Quality Improvement Through Statistical Methods

1. Front Matter

   Pages i-xxxiii

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2. Statistics and Quality

   1. Front Matter

      Pages 1-1

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   2. Scientific Learning

      • George E. P. Box

      Pages 3-12

   3. Industrial Statistics and Innovation

      • R. L. Sandland

      Pages 13-21

   4. Understanding QS-9000 With Its Preventive and Statistical Focus

      • Bovas Abraham, G. Dennis Beecroft

      Pages 23-33

   5. A Conceptual Framework for Variation Reduction

      • Shams-ur Rahman

      Pages 35-44

   6. The Role of Academic Statisticians in Quality Improvement Strategies of Small and Medium Sized Companies

      • John F. Brewster, Smiley W. Cheng, Brian D. Macpherson, Fred A. Spiring

      Pages 45-58

3. Statistical Process Control

   1. Front Matter

      Pages 59-59

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   2. Developing Optimal Regulation and Monitoring Strategies to Control a Continuous Petrochemical Process

      • A. J. Ferrer, C. Capilla, R. Romero, J. Martin

      Pages 61-77

   3. Capability Indices When Tolerances Are Asymmetric

      • Kerstin Vännman

      Pages 79-95

   4. Robustness of On-line Control Procedures

      • M. S. Srivastava

      Pages 97-108

   5. An Application of Filtering to Statistical Process Control

      • A. Thavaneswaran, B. D. Macpherson, B. Abraham

      Pages 109-120

   6. Statistical Process Control and Its Applications in Korean Industries

      • Sung H. Park, Jae J. Kim

      Pages 121-133

   7. Multivariate Statistical Process Control of a Mineral Processing Industry

      • Nihal Yatawara, Jeff Harrison

      Pages 135-149

   8. Developing Objective Strategies for Monitoring Multi Input/Single Output Chemical Process

      • B. K. Pal, V. Roshan Joseph

      Pages 151-162

   9. Properties of the Cpm Index for Seemingly Unstable Production Processes

      • Olle Carlsson

      Pages 163-172

   10. Process Capability Indices for Contaminated Bivariate Normal Populations

       • Subrahmaniam Kocherlakota, Kathleen Kocherlakota

       Pages 173-186

   11. Quality Improvements by Likelihood Ratio Methods for Surveillance

       • Marianne Frisén, Peter Wessman

       Pages 187-193

   12. Properties of the Taguchi Capability Index for Markov Dependent Quality Characteristics

       • Erik Wallgren

       Pages 195-203

4. Design and Analysis of Experiments

   1. Front Matter

      Pages 205-205

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This book is based on the papers presented at the International Conference 'Quality Improvement through Statistical Methods' in Cochin, India during December 28-31, 1996. The Conference was hosted by the Cochin University of Science and Technology, Cochin, India; and sponsored by the Institute for Improvement in Quality and Productivity (IIQP) at the University of Waterloo, Canada, the Statistics in Industry Committee of the International Statistical Institute (lSI) and by the Indian Statistical Institute. There has been an increased interest in Quality Improvement (QI) activities in many organizations during the last several years since the airing of the NBC television program, "If Japan can ... why can't we?" Implementation of QI meth­ ods requires statistical thinking and the utilization of statistical tools, thus there has been a renewed interest in statistical methods applicable to industry and technology. This revitalized enthusiasm has created worldwide discussions on Industrial Statistics Research and QI ideas at several international conferences in recent years. The purpose of this conference was to provide a forum for presenting and ex­ changing ideas in Statistical Methods and for enhancing the transference of such technologies to quality improvement efforts in various sectors. It also provided an opportunity for interaction between industrial practitioners and academia. It was intended that the exchange of experiences and ideas would foster new international collaborations in research and other technology transfers.

• Applied Statistics
• Quality Control Engineering
• approximation
• control engineering
• function
• optimization
• statistics

• Institute for Improvement in Quality and Productivity, University of Waterloo, Waterloo, Canada

  Bovas Abraham

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