☰

Business & Money

Management & Leadership

Quality Control & Management

Quality Control

Taguchi's Quality Engineering Handbook

R 9,684

or 4 x payments of R2,421.00 with Payflex

Payflex

Availability: Currently in Stock

Delivery: 10-20 working days

Taguchi's Quality Engineering Handbook
"This book is a great demonstration of this powerful approach andhow it can make a meaningful difference in any type of business. Ittakes a dedicated engineering approach to implement, but thepayback in customer satisfaction and growth is dramatic."
â€”Lou Giuliano, chairman, president, and CEO, ITT Industries
No other single volume presents the full breadth of foundingbeliefs behind the successful engineering practices used by today'sleading companies. Helpful to companies in both manufacturing andservice industries, Taguchi's Quality Engineering Handbookprovides accessible material on such topics as:
- Quality loss function
- On-line quality engineering
- Signal-to-noise ratio
- Robust engineering
- Design of experiments (known as the "Taguchi method")
- Mahalanobisâ€“Taguchi Systems (MTS)
- and more.
PrizeÂ or Award
- AAP Awards for Excellence in Professional and ScholarlyPublishing, 2006
Country USA
Brand Wiley
Manufacturer Wiley-Interscience
Binding Hardcover
ItemPartNumber 9780471413349
UnitCount 1
Format Illustrated
EANs 9780471413349
ReleaseDate 0000-00-00

You might also like...

Juran's Quality Handbook: The Complete Guide to Performance Excellence, Seventh Edition

Juran's Quality Handbook: The Complete Guide to Performance Excellence, Seventh Edition

Design of Experiments Using The Taguchi Approach: 16 Steps to Product and Process Improvement

Design of Experiments Using The Taguchi Approach: 16 Steps to Product and Process Improvement

Optimal Design of Experiments: A Case Study Approach

Optimal Design of Experiments: A Case Study Approach

Design for Manufacturability Handbook

Design for Manufacturability Handbook

EMP III (Evaluating the Measurement Process): Using Imperfect Data

EMP III (Evaluating the Measurement Process): Using Imperfect Data

Quality Engineering Using Robust Design

Quality Engineering Using Robust Design