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Reducing variation can simultaneously reduce overall cost, improve function and increase customer satisfaction with a product. This book helps you focus directly on the goal of achieving variation reduction. It is not a compendium of all the various analytical tools and methods you can use; presented here is an effective, low-cost strategy for finding a dominant cause of variation based on the method of elimination, a proven search method based on available observational data.
The authors discuss a detailed framework for planning and analyzing empirical investigations, known by its acronym QPDAC (Question, Plan, Data, Analysis, Conclusion), and they classify all effective ways to reduce variation into seven approaches. This variation reduction algorithm is not meant to replace global improvement systems such as Six Sigma; it is narrowly focused on process improvement of high-volume manufacturing processes. A unique aspect of the resulting algorithm forces early consideration of the feasibility of implementing each of the approaches.
Statistical Engineering will benefit those involved in process improvement, including process engineers with responsibility for reducing variation, Six Sigma Green Belts and Black Belts, trainers in process improvement methods, academics and students interested in quality and productivity improvement and teachers and students of courses in engineering statistics.
This special low-priced edition is for sale in India, Bangladesh, Bhutan, Myanmar (Burma), Sri Lanka, Nepal, Pakistan, Southeast Asia and the Middle East. ISBN - 9788122431094
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Pages : 362
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