4. A Response Surface Design with a Categorical Factor

  1. Peter Goos1 and
  2. Bradley Jones2

Published Online: 24 JUN 2011

DOI: 10.1002/9781119974017.ch4

Optimal Design of Experiments: A Case Study Approach

Optimal Design of Experiments: A Case Study Approach

How to Cite

Goos, P. and Jones, B. (2011) A Response Surface Design with a Categorical Factor, in Optimal Design of Experiments: A Case Study Approach, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119974017.ch4

Author Information

  1. 1

    University of Antwerp and Erasmus University Rotterdam, Netherlands

  2. 2

    JMP Division of SAS, UK

Publication History

  1. Published Online: 24 JUN 2011
  2. Published Print: 1 JUL 2011

ISBN Information

Print ISBN: 9780470744611

Online ISBN: 9781119974017

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Keywords:

  • response surface design - with a categorical factor;
  • factors, driving performance of product, or process - finding optimal settings, for factors;
  • Fraction of Design Space (FDS) plots - powerful diagnostic tool for comparing designs, precise prediction;
  • case, robust and optimal process experiment - factor-level ranges for robustness experiment;
  • D-optimal 24-run design - for robustness experiment;
  • data analysis - data for robustness experiment;
  • peek into black box, quadratic effects - optimal settings for factors;
  • dummy variables for multilevel categorical factors - robustness at Lone Star Snack Foods;
  • constructing fraction of design space plots - FDS plots, precision of prediction;
  • background reading, design optimality criteria - in line with optimal experimental design

Summary

This chapter contains sections titled:

  • Key concepts

  • Case: a robust and optimal process experiment

  • Peek into the black box

  • Background reading

  • Summary