 
    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.
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This text is concerned with statistical methods such as statistical process control; design of experiments, reliability and life testing and robust design methods which are relevant in quality improvement efforts in research and development and in industrial practice. It brings together statistical technology, methods and applications which emerged at an international conference in Cochin, India. It also discusses statistical education, innovation and quality systems, along with process improvement case studies. The text is applications-oriented and should be of relevance to applied statisticians and researchers, quaility engineers and other industial practitioners who may need an understanding of new methodologies.
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