Statistical Process Control in Industry : Implementation and Assurance of Spc

During the past decade interest in quality management has greatly increased. One of the central elements of Total Quality Management is Statistical Process Control, more commonly known as SPC.
This book describes the pitfalls and traps which businesses encounter when implementing and assuring SPC. Illustrations are given from practical experience in various companies. The following subjects are discussed: implementation of SPC, activity plan for achieving statistically controlled processes, statistical tools, and lastly, consolidation and improvement of the results. Also, an extensive checklist is provided with which a business can determine to what extent it has succeeded in the actual application of SPC.
Audience: This volume is written for companies which are going to implement SPC, or which need a new impetus in order to get SPC properly off the ground. It will be of interest in particular to researchers whose work involves statistics and probability, production, operation and manufacturing management, industrial organisation and mathematical and quantitative methods. It will also appeal to specialists in engineering and management, for example in the electronic industry, discrete parts industry, process industry, automotive and aircraft industry and food industry.

` ...it is much more than the generic textbook covering average and range charts. The material is presented in a very clear and objective way. Overall, the authors provide an Z to Z guide for implementing SPC. They give a historical perspective, show the need for statistical thinking and SPC, provide the tools, give guidance on how to implement the tools, and then show the reader how to move from the control phase to the assurance phase. Although statistical presentation is above the basic level, the basics are presented in a clear and understandable way. I recommend this book to individuals who are looking for ideas on how to successfully implement a borad-based SPC program within their organizations.' Technometrics, 42:4 (2001)