The Mahalanobis-Taguchi Strategy

The Mahalanobis-Taguchi Strategy
Author: Genichi Taguchi
Publisher: John Wiley & Sons
Total Pages: 262
Release: 2002-05-23
Genre: Business & Economics
ISBN: 9780471023333

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This book, written by one of the founding fathers of statistical quality control, covers the latest measurement technology for multi- variable processes.


The Mahalanobis-Taguchi System
Language: en
Pages: 220
Authors: Genichi Taguchi
Categories: Business & Economics
Type: BOOK - Published: 2001 - Publisher: McGraw Hill Professional

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This resource shows how to harness the power of an amazing new pattern-recognition and forecasting method from Dr. Genichi Taguchi, a world-renowned quality gen
The Mahalanobis-Taguchi Strategy
Language: en
Pages: 262
Authors: Genichi Taguchi
Categories: Business & Economics
Type: BOOK - Published: 2002-05-23 - Publisher: John Wiley & Sons

GET EBOOK

This book, written by one of the founding fathers of statistical quality control, covers the latest measurement technology for multi- variable processes.
Mahalanobis-Taguchi System - Ise
Language: en
Pages: 190
Authors: Genʼichi Taguchi
Categories: Pattern recognition systems
Type: BOOK - Published: 2001 - Publisher:

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"MTS goes beyond theory - it shows you exactly how international business giants have successfully put the system to work for them. The book includes 15 case st
Quality Recognition & Prediction
Language: en
Pages: 256
Authors: Shoichi Teshima
Categories: Technology & Engineering
Type: BOOK - Published: 2012-06-15 - Publisher: Momentum Press

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The Mahalanobis-Taguchi data handling and pattern recognition system is widely established-- built and extended from the original quality control precepts of Ge
Multivariate Statistical Methods in Quality Management
Language: en
Pages: 318
Authors: Kai Yang
Categories: Technology & Engineering
Type: BOOK - Published: 2004-03-17 - Publisher: McGraw Hill Professional

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Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate sta