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Statistical Engineering: An algorithm for Reducing Variation in Manufacturing Processes

Written By Steiner, Stefan and Mackay, Jock
2005, Edition 1
Category: Six Sigma
Level: Intermediate

Quality Press
600 N. Plankinton Ave.
Milwaukee, 53203
United States of America
URL: http://qualitypress.asq.org/

About This Book

Author's note: Statistical Engineering (SE) is an algorithm and a collection of data-based strategies and tools designed to improve the performance of high to medium volume manufacturing processes. The key step of the algorithm is the appropriate selection and efficient application of one of seven variation reduction approaches: ·fix the obvious using knowledge of a dominant cause of variation ·desensitize the process to variation in a dominant cause ·feedforward control based on a dominant cause ·feedback control ·make the process robust ·100% automated inspection ·move the process center closer to target In most applications of SE we recommend searching for a dominant cause of variation. SE promotes an efficient search for this cause using the method of elimination and special statistical tools. SE is widely used in the automotive sector by both OEMs and their suppliers. Because of its algorithmic structure and specialized purpose, it is easy to fit SE into Six Sigma and other Continuous Improvement systems. This book will change how you think about process improvement.

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