Six Sigma and Process Improvement
Quality Engineering Using Robust Design
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- explores an innovative method (based on the Taguchi Method) of design optimization for performance, quality, and cost — the Robust Design.
- shows how to do many things which involve: 1) making product performance insensitive to raw material variation, 2) developing designs that are robust against manufacturing variation, 3) using designs that are the least sensitive to changes in the operating environment, 4) taking advantage of a structured development process that allows engineering time to be used most productively, 5) using orthogonal arrays to study a large number of decision variables with a small numbers of experiments, and 6) investigating and putting to work a measure of quality called signal-to-noise (S/N) ratio to predict the quality of a product from the customer's perspective.
- focuses on the actual engineering problems rather than statistical theory.
- features a series of real case studies that relate the method to the fabrication of integrated circuits, circuit design, computer tuning, and mechanical routing.
- Copyright 1989
- Dimensions: 7 X 9 1/4
- Pages: 250
- Edition: 1st
- ISBN-10: 0-13-745167-9
- ISBN-13: 978-0-13-745167-8
Phadke was trained in robust design techniques by Genichi Taguchi, the mastermind behind Japanese quality manufacturing technologies and the father of Japanese quality control. Taguchi's approach is currently under consideration to be adopted as a student protocol with the US govrnment. The foreword is written by Taguchi. This book offers a complete blueprint for structuring projects to achieve rapid completion with high engineering productivity during the research and development phase to ensure that high quality products can be made quickly and at the lowest possible cost. Some topics covered are: orthogonol arrays, how to construct orthogonal arrays, computer-aided robutst design techniques, dynamic systems design methods, and more.
Table of Contents
2. Principles of Quality Engineering.
3. Matrix Experiments Using Orthogonal Arrays.
4. Steps in Robust Design.
5. Signal-to-Noise Ratios.
6. Quality Characteristics.
7. Constructing Orthogonal Arrays.
8. Computer-Aided Robust Design.
9. Design of Dynamic Systems.
10. Tuning Computer Systems for High Performance.
11. Reliability Improvement.
Appendix A: Orthogonality of a Matrix Experiment.
Appendix B: Unconstrained Optimization.
Appendix C: Standard Orthogonal Arrays and Linear Graphs.
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