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Statistical robust design : an industrial perspective/ Magnus Arner

By: Material type: TextTextPublication details: Chichester : John Wiley, 2014.Description: x, 234 pages; dig.; 23.5 cmISBN:
  • 9781118625033
Subject(s): DDC classification:
  • 23rd. SB:745.2 Ar748
Contents:
1. What is robust design?-- 2. DOE for robust design, part 1-- 3. Noise and control factors-- 4. Response, signal, and P diagrams-- 5. DOE for robust design, part 2-- 6. Smaller-the-better and larger-the-better-- 7. Regression for robust design-- 8. Mathematics of robust design-- 9. Design and analysis of computer experiments-- 10. Monte Carlo methods for robust design-- 11. Taguchi and his ideas on robust design
Summary: Robust Design is an important topic in many areas of the manufacturing industry, there is little on the market that provides adequate coverage. This book deals with the statistical theory of how to design products to be robust against random variation in ""noise"". It adopts a practice-oriented approach to robust design, digressing from the traditional Taguchi approach. Examples featured are taken from an industrial setting to illustrate how to make use of statistics to identify robust design solutions.
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Includes index

1. What is robust design?--
2. DOE for robust design, part 1--
3. Noise and control factors--
4. Response, signal, and P diagrams--
5. DOE for robust design, part 2--
6. Smaller-the-better and larger-the-better--
7. Regression for robust design--
8. Mathematics of robust design--
9. Design and analysis of computer experiments--
10. Monte Carlo methods for robust design--
11. Taguchi and his ideas on robust design

Robust Design is an important topic in many areas of the manufacturing industry, there is little on the market that provides adequate coverage. This book deals with the statistical theory of how to design products to be robust against random variation in ""noise"". It adopts a practice-oriented approach to robust design, digressing from the traditional Taguchi approach. Examples featured are taken from an industrial setting to illustrate how to make use of statistics to identify robust design solutions.

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