Handbook of Total Quality Management

Handbook of Total Quality Management

Christian N. Madu, Ph.D Research Scholar, Professor and Chair

Management Science Program Editor-in-Chief, International Journal of Quality Science

Department of Management and Management Science Lubin School of Business

Pace University New York, USA

~ ., SPRINGER SCIENCE+BUSINESS MEDIA, B.V.

A c.1.P. Catalogue record for this book is available from the Library of Congress

ISBN 978-1-4613-7409-1 ISBN 978-1-4615-5281-9 (eBook) DOI 10.1007/978-1-4615-5281-9

All Rights Reserved © 1998 Springer Science+Business Media Dordrecht

Originally published by Kluwer Academic Publishers in 1998 Softcover reprint ofthe hardcover lst edition 1998

No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical,

inc1uding photocopying, recording or by any information storage and retrieval system, without written permission from the copyright owner.

This book is dedicated to my wife Assumpta and our three boys -

Chichi, Chike and Chidi

Contents

Contributors xi Foreword xv Preface xvii Biographical sketch xix Notable quality scholars xxi Glossary xxv

1. Introduction to quality 1 Christian N. Madu

2. Comparing Deming's and Juran's philosophies to the formation of total quality leaders' world views 21 Chu-Hua Kuei

3. Strategic quality planning 41 Bin Srinidhi

4. Quality improvement through learning curve analysis 87 Adedeji B. Badiru

5. Human resources and training 108 Amrik Sohal and Andrea Howell

6. Quality management in small and medium-sized companies and strategic management 128 M. Dolores Moreno-Luzon, F.J. Peris and F.J. Santonja

7. Developing attributes of quality for Internet applications 154 Christian N. Madu

8. Strategic total quality management 165 Christian N. Madu

9. Accounting and capital budgeting for quality 213 Vasanthakumar N. Bhat

10. Success in AMT implementation and quality enhancement: is there a link? 225 Hamid Noori, John L. Michela and Shailendra Jha

11. Service quality 245 Chu-Hua Kuei

viii Contents

12. Quality, productivity and information systems Joak Jurison

13. Total quality management in the supply chain Paul Levy

14. Involving the supply chain in design Jeffrey K. Liker and S. Nazli Wasti

15. Self-assessment Klaus J. Zink and Andreas Schmidt

16. Process performance, appraisal and employee development

260

275

304

320

planning 344 Ron S. Kenett and Marc E. Maisel

17. Introduction to ISO and ISO quality standards 365 Christian N. Madu

18. TQEM - methods for continuous environmental improvement 388 John F. Affisco

19. Benchmarking: a quest for continuous improvement 409 Injazz J. Chen and Kenneth A. Paetsch

20. Concurrent engineering 425 Joseph T. Emanuel and Dennis E. Kroll

21. Reengineering and continuous improvement 446 George W Arnold and M. Hosein Fallah

22. Quality function deployment 460 Mark A. Vonderembse and Tom Van Fossen

23. Introduction to probability and statistics 475 Christian N. Madu

24. Tools for quality control and process redesign 508 Nicholas C. Georgantzas

25. Statistical quality control 528 Christian N. Madu

26. Design of experiments: a polymer coating process 565 Nicholas Georgantzas

27. Quality engineering: loss functions, parameter design, and robust quality 593 Shane J. Schvaneveldt and Takao Enkawa

28. Reliability and maintainability 611 Surendra M. Gupta

Contents IX

29. Total quality management in China 626 Chyau Tuan and Linda Fung-Yee Ng

30. Total quality management in India: a tool with widening acceptance 638 Surendra K. Kaushik

31. The development of national consciousness of quality: the Singapore experience 650 Eric w.K. Tsang

32. Total quality management in Europe 665 Ton van der Wiele and Barrie Dale

33. Total quality management - implementation on the basis of Poland 682 Edward Kindlarski and Ben Bella Jaoko

34. The development of total quality management in Denmark 700 Jens J. Dahlgaard and Ove Hartz

35. Total quality in Australia and New Zealand 717 Danny Samson

36. Quality management in developing economies 734 Christian N. Madu

37. Malcolm Baldrige, Deming Prize and European Quality Awards: a review and synthesis 754 Pradeep Gopalakrishna and Mahesh Chandra

Appendix 769 Index 781

Contributors

Dr John F. Affisco, Professor of Business Computer Information Systems and Quantitative Methods, Frank G. Zarb School of Business, Hofstra University, Hempstead, NY 11550, USA.

Dr George W. Arnold ENGSCD, Director Standards and Intellectual Prop­erty, Lucent Technologies, Inc., Holmdel, NJ, USA.

Dr Adedeji B. Badiru, Professor of Industrial Engineering and Dean of University College, University of Oklahoma, Norman, Oklahoma, USA.

Dr Vasanthakumar N. Bhat, Professor of Management Science, Lubin School of Business, Pace University, New York, USA.

Dr Mahesh Chandra, Associate Professor of Computer Information Systems and Quantitative Methods, Frank G. Zarb School of Business Hofstra University, Hempstead, NY 11550, USA.

Dr Injazz J. Chen, Associate Professor of Operations Management DBA Program Co-ordinator, College of Business Administration, Cleveland State University, Cleveland, Ohio, USA.

Dr Barrie Dale, Professor of Quality Management, Manchester School of Management, University of Manchester Institute of Science and Technol­ogy, Manchester, UK.

Dr J. J. Dahlgaard, Professor, Research Group of Quality Management, The Aarhus School of Business, AARHUS V. Denmark.

Dr Joseph T. Emanuel, IMET Department, Bradley University, Illinois, USA.

Dr Takao Enkawa, Department of Industrial Engineering and Mgmt, Tokyo Institute of Technology, Tokyo, Japan.

Dr M. Hosein Fallah, Product Realization Technologies, Bell Laborato­ries, Holmdel, NJ, USA.

Dr Nicholas C. Georgantzas, Professor of Management Systems, Fordham University, Lincoln Center, New York, USA.

Dr Pradeep Gopalakrishna, Professor of Marketing, Lubin School of Business, Pace University, New York, USA.

xii Con tribu tors

Dr Surendra M. Gupta, the Director of the Laboratory for Responsible Manufacturing and is on the faculty of the Department of Mechanical, Industrial and Manufacturing Engineering at Northeastern University in Boston.

Dr Dve Hartz, Associate Professor, Dept of Industrial Management, Technical University of Denmark, Denmark.

Dr Andra Howell, Monash University, Faculty of Business and Econom­ics, PO Box 197 Caulfield East, Melbourne, Victoria, Australia.

Dr Ben Bella Jaoko, Warsaw University of Technology, Institute for Organization of Production Systems, Faculty of Production Engineering, Quality Systems Group, Warsaw, Poland.

Dr Schailendra Jha, School of Business and Economics, Wilfred Laurier University, 75 University Avenue West, Waterloo, Ontario, Canada.

Dr Jaak Jurison, Associate Professor and Deputy Chair, Information and Communications Systems, Graduate School of Business Administration, Fordham University, New York, New York, USA.

Dr Surendra K. Kaushik, Department of Finance and Economics, Lubin School of Business, Pace University, One Pace Plaza, New York, NY 10038, USA.

Dr Ron S. Kenett, Senior Partner, Kenett-Preminger Associates, KPA Ltd Management Consulting, Representing the Juran Institute in Israel, Herzlia Pituah, Israel

Professor Edward Kindlarski, Warsaw University of Technology, Insti­tute for Organization of Production Systems, Faculty of Production Engineering, Quality Systems Group, Warsaw, Poland

Dr Dennis E. Kroll, IMET Department, Bradley University, Illinois, USA

Dr Chu-Hua Kuei, Professor of Management and Management Science, Lubin School of Business, Pace University, New York, USA

Dr Paul Levy, Centre for Research in Innovation Management, Brighton Business School, University of Brighton, Falmer, Brighton, UK

Dr Jeffrey K. Liker, Associate Professor, Industrial and Operations Engi­neering, University of Michigan, Ann Arbor, Michigan, USA

Dr M.D. Moreno-Luzon, Professor of Economics and Business Studies, University of Valencia, Edificio Oriental Departamental, Valencia, Spain.

Dr Christian N. Madu, Research Scholar, Professor and Program Chair, Management Science Program, Lubin School of Business, Pace Uni­versity, New York, USA.

Contributors Xlll

Mr Marc E. Maisel, Senior Consultant, KPA Ltd Management Consult­ing, Representing the Juran Institute in Israel, Herzlia Pituah, Israel.

Dr John L. Michela, School of Business and Economics, Wilfred Laurier University, 75 University Avenue West, Waterloo, Ontario, Canada.

Dr Linda Fung-Vee Ng, Professor, Department of Decision Sciences and Managerial Economics, The Chinese University of Hong Kong, Shatin, Nt, Hong Kong.

Dr Hamid Noori, Professor of Technology and Operations Management, School of Business and Economics, Wilfred Laurier University, Waterloo, Ontario, Canada.

Dr Kenneth A. Paetsch, Assistant Professor, Department of Operations Management, College of Business Administration, Cleveland State Uni­versity, Cleveland, Ohio, USA.

Dr F. J. Peris, Professor of Economics and Business Studies, University of Valencia, Edificio Oriental Departamental, Valencia, Spain.

Dr Danny Samson, Leslie Froggatt Professor of Manufacturing Manage­ment and Director, Centre for Manufacturing Management, Melbourne Business School Ltd, The University of Melbourne, Carlton, Victoria, Australia.

Dr F. J. Santonja, Professor of Economics and Business Studies, Uni­versity of Valencia, Edificio Oriental Departamental, Valencia, Spain.

Dipl.-Wirtsch.-Ing A. Schmidt, Assistant Lecturer, Industrial Manage­ment and Human Factors, University of Kaiserlautern, Kaiserlautern, Germany.

Dr Shane J. Schvaneveldt, Department of Business Administration, Weber State University, Ogden, Utah, USA.

Dr Amrik Sohal, Monash University, Faculty of Business and Econom­ics, PO Box 197 Caulfield East, Melbourne, Victoria, Australia.

Dr Bin Srindidhi, Associate Professor, Accounting and Information Systems Area, Faculty of Management, Rutgers University, University Heights, Newark, New Jersey, USA.

Dr Eric W.K. Tsang, Lecturer, School of Accountancy and Business, Nanyang Technological University, Singapore.

Dr Chyau Tuan, Professor, Department of Decision Sciences and Mana­gerial Economics, The Chinese University of Hong Kong, Shatin, Nt, Hong Kong.

Dr Ton van der Wiele, Professor of Economics, Strategic Quality Man­agement Institute, Erasmus Universiteit Rotterdam, Rotterdam, The Netherlands.

xiv Contributors

Mr Tom Van Fossen, Leelanau Industries, 6052 E. Traverse Highway, Traverse City, Michigan, USA.

Dr Mark A. Vonderembse, Professor of Operations Management and Director Manufacturing Management MS and PhD Program, The Uni­versity of Toledo, College of Business Administration, Toledo, Ohio, USA.

Dr S. Nazli Wasti, Assistant Professor, Department of Management, Middle East Technical University, Turkey.

Dr Klaus J. Zink, Professor, Chair for Industrial Management and Human Factors, University of Kaiserlautern, Kaiserlautern, Germany.

Foreword

Any handbook on a major topic will have inclusions and omissions. This book contains vast comprehensive inclusions of virtually all explorations on quality management. Handled by 47 authors based in 13 different countries with extensive experience on world class quality management, this book is invaluable as a reference guide, class usage and professional help.

Quality issues have gained great importance as the business world became global and firms across the many countries sought to compete in both price and quality. Thus, product cost and quality of product or service became the predominant determinant of market share and profit. A long-term view towards attaining market share through reputation as opposed to short-term profit making has become the rule of modern business success. Certifications such as the ISO 9000 series and awards such as Baldrige are sought by companies as proof of the quality of their products to gain entry into the world market-place. At the same time, it is recognized that world class quality requires a commitment that far exceeds what is needed to get these certificates. Thus, this Handbook, quite appropriately, discusses not only the requirement for attaining these certificates and the rules for the awards but goes on to provide help to compete in the global market with world class quality.

Quality can be improved through continuous (Kaizen) improvements and/ or reengineering efforts including process and design innovations. Chapters are included that describe these approaches including practical tools for redesign, self-assessment, human resource training and bench­marking. Contributions include process performance appraisal, service quality management and concurrent engineering. Quality concerns with respect to productivity, information systems and advanced manufactur­ing technology are addressed. How quality can improve through proper learning curve analysis is explained in one article.

Quality consciousness should permeate the entire value chain. Towards this end, there are chapters on effecting quality awareness through supply chains.

A good handbook should deal with details of quality practices in various countries of the world. This is done thoroughly here in several chapters focusing on several countries of Europe and Asia. Countries detailed include Denmark, Poland, Australia, New Zealand, Singapore, China and India. This provides a good comparative perspective on practices.

xvi Foreword

Quality studies are not useful if they are not tied to strategies for improvement. Several chapters consider important strategies for quality improvement and initiation and performance evaluation through audit­ing. There is a separate chapter on quality deployment function which is an important strategic tool.

Implementation of quality analyses and strategy can be effective only when the 'how to' of quality is learned. The editor has included ample coverage on the statistical aspects of the tools. Statistical quality control, design of experiments, Taguchi loss functions, reliability and maintaina­bility are key topics that are covered in good detail and clarity. To aid the unprepared reader, there is a good chapter on introduction to probability and statistics.

The editor, Professor Christian N. Madu is a well-recognized authority on quality with numerous academic and professional publications. As the Editor-in-Chief of the premier quality journal International Journal of Quality Science, he occupies an enviable position that has enabled him to persuasively summon so many experts to write for this Handbook. These chapters are specifically written for this book and are not just reprints of previously published manuscripts. Thus, there is a cohesiveness to the treatment of the subject. This Handbook will be very valuable to both the professionals who wish to consult an authoritative book on quality and the academics and students who wish to keep up with the current evolution on the study of quality management.

Kashi R. Balachandran Professor of Accounting and Operations Management

Stem School of Business New York University

New York, NY

Preface

The Handbook of Total Quality Management is written as an introduction to total quality management with the intention of providing carefully selected and high quality chapters by reputable authors in the field. With the growing emphasis on total quality management and the proliferation of articles in this area, it is important to carefully organize this body of knowledge in a substantial form. Authors have emphasized both theory and practice and have drawn from several important quality applica­tions. To broaden the reader's view of quality, authors were selected from almost all continents covering more than 12 countries and national­ities. These authors present total quality management approaches from different views. We have also included country-specific approaches to quality to illustrate the cultural dependence of quality and to demon­strate that quality can be adapted in any situation.

A mix of articles from both industry and academic experts are offered and we tried as much as possible to cover every pertinent topic in total quality management. The Handbook therefore, promises to be an impor­tant reference manual which can be used as quick reference in industrial application and as a text in teaching courses or conducting seminars on total quality management.

Each chapter is written with the reader in mind. The aim is to commu­nicate and convey the thoughts of the author. Thus, the articles are readable. It is inevitable that a discussion of quality management will contain statistics. Though statistics may be hard for some readers, we have added a chapter on the "Introduction of Probability and Statistics". This chapter hopefully, will help prepare the reader for the more advanced topics on statistics.

The reader will find that this Handbook is very comprehensive and contains major topics that are related to total quality management. The composition of the Handbook includes all related topics in Total Quality Management (TQM), emerging technological issues such as Internet applications, re-engineering and concurrent engineering, statistical issues in quality, quality standards and awards, quality management practice in different countries and service quality. The exposition to these topics will help the reader to venture into more details and advanced topics. The reader is bound to find this Handbook to be the most comprehensive handbook of TQM available in the market.

The Handbook could not have been possible without the devotion and

XVlll Preface

commitment of the authors. Each one of them has worked relentlessly to produce an excellent piece. I am greatly indebted to them. Of course, no one deserves more acknowledgment than my Assistant Editor - Ms Koula Kilaras whose job was to contact the authors and follow-up with all the communications and deadlines. Without her assistance this project would have been impossible. It is Chapman & Hall's decision to publish this work that made the project possible. I greatly appreciate the support that Mark Hammond - Senior Editor - has given to this project and the frequent communication I received for more than a year through e-mail services from his editorial assistants Joanne Jones, Deborah Millar and Alison Provan. All these people have helped to keep up the pressure and now here is the book. I thank my good friend Chu-Hua Kuei for his support through this project and his dedication to make sure that this project was completed on time. I also thank K.R. Balachandran of New York University for writing the Foreword to the Handbook. All the above­mentioned have contributed in making this an excellent book that our readers will be proud of.

Christian N. Madu Pace University

New York

Biographical sketch

Christian N. Madu is research scholar, professor and chair of the management science program at the Lubin School of Business, Pace University. He is the author/co-author of more than 75 research papers in several areas of operations research and management science that have appeared in journals such as Decision Sciences, lIE Transactions, Journal of Operational Research Society, Applied Mathematics Letters, Mathe­matical and Computer Modeling, Long Range Planning, European Journal of Operational Research, OMEGA, Technological Forecasting and Social Change, Socio-economic Planning Sciences, Futures, Quality Management Journal and several others. He is the author/co-author of seven other books includ­ing Strategic Total Quality Management (co-author Chu-Hua Kuei), Manag­ing Green Technologies for Global Competitiveness and edited Management of New Technologies for Global Competitiveness. Dr Madu is also the editor­in-chief of the International Journal of Quality Science and is the President of the Center for Quality and Technology Management - a consulting group that also conducts seminars and in-house training sessions for corporations around the world. He has served as a consultant to several organizations. Dr Madu can be reached through his e-mail address at ChrisMadu@aol.com.

Notable quality scholars

In this section, we briefly introduce quality scholars whose works have had significant impact on the practice of quality.

W. Edwards Deming - considered by many as the father of TQM movement, a notable author and lecturer of statistical quality. Dr Deming is credited for having helped Japanese manufacturers improve their quality after the Second World War. The coveted Japanese quality award - the Deming Prize - is named in his honor. Some of his contributions include the System of Profound Knowledge which consists of four major and interrelated parts: appreciation of a system, knowledge about varia­tion, psychology of individuals, society and change; Deming's 14 points, an outline of management principles that will help to achieve quality improvement; Deming chain reaction, an exposition of the relationship between productivity and quality and job creation; PDCA (plan­do-cheek-act) cycle though not developed by Deming, he popularized its use in planning for quality; and Red Bead Experiment used extensively in his lectures to illustrate why workers should not be ranked to identify the good and bad performers since often times, the problem may be with the system and not the worker.

Dr Deming was born in Sioux, Iowa, on October 14, 1900, and grew up in Cody, Wyoming. He earned a bachelors degree in physics from the University of Wyoming and a PhD in mathematical physics from Yale University in 1928. He worked for the United States Department of Agriculture where he developed a keen interest in statistical control through his encounter with Dr Walter Shewhart in the mid-1920s while working with Western Electric Co. He also worked for the US Bureau of the Census and the US weapons industry. He later worked as a con­sultant and a Distinguished Professor in Management at Columbia University. In 1960, he was the recipient of the Order of Sacred Treasure, 2nd Class, from the Emperor of Japan. He died in 1993 at the age of 93.

Joseph M. Juran - Juran and Deming are the pre-eminent champions of quality and they considerably share in both contribution to the current quality movement and status. Juran's contributions focus on the four areas: definitions of quality and the cost of quality, quality habit, quality trilogy and Universal breakthrough sequence. He defines quality as "fitness for use." This is one of the most popular definitions of quality since it encompasses quality of design, quality of conformance and engineering issues such as availability, safety and field use. He also

xxii Notable quality scholars

introduced the cost of quality in the 1951 edition of his Quality Control Handbook. He identifies four types of cost of quality namely, internal failure costs, external failure costs, appraisal costs and prevention costs. By exposing management to the cost of quality, they hopefully will pay attention to quality improvement efforts.

With 'quality habits', he insists on the need for a firm to have a focused approach to continuously improve quality and this should develop into a habit of quality that will seek realistic goals and objectives. The guide­lines that achieve quality improvement should be clear and management must take action to successfully build the quality habit.

The quality trilogy involves three inseparable parts that constitute actions the firm must take to continuously improve quality. These are quality planning, quality control and quality improvement.

Juran also offers the Universal breakthrough sequence which logically is similar to reengineering. This consists of a set of actions management must take to make a major leap in quality. This involves general actions that are applicable to any organization problem. According to Juran, breakthroughs follow a universal sequence and that sequence involves the following: proof of need, project identification, organizing for improvement, diagnostic journey, remedial action, resistance to change and holding onto gains.

Juran like Deming was exposed to statistical quality control by Dr Walter Shewhart at about the same time. He was born on 24 December, 1904 in Braila, Romania and grew up in Minneapolis, Minnesota. He received a bachelor of science in electrical engineering from the Uni­versity of Minnesota in 1924 and a JD from Loyola in 1935. In 1981, he was recipient of the Order of Sacred Treasure, 2nd Class, from the Emperor of Japan. He currently serves as the Chairman emeritus, Juran Institute Inc., in Wilton, Connecticut.

Harold F. Dodge - is known for his contributions to statistical quality control. In collaboration with Harry. G. Romig, he developed acceptance sampling plans that are widely used for product inspections. These acceptance sampling plans are widely known as Dodge-Romig sampling plans. In 1940, they published acceptance sampling tables for four differ­ent types of sampling namely: single-sampling lot tolerance tables, double-sampling lot tolerance tables, simple-sampling average outgoing quality limit tables and double-sampling average outgoing quality limit tables. He was also instrumental in developing important acceptance sampling concepts such as consumer's risk, producer's risk, operating characteristic curve and average outgoing quality level.

Harry G. Romig - in addition to the work he did with Harold F. Dodge regarding acceptance sampling procedures (see Harold F. Dodge), he developed the first sampling plans using variable data. He also developed the concept of average outgoing quality limit.

Philip B. Crosby - Crosby is an advocate of zero defects. According to

Notable quality scholars xxiii

him, quality is free in the long run. He also introduced the Management Maturity Grid to assess management and its current position on quality. This Grid can help redirect future organizational emphasis on quality. He offered 14 steps for quality improvement that can be used to im­plement the Management Maturity Grid. His contention that zero defect can be achieved and that quality is free have generated a lot of debate.

Kaoru Ishikawa - a well respected Japanese professor of management. He introduced the cause-effect diagram also known as the fishbone or Ishikawa diagram. This diagram classifies problems in four places: methods, manpower, material and machines or what is known as the 4Ms. Potential quality problems can be identified and analysed. Ishikawa also introduced quality circles. Quality circles are gradually being replaced by teams primarily because teams are empowered while quality circles are not.

Shiego Shingo - Shiego Shingo is a co-developer of the inventory management technique known as just-in-time system. Mr Shingo from Japan is known in Japan as Mr Improvement. He introduced what is now known as Fail-Safe design or the Shingo System. This method is based on using source inspection and the poka-yoke system to achieve zero defects. Shingo argues that statistical quality control methods provide after the fact information and do not prevent defects. He argues that checks must be introduced along the process to prevent defects. This involves three steps: successive check inspection, self-check and source inspection.

Yoji Akao - a well respected professor from Japan, Professor Akao introduced the quality function deployment (QFD). In the West, QFD is popularly known as the 'House of Quality'. QFD offers an important way for corporations to understand the needs and wants of their cus­tomers. It also offers the opportunity for benchmarking with world class leaders.

Masaaki Imai - brought to light in the West, the practice of continuous improvement in Japan or what is often referred to as the principles of Kaizen in Japan. Japanese industrial successes are often attributed to Kaizen which calls for small incremental improvements in a process. Continuous improvement is often times synonymous to total quality management.

Genichi Taguchi - a Japanese statistical consultant, revolutionalized the applications of statistics to quality and redefined quality. In his views, products should be robust enough to withstand variations that may result from environmental and production factors. His methods are based on the efficient use of experimental designs. Although his experi­mental design procedures are similar to standard design methods, he, however, offered tables and graphs (linear graphs) that made it easier for practitioners to use. His other major contribution is in his definition of

xxiv Notable quality scholars

quality using a quality loss function (QLF). He defines QLF as a loss to society for producing inferior products. QLF measures the cost of quality by looking at variations from the target value or specification.

George P. Box - is a well respected professor of statistics in the United States. He is well known for his contributions on statistical design of experiments.

Walter A. Shewhart - is regarded by many as the father of statistical quality control. He is credited with having introduced both W. Edwards Deming and Joseph M. Juran to statistical quality control. He developed the statistical control charts and defined two types of causes of variation: natural and special causes of variation. Also, he introduced the plan­do-study-act (PDSA) cycle which is often referred to as the Shewhart cycle. Dr Deming renamed the PDSA cycle the PDCA cycle with C referring to check replacing the S for study.

Armand V. Feigenbaum - is one of the leading advocates of total quality control. In fact, the term 'total quality control' as popularly used in Japan and known as 'total quality management' in the US and most of Europe, was the title of his 1951 book. He originated this concept and has contributed significantly to the TQM movement through his writing and consulting work. He is the founder and president of General Systems Co.

Michael Hammer - is known for his pioneering work on re­engineering. According to Hammer and Champy in their 1993 book, re-engineering is defined as 'the fundamental re-thinking and radical design of business processes to achieve dramatic improvement in critical, contemporary measures of performance, such as cost, quality, service and speed'. This contrasts with continuous improvement which seeks for gradual and incremental improvements over time.

Glossary

Acceptable quality level (AQL) Minimum number of defectives that will be contained in a lot before the lot is accepted as a good lot.

Acceptance criterion Established criterion that shows the maximum allow­able defects in a sample for the lot to be accepted as meeting the quality standard.

Acceptance sampling A sampling procedure applied on existing goods to decide whether to accept or reject the entire lot based on the quality observed from the random sample.

Acceptance sampling plan A plan that specifies the criteria to determine if a lot should be accepted or rejected based on the number of defects found in the sample. This plan specifies the sample size and the maximum allowable defects to be found in a sample.

Accreditation The use of accreditation has become popular especially since the introduction of ISO 9000 series standards. It is used to imply certification of the quality improvement programs or processes of an organization by a duly recognized agency.

Analysis of variance A statistical procedure commonly used to analyse experimental data to estimate variance associated with specific sources of variation.

Attribute measurement Information obtained for quality purposes may be presented in qualitative or categorical forms. For example, a sample may be examined to determine if there is defect or no defect, information may be classified as yes/no, go/no-go, good/bad, and others. These discrete classifications are known as attribute measurement and the control charts used for attribute charts include percent chart (p-chart), count chart (c-chart) and others.

Availability The proportion of time the product or process is able to perform its functions as expected.

Average outgoing quality The quality of the lot after defective items found through inspection have been replaced.

Average outgoing quality limit (AOQL) The highest average percent defec­tive in a sampling plan.

XXVI Glossary

Benchmarking A firm compares its practice to that of world class leaders with the intention of learning from the best performer and improving its own process.

Big Q, Little q This term is used by Joseph M. Juran to illustrate the differences of organization-wide quality management efforts (Big Q) and limited application of quality management such as focus on only product or process (Little q).

Capability index This index shows how well the items that are being produced fit into the design limits.

Check sheet One of the seven tools of quality, it is comprised of a simple data-recording device that is custom-designed by the user to enable easier interpretation of results.

Common causes These are variations in a process that can be explained only by chance occurrence. They are also referred to as normal or natural variations.

Conformance Used to imply that product or services are performing within the design specification.

Consumer's risk The risk incurred when a poor quality lot is accepted. This is also known as the Type II error.

Continuous improvement (Cl) A management philosophy that views quality improvement as a never-ending process that will always lead to incremental improvements.

Continuous improvement process This is a never-ending process through which processes are continuously improved. Many of the improvements may be incremental and not as drastic as in re-engineering. This process in Japan is often referred to as Kaizen.

Control chart A graphical display of process output variable to determine if the process is stable or out of control.

Cost of quality A classification of the cost of quality into four groups: prevention, appraisal, internal and external failure costs. These costs are used to demonstrate the importance of prevention and cost savings that can be achieved through quality practice.

Customer satisfaction A gauge on how well customer requirements are designed into a product or service.

Customer-supplier partnership A partnership between the buyer and the supplier that leads to long time commitment and co-operation in estab­lishing and improving the quality of products supplied to the buyer by the supplier.

Glossary XXVll

Deming Prize Given in Japan in recognition of business excellence through quality. It represents to the Japanese what Malcolm Baldrige represents to Americans.

Deming's chain reaction A relationship map by Deming to illustrate the association between quality and productivity and how that will lead to job creation. Simply put, quality improvement leads to cost reduction which leads to productivity improvement. As a result, markets are captured, the organization stays in business and is able to provide jobs and more jobs.

Deming's 14 points A list of management philosophies provided by W. Edwards Deming as preconditions to achieving total quality management.

Dependability Proportion of time a product is available and capable of performing its function.

Design of experiment A statistical procedure for planning and controlling experiments and analysing and interpreting the outcomes of the experiment.

Employee involvement Participation of employees in decisions on how to improve their work processes.

Empowerment Employees are granted authority to take action as they see fit to improve their work processes without approval from their superiors.

External customer The end user or consumer of a product or service who is not affiliated to the supplier.

Fail-safe design See The Shingo System.

14 points Generally refers to Deming's 14 points that outline his manage­ment philosophies on how to improve or achieve quality in an organiza­tion. Crosby also has his own 14 points.

Histogram A graphical display of the distribution of data to study any underlying patterns that may exist. It is also one of the seven basic quality control tools.

Hoshin planning The strategic planning process used in Japan. This involves development of vision statement that takes a long term view of the goals and plans of the organization. It is periodically reviewed to ensure that it is still aligned with the goals of the organization.

House of quality A house-shaped matrix that is used to make quality function deployment operational. It contains information on customer attributes and how they can be achieved through engineering specifications.

XXV111 Glossary

Inspection Examination of a product or service to determine if it conforms with pre-specified quality guidelines.

Instant pudding A term used to refer to the thinking that quality and productivity improvement can be quickly achieved through affirmation of faith rather than focusing on long-term quality improvement efforts such as training and education.

Internal customer The end user or consumer of a product or service who is affiliated to the supplier.

Ishikawa diagram Also known as fishbone diagram or cause-and-effect diagram. The aim of this diagram is to identify the main causes and sub­causes of a problem. These causes are attributed normally to four factors known as the 4Ms - Man, Machine, Material and Method. These causes lead to the symptom or problem or effect.

ISO 9000 A series of quality standards ranging from design and develop­ment through procurement, production, installation and servicing that were adopted by the International Organization for Standardization (ISO) in 1987.

ISO 9000 certification Certification issued to firms that have followed the ISO guidelines.

ISO 14000 series Like ISO 9000 series, it is a series of five standards that are concerned with establishing guidelines and auditing of environ­mental management systems. The focus is on environmental issues.

Leadership Quality improvement is achieved when top management or corporate leaders participate, commit time, resources and effort and develop clear visions and goals and most importantly, know how to manage people and change.

Lot Quantity of items generated from the production process through which a random sample is taken for quality evaluation.

Lot sentencing This is the decision rule set up to decide whether to accept or reject a lot.

Lot tolerance percent defective (LTPD) When the percentage of defectives in a lot is greater than a specified amount, the lot is defined to be bad and is termed lot tolerance percent defective.

Lower and upper specification limits Lower and upper boundaries that are used to define the limits of variations for a product characteristic.

Maintainability Addresses the ease of servicing a product and the ease of restoring it to its operation state prior to failure.

Malcolm Baldrige National Quality Award The highest quality award given in the United States by the US government in recognition of quality as a

Glossary xxix

major part of successful business strategy. This award is administered by the United States Department of Commerce.

Mean time between failure The average time interval or space between failures for a repairable product.

MIL-Q-9858A A military standard that is used to describe the require­ments for a quality program.

MIL-STO-105E A military standard that is used to describe the sampling procedures and tables when inspection is done by attributes.

MIL-STO-45662A A military standard that is used to describe the require­ments for creating and maintaining a calibration system.

Multiple sampling plan Unlike a single sampling plan, multiple samples are taken to determine whether to accept the lot, reject the lot, or to continue sampling based on the number of defects found in the sample.

100% inspection A procedure whereby all items produced are inspected.

Operating characteristic (OC) curve A curve that displays different sam­pling plans.

Organizational culture Widely held beliefs, value system and behaviors in an organization. Organizational culture is formed over a long period of time and influences the adaptability of new technologies. To benefit from such new technologies such as quality, it may be necessary to develop a conducive culture and environment.

Out of spec Used to denote that a product does not satisfy a given quality specification.

Pareto analysis was introduced by Vilfredo Pareto an Italian economist. The aim of this analysis is to prioritize problems for solutions and it is based on the concept of 'the vital few versus the trivial many'. Joseph M. Juran popularized its use in studying quality problems and adopted the 80-20 rule which simply states that 80% of the problems observed in a process can be accounted for by 20% of the causes of these problems. This focuses attention in solving the critical few problems. However, it does not help to identify these problems.

P chart A control chart that is used to assess the conformance of process output to specifications when the output of the process is measured in terms of proportion or percentage of defects.

POCA A planning tool frequently associated with Deming. This tool illustrates four steps that form a loop on how to continuously improve quality. The PDCA means plan-do-check-act cycle.

Poka-yoke This is based on making the workplace mistake-proof.

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Process capability A statistical measure of process variability for a given attribute.

Producer's risk The risk incurred when a good lot is rejected. It is also known as the Type I error.

Quality audit An independent examination of the quality program to determine if quality initiatives comply with planned quality programs.

Quality circles Group of workers that meet periodically to identify ways to improve their products and processes.

Quality engineering A focus on maximizing the quality of processes and products.

Quality function deployment An approach to understand customers' needs known as the voice of the customer and integrate them into the design specifications of products.

Quality Loss Function (QLF) Developed by Genichi Taguchi relates the cost of quality to variation in a process from the target.

Quality science A rigorous examination of the fundamentals and theories of quality.

Quality trilogy Joseph M. Juran views quality management from a trilogy that consists of quality planning, quality control and quality improvement.

Random sampling A sampling procedure that guarantees equal chance to all observations in the population.

R chart A control chart that is used to measure the precision in the output of a process variable.

Rectification When a lot is rejected, it is effectively screened and all non­conforming items are replaced by conforming items. This process is known as rectification.

Red bead experiment An experiment used widely by Deming to illustrate the theory of variation by showing that workers' performance may be attributed to natural variations inherent in the system.

Re-engineering Involves a fundamental rethinking and radical redesign of a business process. It requires complete overhaul of the entire process and management systems.

Reliability The proportion of time a product performs its intended func­tion under normal conditions without failure.

Right the first time A TQM concept to illustrate that doing things right the first time saves money to the organization in the long run. Its focus is on prevention rather than detection of defect.

Glossary xxxi

Robust design This was introduced by Genichi Taguchi. With robust design, the product is designed to perform over a wider range of conditions because according to Taguchi it is easier to design products that will be insensitive to environmental factors than trying to control such factors.

Scatter diagram Also known as cross plot it is a graphical display of two variables normally dependent and independent variables to study their association. It is also one of the seven basic quality control tools.

Seven tools of quality These are tools that organizations could use to better understand and manage their processes to improve quality. It is com­prised of cause-and-effect diagram, check sheet, control chart, flow chart, histogram, Pareto chart and scatter diagram.

Shewhart cycle The same as the PDCA or PDSA cycle. This was developed by Walter Shewhart but its application was made popular by W. Edwards Deming.

Shingo System Introduced by Shiego Shingo known as Mr Improvement in Japan, focuses on achieving zero defects through the use of source inspection and poka-yoke. Shingo's approach is to introduce quality control checks within the process rather than at the end of the process as done in SQc.

Signal-to-noise ratio Also known as SIN ratio is a performance statistic developed by Genichi Taguchi. It is an attribute-type performance statis­tic that can be used to reduce product or process variation by carefully selecting parameter settings in a experiment. There are basically three types of SIN ratios: the smaller the better, the larger the better and the nominal ratio.

Single sampling plan A procedure where a single sample of size n is taken from a lot and inspected to determine if the number of defectives is less than or equal to a critical number c. If so, the lot is accepted otherwise it is rejected. The term c is known as the acceptance number and it is the maximum number of defects that can be present in the sample before the lot is rejected.

Six-sigma quality Made popular by Motorola Corporation is derived from the normal probability distribution and implies that only 3.4 defects are expected per million parts.

Special causes These are variations in the process that are correctable and may be attributed to factors inherent in the process. They are often referred to as assignable causes.

Stable process A process that is in control or meeting specified guidelines is said to be a stable process.

xxxii Glossary

Statistical process control Involves testing of random samples of outputs from a process to determine if the process is stable or producing items that conform to specifications.

Statistical quality control (SQC) Statistical analysis of quality that involves acceptance sampling and statistical process control.

Taguchi methods Developed by Genichi Taguchi, refers to statistical methods used to optimize the combination of product and process variables to achieve robust design.

Teams Work teams that are formed as in quality circles, to identify ways to improve products and processes. However, unlike quality circles, teams are empowered.

Total quality control A concept originated by Armand V. Feigenbaum and used as a title of his 1951 book Total Quality Control. This concept is based on a company-wide application of quality. Also see total quality management.

Total quality environmental management The application of total quality management concepts to environmental problems.

Total quality management A company-wide application of quality that requires the involvement and participation of everyone in the organiza­tion and a strong support and commitment from top management.

Type I error Also known as the producer's risk can be seen in the quality context as the error committed when a good lot is rejected and classified as defective.

Type II error Also known as the consumer's risk is the error committed when a bad lot is accepted as meeting the quality guidelines or specifications.

Variable measurement This form of measurement is commonly used for items that are measured in a continuous scale. For example, weight of cereal, room temperature, drug content in milligrams. The control charts used here are the x-bar and R-charts.

X chart A control chart that is used to measure the accuracy in the output of a process variable.

Zero defects Introduced by Philip B. Crosby to illustrate the importance of continuous improvement efforts to reduce defects and the cost of poor quality.