Computer Aided Maintenance

Computer-aided Maintenance facility layout. Department of Industrial Engineering. safety. Manufacturing information systems. computerintegrated manufacturing. Issues which are addressed in this series include. material handling. USA The globalization of business and industry and the worldwide competitive economy are forcing business leaders in the manufacturing and service sectors to utilize fully the best equipment and techniques available. University of Louisville.Manufacturing Systems Engineering Series Series editor: Hamid R. The objective is to have efficient control of the organizational structure in order to produce high quality products at lower prices within a shorter period of time. but are not limited to. The aim of the Manufacturing Systems Engineering Series is to provide an outlet for state-of-the-art topics in manufacturing systems engineering. Parsaei. The development of the discipline has helped industry to become more productive and to make more efficient use of resources. We hope that researchers both in academia and government. The recent emphasis and concern about the environment and product recyclability and re-usability have brought new perspectives and more challenges to this ever-growing engineering discipline. as well as private . This series is also intended to provide a scientific and practical basis for researchers. Since the introduction of computers in the 1950s. the following: • • • • • • • Production system design and control Life cycle analysis Simulation in manufacturing Manufacturing cost estimating Industrial safety Fuzzy logic and neural networks in manufacturing CAD/CAM/CIM We would welcome proposals to write material for this series from colleagues and industry leaders around the world. and production planning and shop floor control are just some of the areas in which manufacturing systems engineers have been traditionally involved in order to help improve understanding and awareness in the manufacturing and service sectors. Manufacturing Systems Engineering has experienced tremendous growth. total quality management. practitioners and students involved in manufacturing systems areas. value engineering and cost analysis. Parsaei.organizations and individual practitioners. Smith 4 Rapid Response Manufacturing Edited by Jian Dong . will find this series informative and worthwhile. Hanley 2 Integrated Product. Sai Kolli and Thomas R. Process and Enterprise Design Edited by Ben Wang 3 Occupational Ergonomics Fariborz Tayyari and James L. 1 Manufacturing Decision Support Systems Edited by Hamid R. Computer-aided Maintenance Methodologies and Practices Edited by Jay Lee National Science Foundation Virginia USA and Ben Wang FAMU-FSU College of Engineering Florida USA SPRINGER SCIENCE+BUSINESS MEDIA.V. . B. electronic or mechanical. UK . including photocopying.A c. recording or by any information storage and retrieval system. Frimley.P.I. Typeset in 10/12 Palatino by Cambrian Typesetters. Surrey. without written permission from the copyright owner.1007/978-1-4615-5305-2 Printed an acid-free paper AH rights reserved © 1999 Springer Science+Business Media Dordrecht Origina1ly published by Kluwer Academic in 1999 Softcover reprint of the hardcover Ist edition 1999 No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means. Catalogue record for this book is available from the Library of Congress A catalogue record for this book is available from the British Library ISBN 978-1-4613-7421-3 ISBN 978-1-4615-5305-2 (eBook) DOI 10. Tomohiko Sakao and Yoshiki Shimomura 117 7.Contents List of contributors Preface PART ONE ix Xl Methodologies 1 1. John Tsai and John Fildes 19 3. Machine performance estimation and reliability modeling Chang-Ching Lin and Ben Wang 86 6. Fundamentals of maintenance Gerald M. maintenance and life-extending control of continuous-time production processes Asok Ray and Shashi Phoha 136 8. An integrated automated root cause identification fuzzy neural network reasoning for quality control Farhad Tadayon and Jay Lee 170 9. Maintenance using activity-based costing (ABC) Alice S. Tetsuo Tomiyama. Fundamentals of sensory systems for maintenance engineering Jay Lee. Related work on machine monitoring and diagnostics Hsin Hao (Tom) Huang and Ben Wang 41 4. Tsai 181 . Integrated prognostics. Knapp and Ben Wang 3 2. Design methodology for self-maintenance machines Yasushi Umeda. Parametric modeling methods: theory and a case study Julie Spoerre and Ben Wang 59 5. Yuan-Shin Lee and H. Holloway 17. Williams 16.viii Contents 10. Life extension of operating machinery using the 231 National Information Infrastructure (Nil) Shashi Phoha and Asok Ray PART TWO Case Examples 12. Life cycle maintenance management Shozo Takata 209 11. Joel Trussell 13. Case Example 3: Measurement of machine 302 performance degradation using a neural network model Jay Lee 15. Case Example 4: Detection and isolation 318 of faults in the stamping process using the Haar transform Christopher K. Chukwujekwu Okajor Index 407 . Case Example 2: Data analysis for diagnostics 281 and process monitoring of automotive engines Bruce D. Case Example 6: In-process diagnosis of 356 tool failures in milling KazuoMori 18. Case Example 5: Fault monitoring in 339 manufacturing systems using template models Lawrence E. Case Example 7: Monitoring and predicting 379 surface roughness and bore tolerance in end-milling A. Case Example 1: Motor incipient fault 261 263 detection using artificial neural network and fuzzy logic technologies Mo-yuen Chow.H. Marko 14. Koh and William J. Bryant and Kenneth A. Raleigh. Raleigh. North Carolina State University. Taiwan Kenneth Marko Ford Research Laboratory. USA Mo-Yuen Chow Department of Electrical and Computer Science. Taipei County. University of Kentucky. Hu-Wei. USA Kazuo Mori Department of Manufacturing Systems. Tam-King Road. Dearborn. Industrial and Manufacturing Systems Engineering. USA Christopher Kok-Hwee Koh School of Mechanical and Production Engineering. Knapp Maintenance and Reliability Research Unit. Sec. MI. 4. 499. Agency of Industrial Science and Technology. USA Yuan-Shin Lee Department of Industrial Engineering. St John's and St Mary's Institute of Technology. Lexington. Room 585. Arlington. 414F CRMS Building. 3128 CEBA Building. LA 79893. KY 40506-0108 USA Gerald M. Rolla. Tsukuba City. MI. Singapore 639798 Jay Lee National Science Foundation. 4201 Wilson Boulevard. NC 27695. VA 22230. USA Chang-Ching Lin Department of Industrial Engineering and Management. Namiki 1-2. National Yunlin Polytechnic Institute. Dearborn. Nanyang Avenue. University of Missouri-Rolla. Nantang Technological University. Lawrence Holloway Center for Manufacturing Systems. MO 65409. USA . Japan Anthony Okafor Department of Mechanical Engineering. Ibaraki 305. Tamshui. Louisiana State Univesity. Taiwan. USA Hsin-Hao (Tom) Huang Industrial Engineering. Ford Motor Company. Ford Motor Company. Mechanical Engineering Laboratory.Contributors Bruce Bryant Ford Research Laboratory. Baton Rouge. MITI. Box 7911. North Carolina State University. 64 Wun-Hua Road. NC 27695-7911. UT 84047 USA John Tsai 7400 S. Japan Tetsuo Tomiyama Department of Precision Machinery Engineering. Bunkyo-ku. NC 27695-7911. USA . College of Technology. Chuoku. PO Box 30. Shinjuku-ku. Japan Ben Wang Department of Industrial Engineering. Bunkyo-ku. Hongo 7-3-1. University of Tokyo. FSU/FAMU. UT 84947 USA Yasushi Umeda Department of Precision Machinery Engineering. The Graduate School of Engineering. The Graduate School of Engineering. Carbondale. Japan H. Kansas 67401-8196. Ann Arbor. MI 48109-2122. State College. PA 16802. Apt 13303. Okubo 3-4-1. Midvale. Waseda University. Bunkyo-ku. University Park.x Contributors Shashi Phoha Information Systems. 2409 Scanlan Avenue. Japan Yoshiki Shimomura Mita Industrial Co. Tokyo 169. Tokyo 113. Mailcode 6603. Applied Research Laboratory. Midvale. FL 32310-6046. IL 62901. Salina. Tallahassee. USA Shozo Takata Department of Industrial Engineering. Tokyo 113. 1301 Beal Avenue. Hongo 7-3-1. University of Tokyo. Williams Department of Electrical Engineering and Computer Science. Japan Julie K. Apt 13303. Joel Trussel Department of Mechanical and Computer Engineering. USA Tomohiko Sakao Department of Precision Machinery Engineering. University of Tokyo. 2525 Pottsdamer Street. USA Asok Ray Mechanical Engineering Department. Ltd. Hongo 7-3-1. USA Alice Tsai 7400 S. USA Farhad Tadayon Technology Assistance Center. The Pennsylvania State University. USA William J. State St. University of Michigan. Penn State University. State St. Southern Illinois University. Tamatsukuri 1-2-28. Tokyo 113. Spoerre College of Engineering. PS 16804. North Carolina State University. Osaka. The Graduate School of Engineering. Raleigh. helps reduce scrap and rework. digital condition monitoring. and improves consistency and quality of the part. With the revolutionary advances in information. and life cycle engineering. cost. it covers recent advances in reliability. and computing technologies. This book introduces modern theories. Two issues regarding computer-aided maintenance are addressed: the first issue is the fundamental knowledge. including both theories and methodologies required for practitioners to perform maintenance activities effectively. design for self-maintenance machines. technologies. The recent rush to embrace advanced sensors and control systems in modern equipment has further increased the use of relatively unknown and untested technology. only a small fraction of the downtime is spent repairing the equipment that causes the failure. Typically. we forsee needs for new approaches in design. telecommunication.Preface Equipment reliability and maintenance drastically affect the three key elements of competitiveness . Chapter 1 introduces the fundamentals of maintenance. In addition. signature analysis. techniques and tools such as artificial intelligence. and human resources in the modern factory. process. Well-maintained equipment holds tolerances better. Part One (Chapters 1 to 11) of the book introduces new methodologies which lay a foundation for readers to understand the recent advances in maintenance techniques and methods. based on the introduced theories and methodologies. including the . A substantial part of the downtime is spent on locating the source of the problems. and product lead time. expert systems and neural networks for effective maintenance engineering.quality. Difficulty in identifying the causes of system failures has been attributed to several factors. Part Two (Chapters 12 to 18) provides readers with 'how to know' knowledge and practices by illustrating the introduced methodologies using seven case studies. and the use of materials. The book is divided into two parts with a total of 18 chapters. to solve problems in a very short time frame in order to guarantee success. when a production system goes down. the second and equally pressing issue is to understand how to implement the right maintenance tools and techniques. including system complexity and a lack of knowledge and adequate troubleshooting tools. sensor fusion. A particular example of a selfmaintenance copier is examined to illustrate the design practices. and self-recovery strategy. Chapter 4 focuses on the parameter modeling which deals with the exponentially weighted moving average (EWMA) model for monitoring a process standard deviation as well as the autoregressive (AR) model for the estimation of process parameters. The editors wish to thank the authors and reviewers who made this . maintenance. Chapter 2 introduces fundamental sensory systems related to maintenance engineering. Chapter 3 builds upon Chapter 2's foundation and addresses applied sensory systems for machine monitoring and diagnostics. and monitoring of surface roughness and bore tolerance in end-milling. machine degradation monitoring. In summary. tool failure monitoring in milling. including motor fault detection. repamng planning. Chapters 12 to 18 demonstrate the implementation of the introduced methodologies in the previous chapters for a number of applications. A Boeing door assembly process system is used to explain the applied quality control practices. A methodology dealing with condition-based maintenance for a complex continuous system is introduced. and operation algorithms. fault monitoring in a manufacturing system. including sensors. including the systematic understanding of fault monitoring. including the use of expert systems and an artificial networks system for maintenance practices. It is hoped that Computeraided Maintenance: Methodologies and Practices will bridge the gap for industrial users. fault recognition. Chapter 5 emphasizes the reliability modeling for machine performance including machine performance degradation modeling and fault detection. automotive engines diagnostics.xii Preface definitions of preventative maintenance. signal processing. deterioration process and machine diagnostics. this book takes a user-oriented. hands-on approach for practising engineers or managers to develop initial expertise in computer-aided maintenance methodologies. Chapter 11 examines life extension of operating machinery using the national information infrastructure (NIl). predictive maintenance. Chapter 9 illustrates maintenance using activity-based costing (ABC) for the system justification of deployment of a modern maintenance system. fault detection and isolation in the stamping process. as more and more companies embrace the modern computer-aided maintenance methodologies. Chapter 10 introduces a life cycle maintenance management system. eventually making world-class maintenance a requirement for modern factories to remain competitive and productive. Chapter 8 introduces a methodology for root cause identification using a fuzzy neural network approach. and lifeextending control of continuous-time production processes. Chapter 7 addresses an integrated prognostics. Chapter 6 introduces the design methodology for self-maintenance machines. Jay Lee Ben Wang . for the opportunity to edit the book.Preface xiii book a reality. Parsaei. the Series Editor. The editors also express their appreciation to Dr Hamid R.