ANALYSIS OF RESEARCH ON COMPUTER AIDED PROCESS

PLANNING

Miss. Priti, Assistant professor, Department of Mechanical Engineering, Central University of Karnataka, Kalaburagi

Prof. S S Hebbal, Professor, Dept of Industrial and production engineering, P D A College of engineering

Dr. Syed Qutubuddin, Associate Profesor, Dept of Industrial and production engineering, P D A College of engineering

ABSTRACT: For the past three decades, Computer Aided Process planning (CAPP) has attracted a large amount of research interest. A huge volume of literature has been published on this subject. Today, CAPP research faces new challenges owing to the dynamic markets and business globalization. Thus, there is an urgent need to ascertain the current status and identify future trends of CAPP. Covering articles published on the subjects of CAPP in the past 10 years or so, this article aims to provide an up-to-date review of the CAPP research works, a critical analysis of journals that publish CAPP research works, and an understanding of the future direction in the field. First, general information is provided on CAPP. The past reviews are summarized. Discussions about the recent CAPP research are presented in a number of categories, i.e. feature-based technologies, knowledge – based systems, artificial neural networks, genetic algorithms, fuzzy set theory and fuzzy logic, Petri nets, agent – based technology, Internet – based technology, STEP-compliant CAPP and other emerging technologies. Research on some specific aspects of CAPP is also provided. Discussions and analysis of the methods are then presented based on the data gathered from the Elsevier's Scopus abstract and citation database. The concepts of 'Subject Strength' of a journal and 'technology impact factor' are introduced and used for discussions based on the publication data. The former is used to gauge the level of focus of a journal on a particular research subject/domain, whereas the latter is used to assess the level of impact of a particular technology, in terms of citation counts. Finally, a discussion on the future development is presented.

Keywords: CAPP, MIPLAN, METCAPP SOFTWARE

1. INTRODUCTION

Technological advances are reshaping the face of manufacturing, creating a paperless environment in which computer automated process planning (CAPP) will play an important role. The two reasons for this effect are: Costs are declining, which encourages partnerships between CAD and CAPP developers and access to manufacturing data is becoming easier to accomplish in multivendor environments. This is primarily due to increasing use of LAN’s; IGES and the like are facilitating transfer of data from one point to another on the network; and relational databases (RDBs) and associated structured query language (SQL) allow distributed data processing and data access.

With the introduction of computers in design and manufacturing, the process planning part needed to be automated. The shop trained people who were familiar with the details of machining and other processes were gradually retiring and these people would be unavailable in the future to do process planning. An

alternative way of accomplishing this function was needed and Computer Aided Process Planning (CAPP) was the alternative. Computer Aided Process Planning was usually considered to be a part of computer aided manufacturing. However computer aided manufacturing was a standalone system. In fact a synergy results when CAM is CAD to create a CAD/CAM In such a system CAPP becomes the direct connection between design and manufacturing.

Moreover, the reliable knowledge based computer – aided process planning application – MetCAPP software looks for the least costly plan capable of producing the design and continuously generates and evaluates the best one seen so far. The goal is to find a useful reliable solution to a real manufacturing problem in a safer environment. If alternate plans exist, rating including safer conditions is used to select the best plans.

1.1 COMPUTER AIDED DESIGN (CAD)A product must be defined before it can be manufactured. Computer Aided Design involves any type

of design activity that makes use of the computer to develop, analyze or modify an engineering design. There are a number of fundamental reasons for implementing a computer aided design system.

a. Increase the productivity of designer.

This is accomplished by helping the designer to visualize the product and its component subassemblies and parts, and by reducing the time required in synthesizing, analyzing, and documenting the design. This productivity improvement translates note only into lower design cost but also into shorter project completion times.

b. To improve the quality of the designer.

A CAD system permits a more through engineering analysis and a larger number of design alternatives can be investigated. Design errors are also reduced through the greater accuracy provided by the system. These factors lead to a better design.

c. To improve communication.

Use of a CAD system provides better engineering drawings, more standardization in the drawings, and better documentation of the design, fewer drawing error, and greater legibility.

d. To create a database for manufacturing.

In the process of creating a the documentation for the product design (geometries and dimensions of the product and its components, material specification for components, bill of materials etc), much of the required data base to manufacture the product is also created.

Design usually involves both creative and repetitive tasks. The repetitive tasks within design are very appropriate for computerization.

1.2 COMPUTER AIDED MANUFACTURING (CAM)By the time computer use in design began, numerical control technology (NC technology) had

matured to become cost effective for applications in machining. An important in numerical control is part-programming. A part-program is simply a set of statements comprehensible to the machine control unit

(MCU) that oversees slide and tool movements and other auxiliary functions. In the case of components with complex geometries, part-programs had to carry out lengthy calculations for which it was logical to use computers. This gave rise to machine control units (MCU’s) with built in microprocessors- the building blocks of computers. The use of computers in extending the applications of NC technology, especially to part programming was earlier termed Computer Aided Machining (CAM) and the associated technology was called Computer Numerical Control (CNC). Later Computer Aided Machining became an acronym for Computer Aided manufacturing (CAM). Earlier Computer Aided Manufacturing used to denote computer use in part-programming only. Today it means any non design function of manufacturing that is computer aided.

1.3 CAD/CAM

As the use of computers in design and manufacturing broadened under CAD and CAM, it becomes evident that certain tasks were common to both, eg:- both design and manufacturing require data on tolerance. Part geometries created during CAD can readily be saved in the database for later use. The forward slash (/) between CAD and CAM was meant to reinforce the shared functions of design and manufacturing.

2. PROCESS PLANNINGThe product design is a plan for the product and its components and subassemblies. To convert the product design into a physical entity, a manufacturing plant is needed. The activity of developing such a plan is called process planning. It is a link between product design and manufacturing. Process planning involves determining the sequence of processing and assembly steps that must be accomplished to make the product. It is concerned with the engineering and technological issues of how to make the product and its parts. What types of equipment and tooling are required to fabricate the part and assemble the product? It involves determining the most appropriate manufacturing and assembly process and sequence in which they should be accomplished to produce a given part or product according to the specifications set forth in the product design documentation. All the related information is documented on a Rout Sheet. The planning begins with engineering drawings, specifications, parts or material lists and a forecast of demand. The scope and variety of process that can be planned are generally limited by the available processing equipment and technological capabilities of the company or the plant.

Process planning is usually accomplished by manufacturing engineers. Based on process planner’s skill, knowledge, and experience, the processing steps are developed in the most logical sequence, to make each part.

The following are the list of many decisions and details usually included within scope of process planning. Interpretation of design drawings

The part or product design must be analyzed (materials, dimensions, tolerances, surface finishes etc) at the start of the process planning procedure.

Process and sequences

The process planner must select which processes are required and their sequence. A brief description of all processing steps must be prepared.

ORGANISATION FOR INDUSTRIAL RESEARCH, INC FACILITY F1PART NUMBER :A63799

PRJ# ORDER QTY

MIN.QTY

DUE DATE

PR#

PART NAME:SHAFT .ARM A34UB 45D3

1000 935 249 2

PLNG REV:02 DWG REV:0

PLANNER:ADAMS CODE#: 1310-1181-2111-0000-0100-0000-0000-00

INSPECTIONS GSPSPECIAL INSTRUCTIONS / HANDLING:

#1 #2 #3 ½” DIA MS-500 H.R. STEEL (2”LENGTH)MFG

ENGQ/A

FHBPC

AHOPERNO:

MACHTOOL

OPER DESCRIPTION-ASSY INSTRUCTIONS

SET UP TIMES

PIECE TIMES

OPR

0010 5145 S/U COLLET 2.00 0.173

ROUGH TURN M/C PER TAPE NO:LS982A

0.440 DIA BY 1.7500 LENGTHTH

0.300 DIA BY 0.8120 LENGTHTH

0.275 DIA BY 0.4375 LENGTHTH

FINISH 3/64 GROOVES (TYP) AND CHAMFERS

0.270 DIA. BY 0.375 LENGTH

CHAMFER CUTOFF TO 1.960

0015 1026 #2 CENTERS BOTH ENDS 0.25 0.004

0020 9401 CARBURIZE AND HARDE 0.50

0030 4063 S/U BETWEEN CENTERS 1.25 0.0983

GRIND OD HOLD CONCENTRICITY

HOLD 0.4200 DIM. HOLD 0.2600 DIM.

HOLD 0.2815 DIM. HOLD 0.2712 DIM.

0040 9501 BLAST TO CLEAN 0.001

0050 9201 CHROME PLATE PER PRINT 0.38

0060 9805 FINAL ISPECT

ROUTE SHEET GENERATED BY MIPLAN

Equipment selection.

In general, process planers’ must develop plans that utilize existing equipment in the plant. Otherwise, the component must be purchased or an investment must be made in new equipment.

Tools, Dies, Moulds, fixtures and gauges.

The process planner must decide what tooling is required for each processing step. The actual design and fabrication of these tools is usually delegated to a tool design department and tool room or an outside vendor specializing in that type of tool is contracted.

Method analysis.

Workplace layout, small tools, hoists for lifting heavy parts even in some cases hand and body motions must be specified for manual operations. The industrial engineering department is usually responsible for this area.

Work standards.

Work measurement techniques are used to set time standards for each operation.

Cutting tools and cutting condition.

These must be specified for machining operations often with reference to standard handbook recommendation.

The results of planning are:

Routings which specify operations, operation sequences, work centers, standards, tooling and fixtures. This routing becomes a major input to the manufacturing resource planning system to define operations for production activity control purposes and define required resources for capacity requirements planning purposes. Process plans which typically provide more detailed, step by step work instructions including dimensions related to individual operations, machining parameters, set-up instructions, and quality assurance check points. Fabrication and assembly drawings to support manufacture.

Manual process planning as mentioned earlier is based on a manufacturing engineer’s experience and knowledge of production facilities, equipment, their capabilities, processes and tooling. Process planning is a time-consuming process and the results vary based on the person doing the planning.

3. COMPUTER - AIDED PROCESS PLANNING (CAPP)

Process planning translates design information into the process steps and instructions to efficiently and effectively manufacture products. As the design process is supported by many computer aided tools, computer aided process planning has evolved to simplify and improve process planning and achieve more effective use of manufacturing resources.

3.1 CAD/CAM INTEGRATION AND CAPP FEATURES

A frequently overlooked step in the integration of CAD/CAM is the process planning that must occur. CAD systems generate graphically oriented data and may go so far as graphically identifying metal etc to be removed during processing. In order to produce such things as NC instructions for CAM equipment, basic decisions regarding equipment to be used, tooling and operating sequence need to be made. This is the function of Computer Aided Process Planning. Without some elements of CAPP there would be no such thing as CAD/CAM integration. The CAD/CAM systems that generate tool paths and NC programs include limited CAPP capabilities or imply a certain approach to processing.

CAD systems also provide graphically oriented data to CAPP systems to use to produce assembly drawings etc. Further; this graphically oriented data can then be provided to manufacturing in the form of hardcopy drawings or work instruction displays. This type of system uses work instruction displays at factory workstations to display process plans graphically and guide employees through assembly step by step. The assembly is shown on the screen and as a employee steps through the assembly process with footswitch, the components to be inserted or assembled are shown on the CRT graphically along with text instructions and warnings at each step.

If NC machining processes are involved, CAPP software exists which will select tools, feeds, and speeds and prepares NC programs.

3.2 COMPUTER-AIDED PROCESS PLANNING : TYPES

Computer aided process planning systems are around two approaches. These approaches are called:

1. Retrieval CAPP system or Variant Approach2. Generative CAPP systems or Generative Approach

Some Computer aided process planning systems are combining the two approaches in what is known as Semi Generative Approach.

1. Retrieval CAPP System or Variant Approach

The retrieval type is suitable for a family of parts. This system draws a standard process plan and stores it in the database. Whenever a different part from the family is to be processed, the standard process plan is retrieved and appropriately modified hence the retrieval to this system. The retrieval system relies on the concept of group technology for part coding and classification. It is also compatible with the concept of cellular manufacturing in which cells are designed and laid out for family-of-parts production. In this type, as mentioned earlier a standard process is stored in computer files for each part code number called the Route Sheet.

The retrieval CAPP system operates as given in figure 2. Before the system can be used for process planning, a significant amount of information must be compiled and entered into the CAPP data files. This is referred to as the “preparatory step”. It consists of the following steps:

i. Selecting an appropriate classification and coding scheme for the company.ii. Formatting part families for the parts produced by the company.

iii. Preparing standard process plans for the part families.

Steps (ii) and (iii) continue as new parts are designed and added to the company’s design database.

GENERAL PROCEDURE FOR RETRIEVAL CAPP SYSTEMS

After the preparatory phase has been computed, the system is ready for use. For a new component for which the process plan is to be determined, the first step is to determine the GT code number for the part. With this code number a search is made for the part family file to determine if a standard rout sheet exists for the given part code. If the file contains a process plan for the part, it is retrieved (hence the word “retrieval” for this CAPP system) and displayed for the user. The standard process plan is examined to determine whether any modifications are necessary. It might be that although the new part has the same code number, there are minor differences in the process required to manufacture it. The user edits the standard plan accordingly. This capacity to alter an existing standard process plan is what gives the retrieval system its alternative name: “variant” CAPP system. If the file does not contain a standard process plan for the given code number, the user may search the computer file for a similar or related code number from which a standard

Standard process plan file

Process plan

(Route sheet)

Process plan formatter

Other application programs

New part design

Derive GT code number for part

Search part family file for GT code number

Retrieve standard process plan

Edit existing plan or write new plan

Part family file

Selecting coding system and form part families

Prepare standard process plans for part families

route sheet does exists. Either by editing an existing process plan or by starting from scratch the user prepares the rout sheet for the new part. This rout sheet becomes the standard process plan for the new part code. The process planning session concludes with the process plan formatter, which prints out the route sheet in the proper format. The formatter may call other application programs into use. For eg:- to determine machining conditions for the various machine tool operations in the sequence, to calculate standard time for the operations or to compute cost estimates for the operations. One of the commercially available Retrieval CAPP systems is MultiCapp, from OIR, the Organization for Industrial research. It is an online computer system that permits the user to create new plans, or retrieve and edit existing process plans as explained earlier.

2. Generative CAPP System or Generative Approach

The generative method of developing process plans involves starting from scratch every time a different part is to be processed; no plans are available as the baseline. The basic requirement for a generative process planning system is that the given component model/drawing is to be interpreted in terms of manufacturability. Here instead of retrieving and editing an existing plan contained in the computer database, generative system creates the process plan based on logical procedures. In a fully generative CAPP system the process sequence is planned without human assistance and without a step of predefined plans. A generative CAPP system is usually considered part of the field of expert systems, a branch of artificial intelligence. An expert system is a computer program that is capable of solving complex problems that normally require a human with years of education and experience. Process planning fits within the scope of this definition.

There are several ingredients required in a fully generative process planning system:

i. First the technical knowledge of manufacturing and the logic used by successful process planners’ must be captured and coded into a computer program. In expert systems applied to process planning, the knowledge and logic of human process planners’ is incorporated into a so called “knowledge base”. The generative CAPP system then uses that knowledge base to solve process planning problems (ie create route sheets)ii. Second ingredient in process planning is a computer compatible description of the part to be produced. This description contains all the pertinent data and information needed to plan the process sequence. Two possible means of providing this description are:

a.The geometric model of the part that is developed on a CAD system during product design and a GT code number of the part that defines the part features in significant details.

iii. The third ingredient in a generative CAPP system is the capability to apply the process knowledge and planning logic contained in the knowledge base to a given part description. In other words, the CAPP system uses its knowledge base to solve a specific problem - planning the process for a new part. This problem solving procedure is referred to as the “inference engine” in the terminology of expert systems. By using its knowledge base and inference engine, the CAPP system synthesizes a new process plan from scratch for each new part it is presented.

4. CAPP METHODOLOGY

The developed CAPP system consists of feature recognition module and other modules for selecting machines, tools, machining parameters and optimization modules. The feature recognition module has been developed by Solid Works as modeling software and features are interpreted using a programme written in Visual Basic 6.0.

The Oracle 7.3 has been used for database management. The highlight of the system is that it has got excellent user interface by which user can interact with the system at different levels while generating a process plan.

METHODOLOGYVarious modules used for generating process plan are described as follows:

Feature Extraction Module.The solid modeling software plays an important role in providing features data. The solid modeling

software package used in this work is SolidWorks 98 Plus windows based software. The software coding to extract feature along with its attributes has been implemented in Visual Basic 6.0 and database is created in Oracle 7.3 as backend. Using the Application Programme Interface (API) of SolidWorks 98 Plus, it is possible to fetch any of the functions that are used for the modeling.

Blank Selection ModuleAfter extracting the features information from the feature extraction module, the next step is to find out

the overall dimensions of the raw materials required. Overall size of the component is required for the selection of the raw material from the raw material database.

Once the component is modeled in SolidWorks modeling software, it is possible to find out the overall size of the component directly from SolidWorks Application Program Interface. The system automatically adds the machining allowances on each face. Provisions are also made so that the user can also customize the machining allowances according to requirements.

Set-Up PlanningOnce the features are recognized, the next step is to group the features into set-ups. Set-Up planning

deals with the selection and sequencing of the processes required for generating the final shape of a component. It is a mixture of complex and interrelated tasks. Set-Up planning also includes the orientation in which the component is to be placed on the work-table for machining. It covers work-holding criteria as well.

Set-Up Planning MethodologyThe input for this particular module comes from the feature extraction module. All the features

identified from the CAD model are given to this module for further processing. Here, different features have different possible directions of approach. One of the possible directions of approach is perpendicular to the location face. The user decides this by interfacing with the system and entering the location face details for each and every feature. Any feature, which lies in the particular orientation, is given the location face accordingly.

The feature tree holds the information about its nodes, dimensions, location and tolerance information. It the user selects a particular node, and then information about the feature can be viewed. The algorithm

developed searches through all the features and checks for each face the number of features that can be machined. The feasible faces are then ordered accordingly and then grouped. The desired set-up planning is the one in which maximum number of features like tolerance location is to be given manually prior to set-up formation.

RoutingRouting is the method of directing the blank through various stages to get the required feature. In this

module the following information is generated. Possible route identification Selecting the optimum route Calculating the intermediate dimensions for the route selected.

Possible Route IdentificationThe process selection is done taking into consideration the following details: The geometric and technological information of the features. Each and every feature and its associated accuracy and surface finish requirement are taken into consideration. Based on the surface finish requirement specified and the accuracy indicated, the various possible routes

available in the feature – process – route database are identified.The method adopted gives various options or routs for a given feature. An exclusive feature – process –

route table is maintained in the database and routes are selected base on the accuracy that can be attained using the specific route for a given feature.

A feature may have one or more number of routes and the user is allowed to change the routes according to his requirement. A process route can be divided based on the final finish requirement.

Eg: - To mill a block of accuracy IT 8, may be done in the following two ways.Rough Milling – Semi-Finish Milling – Finish MillingRough Milling – Semi-Finish Milling – Rough-GrindingMany routes are possible similar to these and should be considered before selecting the final route. The

dimensional variations that are allowable for the features on a part to be machined will affect the operations, tools, and set-ups that are required to machine the parts. Stringent tolerance specifications between features will require more accurate operations, tools and additional set-ups for machining them. At this stage itself, feature sequencing is carried out.

Cutting Tool SelectionThe main concerns in tool selection include tool type, material, geometry, and tool dimensions.

Selection of tool type is based mainly on operations to be carried out and the machine tools involved. A criterion for selecting tools for rough machining, for eg: - is to minimize the tool changes and to maximize the number of features machined. Several other factors also influence productivity such as tool material and size.

The process generation module of the CAPP system decides the process to be carried out to finish the party by means of feature process correlation. Based on the tool process correlation the cutting tool is decided. The tool process correlation holds all the information regarding tools and their operations. If the feature is a hole, then a drill is to be used.

But based on the feature dimension, the best matching tool is to be selected from the corresponding database, providing data like tool code, tool length, diameter, and insert material, separate databases are developed and maintained for drill tools, milling cutters, and grinding wheels. The tool selection is facilitated with dual methods, namely automatic selection and manually.

Machine Selection for Individual ProcessMachine selection is based on the blank size and process capability of the machine. For each and every

process one or more number of machines are possible. This is added in a list where it is identified by a key. The list contains the following link information: Set-Up number Feature name Process

After selecting the various possible machines, redundant machines are eliminated and only machines, which are unique, are identified and it is retained for further processing. The information is available as a list structure where the set-up is the main link.

5. CAPP APPLICATIONS: CASE OF METCAPP SOFTWARE

MetCAPP is a knowledge – based process planning and cost estimating system targeted at providing: Improved productivity by reducing process time and variability Reduced inventories Consistent and higher product quality levels

MetCAPP provides the link between design and manufacturing floor. It provides the ability to take CAD generated solid models and use them to generate process plans based on the best: Machines Sequence of steps Timing Routing/ cost combination Provision for alternate and concurrent operationsThe technology modules are: Feature recognition Milling Turning Hole makingThe user effectively manages the system via the technology module manager as illustrated in the figure. MetCAPP, which is a knowledge-based manufacturing process planning and cost estimation system, uses

the Step Optimization to recognize the machining steps, to optimize the time and resources. The Step Optimization should be used only after calculating the steps for all features, either manually or by technology modules. Once the optimization is generated, any changes to the features are reflected in step optimization data.

Through, the inclusion of a process plan in the problem requires optimization criterion. Process planning is connected with optimizing the resources and processing costs as well as processing time. Consequently, the object function used in process planning and its optimization is to minimize the number of rejects and the total processing costs, as well as minimizing the time required to complete all operations.

MetCAPP : TECHNOLOGY MODULE MANAGER AND TECHNICAL FEATURES

Moreover, MetCAPP develops a process plan based on specific elemental manufacturing features. This approach can be used to decompose a very complex part into a number of separate manufacturing features. The process planner still has a full control over the plan by determining the order in which the features are selected and included in the process plan.

Process planning is the glue between product, process, and resources. It is necessary ability to manipulate, view, and deliver multiple data formats and types. Today’s solutions are, at best, short term. Systems should be designed to reflect this, or allow incremental changes. MetCAPP Software analyses the manufacturability of proposed design as follows:

1) Finding Machining Features

Knowledge Based Machining

Technology Module Manager

Milling Module

Milling Module

Manufacturing

technology

database

Rules

Features

Rules

Features

Turning Module

Hole making module

Many aspects of feature recognition problem are still open and active areas of research. Among these are: recognizing and representing interactive features, incremental recognition of features, and incorporation of user customizable feature classes. As an input, MetCAPP takes solid models (for instance from SolidWorks- a 3D software) of a part P and stock S, along with tolerance specifications for P. The tolerance specifications tell how much variation from the nominal geometry is allowable in any physical realization of a part P.

An operation plan is a sequence of machining operations capable of creating P from S. A workpiece is the intermediate object produced by starting with S and performing zero or more machining operations. The machining operations in MetCAPP currently considered are (end milling, side milling, face milling and drilling). Each machining operation will create either a primary feature or a truncation of primary features from P and S. MetCAPP generates F automatically from solid models of P and S.2) Generating Feature Based Models (FBM’s)

A feature Based Model (FBM) is any irredundant subset of features - F such that P can be produced from S by removing the features in F. Each operation plan O of interest corresponds to an FBM, in the sense that each machining operation in O will create either a feature in F or a truncation of a feature in F. Since each FBM is a subset of , FBM can be generated using set-covering techniques.3) Generating Operation Plans

Each FBM can lead to several operation plans, of which some are better than others. Thus, to generate operation plans from a given FBM, MetCAPP again does a depth-first-branch-and-bound search. Due to various types of interactions (accessibility, set-up, etc) among the features in FBM F, these intersections introduce precedence constraints requiring that some features of F be machined before or after other features. MetCAPP generates a total orderings on F consistent with the precedence constraints.4) Operation Plan Evaluation

Designers give design tolerance specifications to specify how far the design can vary from its nominal geometry. To verify whether a given operation plan will satisfy the design tolerances, MetCAPP must estimate what tolerances the operations can achieve. Unlike typical approaches for computer-aided tolerance charting, which are computationally very intensive and only consider limited types of tolerances, MetCAPP evaluates the manufacturability aspects of a wide variety of tolerances.

In manufacturing planning the goal to be achieved is represented by a design specification. In planning a sequence of machining operations it is physically impossible to produce the exact nominal geometry of the design, so the objective is to find any reliable plan which can produce an approximation of the design geometry that satisfies various design tolerances. In addition, it is advantageous to have highly differentiated view of the production costs.

CAD SYSTEM

Identify Features

2. Generate FBM

3. Generate Plan

4. Evaluate Plan

5. Feedback

CAD models of the part P and stock S

Find all primary machining features for P. call this set

Generate the feature-based model F.

Generate an operation plan O for F. If O can satisfy P’s machining tolerances, then estimate its cost and time

Information about P’s manufacturability

Designer

THE BASIC APPROACH USED IN MetCAPP

5.1 The MetCAPP features

Automated Feature RecognitionGenerates the flow of data from solid models directly into MetCAPP. This module allows users to

import 3D solid CAD models into MetCAPP and then automatically analyzes the part to extract manufacturing features for sequencing and process plan generation. Process Documentation. MetCAPP’s report writer

Allows users to merge texts and graphics, including CAD drawings, photographs, electronics documents and bar codes into a single document. This can be printed, sent to the floor electronically or through Application Programme Interface (API) to other parts of the IP system (eg:- NC tape generation, MRP or order entry) Graphics. MetCAPP’s redline capability

Allows the user to add layers of annotations to a file without changing the original drawing / graphic. MetCAPP supports over 40 different graphic file types for viewing, printing, and redline/markup.

The MetCAPP Technology ModulesThese contain rules and data to support a wide range of features. These automatically select a process

sequence, tools for each step and speeds/feeds for each machining pass. The technology modules evaluate the capabilities of the machine and utilize as much machine horsepower as is available at the selected speed range. Templates and Formulas

Provide MetCAPP users the flexibility to define tasks and work procedures specific to their operations. Recall and replication of these on demand further enhances planner productivity. Cost Estimating

Costed routings with accurate tooling, fixturing, and materials provide the estimator with strong quotation support. Group Technology

MetCAPP provides the ability to interrogate a standard database of process plans and identify parts and assemblies by their characteristics. This enables identification of similar parts for more rapid plan generation as well as strong support for configuring products in order entry.

5.2 MetCAPP BENEFITS

- 50 % increases in process planner productivity.- 40 % increase in existing equipment’s capacity.- 25 % reduction in setup costs.- 12 % reduction in tooling requirements.- 10 % reduction in scrap and rework.- 10 % reduction in shop floor labor.- 6 % reduction in work-in-process.- 4 % reduction in material usage.These are in addition to the overall gains resulting from:

- Connecting process planning to their CAD systems for swift feedback, rapid and accurate data transfer, plus work-in-process images when desired.

- Linking process planning to CAM systems.- Linking process planning to Enterprise Planning System, MRP/ERP, yielding a single point of

entry.Today process planning and workshop scheduling in industry are carried out as sequential, non-

collaborative tasks. This has several disadvantages and can be improved by making these activities partly concurrent or at least collaborative. The integration or collaboration of scheduling and process planning has been the focus of extensive international research efforts in recent years. To achieve the overall goals is necessary to be followed the specific technical objectives with consideration of reliability, maintainability, and supportability. A reliable and user-friendly interface to standard CAD systems used in industry is urgently required to close the gap in the CAD-CAM information chain. The MetCAPP system highlights the requirements that a nowadays CAPP system must meet, namely: flexibility, modularity, interoperability, autonomy, and scalability. These have been selected based on weakness of the current available CAPP systems. 1. Automated transfer of geometry and technology information from CAD reduces the effort spent on entering CAD data in to a CAPP system, and 2. Powerful CAPP modules for interactive, semi – automated and generative process planning and full support for time and cost calculation.

Non – linear concept used, for instance in MetCAPP, is especially suited for production environment like mechanical manufacturing of discrete parts of the pilot user.

The use of powerful CAPP tools that meet the performance requirements will improve process-planning quality with respect to applied manufacturing technology and accuracy of time and cost calculation. This will result in better utilization of the available manufacturing resources, more exact product costing, improved product quality and generally speaking towards a safer world. Collaboration between process planning and scheduling will improve the logistical quality of process plans through feedback of loading information.

As a computer aided process planning system, enables the process engineer and/or the cost estimator to more effectively and safely plan the manufacturing process. MetCAPP users realize improved productivity

in reduced process time and variability, reduced inventories and higher product quality levels, and in general safer production. Manufacturing can use MetCAPP for more reliable planning, estimation and shop floor control of manufacturing operation leading towards reduction in number of poor parts and hence guarantee better future performance, as well as improved competitiveness and productivity in a safer environment.

CAPP BENEFITS

Significant benefits can result from implementation of Computer Aided Process Planning. In a detailed survey of twenty – two large and small companies using generative type CAPP system, the following estimated cost savings were achieved.

- 58 % reduction in process planning effort- 10 % savings in direct labor- 4 % savings in material- 10 % savings in scrap- 12 % savings in tooling- 6 % reduction in work process

In addition there are intangible benefits as follows:

- Process rationalization and standardization- Increased productivity of process planners- Reduced process planning and production lead time; faster response to engineering changes- Greater process plan consistency, access to up to date information in a central database- Improved cost estimating procedures and fewer calculation errors- More complete and detailed process plans- Improved legibility- Improved production scheduling and capacity utilization- Improved ability to introduce new manufacturing technology and rapidly update process plans to utilize

the improved technology.6. CONCLUSIONCAPP is a highly effective technology for discrete manufacturers with a significant number of products and process steps. Rapid strides are being made to develop generative planning capabilities and incorporate CAPP into a computer integrated manufacturing architecture. The first step is the implementation of GT or FT classification and coding. Commercially available software tools currently exist to support both GT and CAPP. As a result, many companies can achieve the benefits of GT and CAPP with minimum cost and risks. Effective use of these tools can improve a manufacturer’s competitive advantage too.

REFERENCES Mikell P. Groover & Emory W. Zimmres. Jr, “ Computer Aided Desibn and Manufacturing”, Prentice Hall Publication, 1994. “CAPP turning Manufacturing”, The Machinist, May – june 2003 http://www.cimplex.com/metcapp.hmt

“Computer Aided Process Planning based on Information Management”, journal of Materials Processing Technology 103 (2000) 120 – 127 “Computer Aided Process Planning” , Kenneth Crow, DRM Associates. “ A Reliable Knowledge Based Computer Aided Process Planning Application – Case of MetCAPP Software”, Galia Novakova, PhD student, Polytechnical University of Turin, Department Of Production Systems and Economics. Mikell P. Groover “Automation Production Systems and Computer integrated Manufacturing”, Prentice Hall India Pvt Ltd, 1997 James.a.Rehg and H.W. Kraebber, “Computer Integrated Manufacturing”, Pearson Education Asia, 2002.