility can adversely affect the quality of fine chemical products and other products that require close tolerances for temperature, humidity, and air pressure parameters during their production.

• Excessive Downt ime-The inability to integrate a safety shutdown alarm with an intelligent, staged shutdown of the process can cause excessive downtime and lost production time.

• Separate Systems Performing Analysis and Repor t ing-Convent ional manufacturing facilities usually have analysis and reporting capabilities spread throughout the plant in independent systems. Multiple operating stations generate reports in different formats among various manufacturing areas. This approach makes it difficult to collect, analyze, and historize important events. In addition, operators must be trained to use a variety of systems, formats, and protocols.

• Inconsistent Measurement , Control, and Management of Facilities Cos ts -Cos ts of utilities and environmental units are difficult to measure and control. Many facilities previously had no way to track these costs or allocate them back to product lines, plant areas, or departments. In addition, the production cycle and the physical facility may have peak energy needs that occur simultaneously, resulting in "high peak" energy billing and/or "brown out" conditions. Integrating the manufacturing process with utilities and environmental process units can help manufacturers: predict when peak energy usage will occur; schedule and allocate energy usage costs efficiently; and distribute utility resources (chilled water, steam, compressed air).

5.2.3 The Integrated Manufacturing Facility Solution

Figure 32 illustrates an Integrated Manufacturing Facility Solution, as envisioned by Honeywell.

The integration of a building control network with a manufacturing control network can offer users these competitive advantages:

• Better Product Qual i ty-Integrated building and manufacturing control strategies help keep the internal facility environment consistent with the product being manufactured, resulting in products of consistent quality and more productive workers

• Flexible Manufactur ing Capabil i t ies-Integrating process control and building control allows manufacturers to respond to changing market demands with quicker setups and faster transitions between product runs

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Plant Management

Security Γ

Building Control Network


Laboratory

Receiving Area

JZJL Mfg. Area

Packaging * Area

Storage and

Packaging * Area

Shipping

Clean Room



Units




Manufacturing Control Focus

Material Handling

Process Control

Packaging Control

Manufacturing Control Network

Figure 32: Integrated Manufacturing Facility

• Increased Uptime, Reduced Product Costs, and Lower Scrap Rates--The Integrated Manufacturing Facility can warn production operators when environmental conditions are out of specification, or when a potential safety hazard exists before out-of-specification conditions or hazards occur; early alarming gives operators time to react to this information and correct it, before a manufacturing control problem occurs; if a shutdown situation should occur, early alarming can help stage a

nsoft

n shutdown and eliminate costly startups

• Coordinated Supervisory and Reporting Capabi l i t ies-The Integrated Manufacturing Facility integrates analysis of building control and manufacturing control, providing:

• Improved ability to comply with F D A and E P A regulations • A convenient "single-window" for reporting and tracking • History and trending analysis for both systems • A consistent operator interface • Reduced operator training

• Improved Management and Tracking of Facilities Cos t s -The Integrated Manufacturing Facility can measure, control, and manage facilities costs, providing-plant operations personnel with tighter tracking and billing of operational costs to appropriate manufacturing units, and optimized energy conservation

5.2.4 Manufacturing Applications

Internal cultural and organizational issues can sometimes impede even the best integration efforts. Fortunately, many industries are moving quickly toward focusing on both building control and

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manufacturing control. These manufacturers are looking beyond departmental barriers to create integration solutions for a variety of applicat ions-from simple, single-loop applications to those that are extremely complex. Fast, fundamental benefits occur in industries that recognize the positive impact of control integration on the quality of products being manufactured. For example:

• Pharmaceut ica l s -have stringent ambient temperature, humidity, and pressure requirements in manufacturing, laboratory, and animal room environments. In addition, many F D A requirements now extend beyond the process system to include building control. Integration between building control and manufacturing control can help pharmaceuticals manufacturers control these processes more tightly, thereby improving product quality and meeting increasingly strict federal regulatory requirements.

• Food, Beverage and Consumer Goods-face increasingly complex formulations and processes. A need exists in these industries for information to be shared between facility services and the process, so that a wider variety of products can be tightly controlled during the production process. Integration provides better data-sharing and communications throughout the facility, as well as consistently high-quality products.

• Textile Fiber Industr ies and Paper Products Convers ion-have strict humidity and temperature control requirements. Integration of building control with manufacturing control is crucial to the consistent, cost-effective production of quality products.

• Silicon Chip Manufacturers-s i l icon chip manufacturers face sophisticated control needs within clean room and assembly areas. In addition, the building control system often:

• Annunciates alarms for toxic material detection and provides safety warning systems for notification of occupants

• Provides focused control solutions for many sensitive applications

• Controls process waste

Integration of building control with manufacturing control in this type of application helps manufacturers maintain quality and reduce scrap.

5.2.5 Approaches To Achieving An Integrated Manufacturing Facility

There are two basic approaches to achieving an Integrated Manufacturing Facility. In the first approach, manufacturing process requirements drive the integration, and commercial building controllers are integrated into a higher-level industrial control system.

In the second approach, building control system requirements drive the integration, and individual industrial control devices are integrated into a building control system.

Manufacturing process requirements drive, e.g., photographic film manufacturing (see example below) and parenteral pharmaceuticals manufacturing; building control requirements drive, e.g., laboratories and cleanrooms.

By way of example, the following paragraphs describe the use and benefits of the Integrated Manufacturing Facility in a photographic film production facility.

In many manufacturing processes, such as photographic films, the building environment is a process parameter that directly impacts product quality and plant profitability. Examples of building environment

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process parameters include the measurement and control of humidity, temperature, pressure, and air quality . As manufacturers automate their process control systems, they also study how to tightly integrate their building control systems with their process. These building control systems typically control heating, ventilating and air conditioning (HVAC) and are candidates for integration into a single system-again, known as an Integrated Manufacturing Facility.

Because the building environment and process are highly interactive during photographic film production, a film plant needs to be completely enclosed, or "under roof." The product, be it in the form of raw material, in-process inventory, or finished goods, is sensitive to environmental conditions during both storage and processing. Because of the length of time film spends in various phases of storage, the storage environment is often critical to the quality of the final product. The processing phase is typically much shorter in duration and therefore is less dependent on environmental conditions. However, this phase is still important , because conversion takes place during processing.

5.2.6 Process Description

Time of exposure to conditions of temperature, humidity, and light during storage is a critical quality parameter. Product-dependent variables during manufacturing include drying pressure, temperature, humidity, and air quality. How these variables are controlled can make the difference between an acceptable product and a rejected product.

The process flow in a film plant begins with raw material storage of chemical compounds, such as paper and film backings, water solvents, resins, and active ingredients.

The initial processing stage is called solution manufacturing. Next comes a coating process. After the coating phase, the film dries in a multi-zone continuous dryer. Pressure, temperature , and flow rate are critical to maintaining product quality during this drying process. The final phase of photographic film production is the converting and packaging process. Most of this process is performed in a "lights out" environment because of film's inherent sensitivity to light.

Most film plants today have separate process control, building control, fire protection, and safety systems. This control approach can result in duplication of monitoring and operating costs and/or poor or nonexistent communications between systems.

Several problems in a photographic film plant present opportunit ies for using an Integrated Manufacturing Facility. For example, pressure must be tightly controlled in the various storage and processing rooms, as well as within some of the process units, such as continuous dryers. Product quality often depends on very stable and consistent airflow patterns throughout the manufacturing process.

In addition, separate safety shutdown systems are difficult to monitor and diagnose. Unnecessary shutdowns caused by faulty sensors or system errors usually take hours to investigate and recover from, often causing hours of lost production and product waste. Connecting these critical personnel safety systems into an integrated manufacturing facility system not only reduces waste and downtime but also speeds diagnostic maintenance and system recovery efforts.

5.2.7 Solutions and Benefits

Plant personnel have repeatedly expressed a need for a system that provides alarms, history, trends, and reports to: prevent upsets leading to quality defects; satisfy regulatory, customer, and management requirements; and establish correlations between quality of products and environmental conditions.

A system of this type would provide operators with quality data that displays storage parameters as well as

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process parameters for any batch, lot, or roll.

Potential benefits of building and manufacturing integration in a photographic film plant include improved quality-i.e. , more consistent production results from minimizing process variabili ty-and waste reduction, increased uptime, and reduced training, spares, and support costs for various separate systems-i.e., an integrated system quickly identifies problems, establishes correlations, saves time, and eliminates finger-pointing between working groups or departments. This leads to more productive use of personnel in solving plant problems, lowering costs, and improving overall manufacturing competitiveness.

5.2.8 Conclusion

An Integrated Industrial Facility can provide world class manufacturing benefits to manufacturers in a variety of industries. Honeywell claims to be the first control supplier to bring this integration technology to control customers on a worldwide basis.

Integration of manufacturing control and building control can help manufacturers achieve and maintain:

• Consistent production of quality products • Flexible manufacturing capabilities • Increased upt ime • Reduced product costs • Lower scrap rates • Tight, trackable compliance with F D A and E P A regulations • Improved management and tracking of facilities costs • Integrated plant-wide communications • High levels of employee safety • Energy reduction programs

Honeywell believes it can help achieve and sustain the Manufacturing Competitiveness of its customers through the Integrated Manufacturing Facility.

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Vendors

The following list of products was taken from a 1989 research report by the staff of United Technologies Research Center, E. Hartford, CT. At that t ime there were 134 CAPP systems; however, the majority of these systems were either research systems, in-house systems, or systems developed in academe. Often the researchers failed to give full information regarding the systems developer or the systems, themselves. The systems listed below are those that are complete (not partial, quasi-, or non-CAPP systems), commercially available, and included sufficient information to be useful for manufacturing applications. Information on all systems studied by the researchers may be obtained by contacting CAM-I Inc., 1250 E. Copeland Rd., Suite 500, Arlington, T X 76011; 817/860-1654; F A X 817/275-6450

System: AC/PLAN Vendor: American Channels, Inc

Lexington, M A

• An enhanced variant planning system; uses keywords to pick out the most similar plan; uses search function to choose operations from other plans.

System: Alphagraphics Vendor: Birsch, Birn & Partners

Ft. Lauderdale, FL

• A variant, G T oriented system; primary focus on classification and coding.

System: Autoplan Vendor: Metcut Research Associates, Inc.

Cincinnati, O H

• A hybrid (variant/generative combination) system using graphics for interactive selection of resources.

System: CAPP (CAM-I's Automated Process Planning) Vendor: Computer-Aided Manufacturing International

Arlington, T X

• O n e of the oldest and most commonly used variant process planning system; uses G T methods.

System: CutPlan Vendor: Metcut Research Associates, Inc.

Cincinnati, O H

• GT-based, variant system.

System: CutTech Vendor: Metcut Research Associates, Inc.

Cincinnati, O H

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• Expert machining operation detailing program; selects tools, cutting parameters (selection, speeds, feeds), tolerances, cost estimating.

System: GECAPP-PLUS Vendor: General Electric

Albany, NY

• Hybrid modular system; modules may be purchased separately; limited generative capability.

System: IntelliCap Vendor: CimTelligence

Lexington, M A

• A variant system combining AI, GT, and relational database technologies.

System: IntelliGen Vendor: CimTelligence

Lexington, M A

• An AI, GT-based shell system designed to capture user's expertise.

System: L O C A M Vendor: Logan Associates

Natick, M A

• A popular hybrid system; user logic stored using decision tables.

System: Mult iCAPP Vendor: Organization for Industrial Research

Bedford, M A

• Variant system similar to CAM-I CAPP; besides G T code, retrieves plans by matrix, variance code matching (similar part families), and information within a plan.

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Computer

Documents

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