GUIDELINES FOR

Improving Plant Reliability through Data Collection and Analysis

CENTER FOR CHEMICAL PROCESS SAFETY of the

AMERICAN INSTITUTE OF CHEMICAL ENGINEERS

3 Park Avenue, New York, New York 10016-5901

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GUIDELINES FOR

Improving Plant Re1 iabil ity through Data Collection and Analysis

Publications Available from the CENTER FOR CHEMICAL PROCESS SAFETY

of the AMERICAN INSTITUTE OF CHEMICAL ENGINEERS

CCPS Guidelines Series

Guidelines for Improving Plant Reliability through Data Collection and

Guidelines for Pressure Relief and Effluent Handling Systems Guidelines for Design Solutions for Process Equipment Failures Guidelines for Safe Warehousing of Chemicals Guidelines for Postrelease Mitigation in the Chemical Process Industry Guidelines for Integrating Process Safety Management, Environment,

Guidelines for Use of Vapor Cloud Dispersion Models, Second Edtion Guidelines for Evaluating Process Plant Buildings for External Explosions

and Fires Guidelines for Writing Effective Operations and Maintenance Procedures

Guidelines for Chemical Transportation Risk Analysis Guidelines for Safe Storage and Handling of Reactive Materials Guidelines for Technical Planning for On-Site Emergencies Guidelines for Process Safety Documentation Guidelines for Safe Process Operations and Maintenance Guidelines for Process Safety Fundamentals in General Plant Operations Guidelines for Chemical Reactivity Evaluation and Application to Process

Tools for Making Acute k s k Decisions with Chemical Process Safety

Guidelines for Preventing Human Error in Process Safety Guidelines for Evaluating the Characteristics of Vapor Cloud Explosions,

Flash Fires, and BLEVEs Guidelines for Implementing Process Safety Management Systems

Guidelines for Safe Automation of Chemical Processes Guidelines for Engineering Design for Process Safety Guidelines for Auditing Process Safety Management Systems Guidelines for Investigating Chemical Process Incidents Guidelines for Hazard Evaluation Procedures, Second Edition with Worked

Plant Guidelines for Technical Management of Chemic.1 Process Safety,

Analysis

Safety, Health, and Quality

Design

Applications

Examples

Revised Edition Cmiinued at the end of this book

GUIDELINES FOR

Improving Plant Reliability through Data Collection and Analysis

CENTER FOR CHEMICAL PROCESS SAFETY of the

AMERICAN INSTITUTE OF CHEMICAL ENGINEERS

3 Park Avenue, New York, New York 10016-5901

Copyright 0 1998 American Institute of Chemical Engineers 3 Park Avenue New York. New York 10016-5901

All rights reserved. N o part of this publication may be reproduced, stored in a retrieval system, o r transmitted in any form o r by any means, electronic, mechanical, photocopying, recording, o r otherwise without the prior permission of the copyright owner.

Library of Congress Cataloging-in Publication Data Guidelines for improving plant reliability through data collection and

analysis /Center for Chemical Process Safety of the American Institute of Chemical Engineers

P. cm. Includes bibliographical references and index.

1. Chemical process control-Statistical methods. ISBN 0-8169-0751-X

2. Reliability (Engineering)-Statistical methods. Chemical Engineers. Center for Chemical Process Safety. TP155.75 .G85 1998 98-39578 660 ' .2815-dc2 1 CIP

1. American Institute of

This book is available at a special discount when ordered in bulk quantities. For information, contact the Center for Chemical Process Safety at the address shown above.

It is sincerely hoped that the information presented in this document will lead to an even more impressive record for the entire industry; however, the American Institute of Chemical Engineers, its consultants. CCPS Subcommittee and Process Equipment Reliability Database project members, their employers, their employers' officers and directors, and Det Norske Veritas (USA) Inc.. disclaim making or giving any warran- ties or representations, express or implied, including with respect to fitness, intended purpose, use or mer- chantability and/or correctness or accuracy of the content of the information presented in this document. As between (1) American Institute of Chemical Engineers, its consultants, CCPS Subcommittee and Process Equipment Reliability Database members, their employers, their employers' officers and directors, and Det Norske Veritas (USA) Inc., and (2) the user of this document, the user accepts any legal liability or responsi- bility whatsoever for the consequence of its use or misuse.

Preface

Acknowledgments

xi

xiii

1 Introduction

1.1. Background 1.2. Taxonomy 1.3. Data AggregatiodSharing

2 Definitions

2.1. Introduction 2.2. Discussion of Key Reliability Terms 2.3. Glossary of Terms

.3 Methods of Analysis

3.1. Introduction 3.2. Basic Concepts of Data Analysis

3.2.1. Failure Data 3.2.2. Need for Correct Failure Modes 3.2.3. Types of Systems-Repairable or Nonrepairable 3.2.4. Reliability versus Availability

7 7 7

10

17 17 18 18 18 18

19

V

vi Contents

3.2.5. Types of Data-Censoring 3.2.6. Definitions 3.2.7. Dealing with Censored Data 3.2.8. Common Cause Failures 3.2.9. Predictive versus Descriptive Methods

3.3. Data Manipulation Examples 3.3.1. Methods of Analysis

3.4. Cyclical Service 3.5. Batch Service 3.6. Standby Service 3.7. Failures Following a Repair 3.8. Selecting an Operating Mode 3.9. Analysis Based on Statistical Inferences

3.9.1. Modeling Reliability Parameters for the Population 3.9.2. The Weibull Distribution 3.9.3. Graphical Method for Estimating the Weibull Parameters 3.9.4. The Exponential Distribution 3.9.5. Confidence Limits for Reliability Parameters

References

4 Example Applications

4.1. Introduction 4.2. Conducting a Reliability Analysis-Pump Example 4.3. Right-Censoring 4.4. MTTF by Numerical Integration 4.5. Reliability Calculations for Repaired Items 4.6. Calculation of MTTR by Numerical Integration 4.7. Fitting a Weibull Distribution 4.8. Combinations of Failure Distributions 4.9. System Performance-Compressor Example 4.10. Life-Cycle Costs-Compressor Example (continued) 4.11. Maintenance Budgeting-Compressor Example

4.12. Throughput Targets-Compressor Example (continued) 4.13. Summary References

(continued)

19 20 21 22 22 23 23 38 38 38 38 39 39 40 40 41 43 43 46

47 47 48 52 54 56 56 60 61 64 70

7 2 7 2 7 5 75

Contents vii

5 Data Structure

5.1. Data Structure Overview 5.2. General Taxonomy

5.2.1. Taxonomy Levels 1 4 (Industry, Site, Plant, Process Units) 5.2.2. Taxonomy Levels 5-7 (System, Component, Part) 5.2.3. Treatment of Subordinate Systems in the CCPS Database

5.3.1. Inventory Tables 5.3.2. Event Tables 5.3.3. Failure Logic Data

5.3. Database Structure

6 Quality Assurance of Data

6.1. Introduction 6.2. Basic Principles of Quality as Applied

6.3. Quality Management 6.4. Quality Principles 6.5. Verification of Data Quality

to Equipment Reliability Data

6.5.1. Quality Plan for Database Administrator (DA) 6.5.2. Quality Plan for Data Subscribers 6.5.3. Certification of Data Subscribers 6.5.4. Internal Verification of Data Quality 6.5.5. Verification of Data Prior to Acceptance 6.5.6. Recertification of Data Contributors 6.5.7. Appeal Process 6.5.8. Audits of Work Process

APPENDIX I Guidelines for Data Collection and Submission

I. 1. Introduction I. 1.1. Data Types I. 1.2. Subscriber Data I. 1.3. Inventory Data

77 77 78 80 81 82

82 83 86

92

95 95

96 97 97 98 99 100 100 101 101 101 102 102

103 104 104 104 105

viii Contents

I. 1.4. Event Data I. 1.5. Data Analysis I. 1.6. Database Limitations 1.1.7. Goals of the Equipment Reliability Process 1.1.8. Certification of a Subscriber

1.2.1. Introduction 1.2.2. Inventory Descriptions and Data Sheets I. 2.3. Event Descriptions and Data Sheets

1.2. Data Definitions and Descriptions

1.3. Data Flow 1.4. Internal Quality Assurance of Data

1.4.1. Data Input Organization 1.4.2. Quality Plan 1.4.3. Deviation Reporting

1.5. Data Submission Procedure 1.5.1. User Software Requirements 1.5.2. Data Submission Protocol I.5.3. Format of Data Submission 1.5.4. Availability of New Data

1.6. External Quality Assurance of Data I.6.1. Field Verapcation 1.6.2. Spot Checks I.6.3. Receipt and Logging I.6.4. Validation I. 6.5. Procedures for Nonconformities

1.7. Data Contribution and Data Distribution I. 7.1. Data Contribution I. 7.2. Data Distribution

APPENDIX 11 Sample Pick Lists for Data Fields

11.1. Pick Lists Related to Upper Level Taxonomy 11.2. Pick Lists Related to Plant Inventory and Events 11.3. Pick Lists Related to General Equipment Information 11.4. Pick Lists Related to Relief Devices 11.5. Tables Related to Compressors 11.6. Pick Lists Related to Heat Exchangers

113 1 13 114 115 125 128 128 128 142 149 150 150 151 154 154 154 154 155 155 155 155 155 155 156 156 157 157 158

159 159 160 161 163 167 171

Contents ix

APPENDIX 11 I Proced u re for Develo pi ng System- Level Tax0 nom i es

111.1. Background and Theory 111.1.1. Objective 111.1.2. Overview of the Taxonomy Development Process

111.2.1. Define the System 111.2.2. Analyze Functional Characteristics I I I . 2 , j Spcifr the Inventory Data 111.2.4. Specifi the Event Data

111.2. Procedure

References

172 172 172 1 73 175 1 75 178 182 184 188

Index 189

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Preface

The unique value of this book is that it is the defining document for an industry-wide Plant and Equipment Reliability Database. The intent, struc- ture, and implementation of the database are described fully within the book and its appendices. This Guideline book, developed for the Center for Chemical Process Safety (CCPS), is designed as a text to be used by operating and maintenance staff, reliability engineers, design engineers, and risk analysts. It treats the broad topic of equipment reliability, but also provides details about the design and operation of a process-plant/equip- ment reliability database.

The major objective of this book is to lay the foundation for an indus- try-wide reliability database. In fulfilling this objective, the book satisfies three auxiliary objectives. The first is to document and explain the theory of reliability data, including failure rates and the data structure employed by CCPS to accomplish its goals. The second is to demonstrate the useful- ness of quality data by presenting worked examples. The text emphasizes that data needs are driven by analyses that provide added value. The book will help to illustrate this point. It will also help the reader understand how to actually carry out the analyses. The third objective is to provide an over- view for the necessary quality assurance that must be implemented by both the plants maintaining a local database and a centralized database adminis- trator to whom data is submitted for aggregation and distribution.

After an introduction to the purpose and basic operating concepts of the database in Chapter 1, the necessary background and terminology for reliability data analysis are developed in Chapters 2 and 3. Chapter 4 pro- vides example applications of developing reliability data. Chapter 5 covers the details behind the structure of the CCPS database. Chapter 6 deals with quality assurance for the database.

A set of appendices provides specific information about database oper- ating guidelines, pick lists, and a procedure for developing future equip- ment taxonomy information.

xi

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The Center for Chemical Process Safety (CCPS) wishes to thank all the company representatives of the sponsor companies of the Process Equip- ment Reliability Database Project who provided the invaluable guidance in the development of this protocol. In particular, the leadership of Mr. Hal Thomas of Air Products and Chemicals as Project Chairman, was instru- mental in the completion of this project. CCPS also wishes to express its appreciation to the members of the equipment subcommittees for the development of the database taxonomies.

The company representatives include the following individuals:

Hal Thomas (Air Products & Chemicals) Ed Zamejc (Amoco Corporation), Donnie Carter and Patrick McKem (ARCO) Malcolm Hide (BOC Group) Colin Wills and Bobby Slinkard (BP Oil International) Richard King and Peter Hughes (Caltex Services Corp) Ashok Rakhe and Dan Long (Celanese Limited) Wilbert Lee (Chevron Research and Technology Co.) Ted Bennett (Dow Chemical Co) Roy Schuyler (DuPont Engineering) Tom Whittemore and Mark Templeton (Eastman Chemical Co.) Robert Motylenski (Exxon Research & Engineering Co) Kumar Bhimavarapu (Factory Mutual Research Corp) Jack Dague (GE Plastics) Larry Meier and Keith Burres (Hartford Steam Boiler Inspection

Gary Helman (Hercules, Inc) Malcolm Preston, John Nigel, and Keith Buchwald (ICI) Adrian Balda (Intevep S.A.)

and Insurance Co)

... XI11

xiv Acknowledgements

Tetsuo Shiro and Morio Fujimura (Mitsubishi Chemical Co.) Carlton Jensen (Phillips Petroleum Co) William Angstadt and Richard Pettigrew (Rohm and Haas Co) Harley Tripp, John Reynolds, and Mike Drossjack (Shell Oil Co) Rob Mann and Darrel Alger (Syncrude Canada, Ltd) Tommy Martin (Texaco USA) Douglas Cramer (Westinghouse Savannah River Co).

The Equipment Subcommittee Chairman included:

Paul Altpeter-Compressors (Air Products and Chemicals Co) William Angstadt-Instrumentation (Rohm and Haas Co) Ted Bennett-Furnaces (Dow Chemical Co) Douglas Ferguson-Vessels (DuPont Engineering) Tommy Martin-Piping (Texaco, USA) Larry Meier-Heat Exchangers (Hartford Steam Boiler Inspection

Tom Whittemore, Jr.-Pumps (Eastman Chemical Co) Ed Zamejc-Pressure Reliving Devices (Amoco Corporation).

Det Norske Veritas (USA) Inc. (DNV), Houston, Texas, was the contrac- tor who prepared these Guidelines and is providing the software develop- ment. Bernie Weber was DNV’s Project Manager. The principal authors were Mike Moosemiller, and Bernie Weber. A special thanks to Anne McKinney for her technical assistance and to Kathy Dubiel and Kelly Holmstrom who provided dedication and skill in manuscript preparation.

This project is the fruition of equipment reliability database projects starting in 1987 championed by Les Wittenberg, CCPS and managed by Joseph Metallia as a Staff Consultant for CCPS. Les and Joe struggled with how to get a database going over much criticism. In late 1997 Joe Metallia turned over the project management to a new staff consultant, David Belonger. Andrew Wolford of DNV provided many creative ideas and lived through the lean years. His contributions to obtain sponsors were key to the on-going database.

We gratefully acknowledge the comments and suggestions submitted by the following companies and peer reviewers: Lucia Dunbar (AEA Tech- nology), G. Bradley Chadwell (Battelle Memorial Institute), Daniel Crow1 (Michigan Technological University), Robert L. Post (Rohm and Haas Com- pany), Brian D. Kelly (Syncrude Canada Ltd).

and Insurance Co.)

1

1 .l. Background

Introduction

Quality failure rate data have long been a desire within the Chemical Pro- cess Industry. Unfortunately, too often the emphasis has been on the col- lection of data (which in and of itself is useless) rather than on value-added uses of data. This implies that one must answer the question of what to do with the data once it is collected. To some extent this is done, but generally the effort has been cut short and has mainly addressed perceived data requirements, regulatory requirements, and data that make day-to-day work assignments more efficient, or provides proof of work performed. The type of information that would allow more effective continuous improvement is too often included without any real thought other than, “sounds like we should have it,” or “we might need it someday.”

The major objective of this book is to lay the foundation for an indus- try-wide reliability database. The database has been designed to make avail- able high quality, valid, and useful data to the hydrocarbon and chemical process industries enabling analyses to support availability, reliability, and equipment design improvements, maintenance strategies, and life cycle cost determination. By design, the database structure contains voluminous detail; however, not all of the detail is required by the user. Each operating company decides the amount of detail input by the user. In fact, the level of detail required for basic analyses is minimal. The detail of the results, how- ever, will be commensurate with the details input to the database.

The foundation for the database was developed from a project directed by the Center for Chemical Process Safety (CCPS). The CCPS has formed a group of sponsor companies to support and direct this effort. The sponsor companies, through representatives on a Steering Commit- tee, are actively participating in the design and implementation of the data- base.

1

2 1. introduction

(~I------+pzzz-lnformationI~~ FIGURE 1.1 The role of data in the decision-making process.

Economic Risk Social Risk

This book, which is expected to be the first in a series, lays out the fun- damental concepts of data collection in a way that is intended to provide useful information for decision making as shown in Figure 1.1.

A successful system converts data into information useful for making value added decisions, which can be economic, or safety related in nature. In all cases these translate into business risk as shown in Figure 1.2.

The main objective of this book is to provide the basis for data struc- ture and collection methods to support reliability analyses. In turn, it is hoped that this book will promote the systematic collection and analysis of plant and equipment data. A secondary objective is that this book will serve as a guideline for the CCPS plant and equipment reliability databases and subsequent projects in this field.

Making this happen requires the understanding and integration of sev- eral cross-functional disciplines. As such this book is intended for use by

Maintenance Engineers Reliability Engineers Design Engineers Production Engineers Information Technology Software Developers Process Safety Risk Analysts

By utilizing basic industry management systems that exist at every facil- ity, it is possible to leverage these systems in a way that provides data in a cost effective manner for further value-added analyses and subsequent decisions. Examples of value-added analyses are best equipment for appli- cation, optimal test intervals, knowledge of system or component wear out, optimal maintenance strategy or improved risk analysis. In turn these provide the foundation for achieving improved plant availability and/or reliability and reduced risk.

Environmental Risk Safety Risk

1.2. Taxonomy 3

As the need for more sophisticated analysis increases, so does the need for higher quality, more specific data. This is illustrated by Figure 1.3. Chapters 3 and 4 provide more detail regarding the types of data required for the varying complexity of analyses.

1.2. Taxonomy

An effective taxonomy produces useful data for reliability analyses. The basic building blocks for a reliability analysis fall into two main classes: data regarding specific events occurring for a piece of equipment, and data describing the sample space of equipment. The first class (Event Data) is used as a numerator in the reliability calculation, the second class (Inven- tory Data) is used in the denominator. Chapter 5 is dedicated to the description of the inherent taxonomy used in the database.

High

FIGURE 1.3. Detail of data required fot comp/exifyofana/ysis.

4 1. Introduction

The taxonomy and database structures have been developed to facili- tate analysis, and are shown in Figure 1.4. A taxonomy such as this will allow sorting and selection of specific types of data, with the types of design, operational, and environmental conditions, which are similar to that of interest in your plant.

E l Site E l Plant E l Unit E l System

Component u

Inventory Data Made Up Of: -Unique Item Data

Fl Event I I I

I 1

FIGURE I .4. CCPS database taxonomy.

1.3. Data AggregatiodSharing 5

1.3. Data Aggregation/Sharing

CCPS hopes to provide the foundation that allows the hydrocarbon and chemical process industry to establish a standard. This is important because it allows for different systems to become more compatible, increasing the value of industry data. Benefits accrue from being able to aggregate data without degrading its quality. Figure 1.5 shows the CCPS concept, with CCPS acting as an industry clearinghouse.

This concept allows individual plants the ability to measure their per- formance and to seek improvement in their designs and maintenance strat- egies. At the company level, it allows the performance comparison of its plants.

CCPS Industry Database

A A ..........................................................................................................................

Company 3 Database

Company 1 Company 2 Database Database

A :. ................... .............................................................................

Database Database Database

f Inventory FtJ

loata Event - FIGURE 1.5. CCPS data daregation concept.