Chapter 7. Design and Analysis of Industrial Experiments
- Shirley Coleman Technical Director2,
- Tony Greenfield3,
- Dave Stewardson2,
- Douglas C. Montgomery4
Published Online: 3 MAR 2008
DOI: 10.1002/9780470997482.ch7
Copyright © 2008 John Wiley & Sons, Ltd
Book Title
Statistical Practice in Business and Industry
Additional Information
How to Cite
Robinson, T. J. (2008) Design and Analysis of Industrial Experiments, in Statistical Practice in Business and Industry (eds S. Coleman, T. Greenfield, D. Stewardson and D. C. Montgomery), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470997482.ch7
Editor Information
- 2
Industrial Statistics Research Unit, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
- 3
Greenfield Research, Little Hucklow, Buxton SK17 8RT, UK
- 4
Regents' Professor of Industrial Engineering & Statistics, ASU Foundation Professor of Engineering, Department of Industrial Engineering Arizona State University Tempe, AZ 85287-5906, USA
Publication History
- Published Online: 3 MAR 2008
- Published Print: 7 MAR 2008
Book Series:
ISBN Information
Print ISBN: 9780470014974
Online ISBN: 9780470997482
- Summary
- Chapter
Keywords:
- controllable factors and uncontrollable factors;
- hard to change factors;
- experimental design and treatment combination;
- phase one - region seeking;
- popular optimisation algorithm - steepest ascent/descent;
- two-level factorial design;
- fractional factorial designs;
- sparsity-of-effects principle and ABC interaction;
- path of steepest ascent (or descent);
- second-order model - central composite design (CCD)
Summary
This chapter contains sections titled:
Introduction
Two-level factorial designs
Centre runs
Blocking in 2k factorial designs
Fractional factorial designs
Process improvement with steepest ascent
Optimal designs and computer-generated designs
Graphical techniques for comparing experimental designs
Industrial split-plot designs
Supersaturated designs
Experimental designs for quality improvement
The future
References