Design of Experiments Using The Taguchi Approach
16 Steps to Product and Process Improvement
1. Auflage April 2001
560 Seiten, Hardcover
Wiley & Sons Ltd
Fulfill the practical potential of DOE-with a powerful, 16-step
approach for applying the Taguchi method
Over the past decade, Design of Experiments (DOE) has undergone
great advances through the work of the Japanese management guru
Genechi Taguchi. Yet, until now, books on the Taguchi method have
been steeped in theory and complicated statistical analysis. Now
this trailblazing work translates the Taguchi method into an
easy-to-implement 16-step system.
Based on Ranjit Roy's successful Taguchi training course, this
extensively illustrated book/CD-ROM package gives readers the
knowledge and skills necessary to understand and apply the Taguchi
method to engineering projects-from theory and applications to
hands-on analysis of the data. It is suitable for managers and
technicians without a college-level engineering or statistical
background, and its self-study pace-with exercises included in each
chapter-helps readers start using Taguchi DOE tools on the job
quickly. Special features include:
* An accompanying CD-ROM of Qualitek-4 software, which performs
calculations and features all example experiments described in the
book
* Problem-solving exercises relevant to actual engineering
situations, with solutions included at the end of the text
* Coverage of two-, three-, and four-level factors, analysis of
variance, robust designs, combination designs, and more
Engineers and technical personnel working in process and product
design-as well as other professionals interested in the Taguchi
method-will find this book/CD-ROM a tremendously important and
useful asset for making the most of DOE in their work.
Acknowledgments.
Symbols and Abbreviations.
Introduction.
Design of Experiments and the Taguchi Approach.
Definition and Measurement of Quality.
Common Experiments and Methods of Analysis.
Experimental Design Using Orthogonal Arrays.
Experimental Design with Two-Level Factors Only.
Experimental Design With Three- and Four-Level Factors.
Analysis of Variance.
Experimental Design for Studying Factors Interaction.
Experimental Design with Mixed-Level Factors.
Combination Designs.
Strategies for Robust Design.
Analysis Using Signal-to-Noise Ratios.
Results Comprising Multiple Criteria of Evaluations.
Quantification of Variation Reduction and Performance Improvement.
Effective Experiment Preparation and Planning.
Case Studies.
Appendix.
What's on the Disk.
Index.
List of Symbols.
