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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 39, 2007 - Issue 3
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Articles

Optimal Designs for Mixture-Process Experiments with Control and Noise Variables

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Pages 179-190 | Published online: 21 Nov 2017

References

  • Borror; C. M.; Montgomery, D. C.; and Myers, R. H. (2002). “Evaluation of Statistical Designs for Experiments Involving Noise Variables”. Journal of Quality Technology 34, pp. 54–70.
  • Borkowski, J. (2003). “Using a Genetic Algorithm to Generate Small Exact Response Surface Designs”. Journal of Probability and Statistical Science 1, pp. 65–88.
  • Cornell, J. A. (2002). Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data, 3rd ed. New York, NY: John Wiley & Sons.
  • Cornell, J. A. (1995). “Fitting Models to Data from Mixture Experiments Containing Other Factors”. Journal of Quality Technology 27, pp. 13–33.
  • Derringer, G. and Suich, R. (1980). “Simultaneous Optimization of Several Response Variables”. Journal of Quality Technology 12, pp. 214–219.
  • Goldfarb, H. B.; Borror, C. M.; and Montgomery, D. C. (2003). “Mixture-Process Variable Experiments with Noise Variables”. Journal of Quality Technology 35, pp. 393–405.
  • Goldfarb, H. B.; Borror, C. M.; Montgomery, D. C.; and Anderson-Cook, C. M. (2004). “Evaluating Mixture-Process Designs with Control and Noise Variables”. Journal of Quality Technology 36, pp. 245–262.
  • Goldfarb, H. B.; Borror, C. M.; Montgomery, D. C.; and Anderson-Cook, C. M. (2005). “Using Genetic Algorithms to Generate Mixture-Process Experimental Designs Involving Control and Noise Variables”. Journal of Quality Technology 37, pp. 60–74.
  • Hamada, M.; Martz, H. F.; Reese, C. S.; and Wilson, A. G. (2001). “Finding Near-Optimal Bayesian Experimental Designs via Genetic Algorithms”. The American Statistician 55, pp. 175–181.
  • Hamada, M.; Martz, H. F.; and Steiner, S. (2005). “Accounting for Mixture Errors in Analyzing Mixture Experiments”. Journal of Quality Technology 37, pp. 139–148.
  • Heredia-Langner, A.; Carlyle, W. M.; Montgomery, D. C.; Borror, C. M.; and Runger, G. C. (2003). “Genetic Algorithms for the Construction of D-Optimal Designs”. Journal of Quality Technology 35, pp. 28–46.
  • Heredia-Langner, A.; Montgomery, D. C.; Carlyle, W. M.; and Borror, C. M. (2004). “Model-Robust Designs: A Genetic Algorithm Approach”. Journal of Quality Technology 36, pp. 263–279.
  • Lucas, J. M. (1994). “How to Achieve a Robust Process Using Response Surface Methodology”. Journal of Quality Technology 26, pp. 248–260.
  • Myers, R. H.; Montgomery, D. C.; Vining, G. G.; Borror, C. M.; and Kowalski, S. M. (2004). “Response Surface Methodology: A Retrospective and Literature Survey”. Journal of Quality Technology 36, pp. 53–77.
  • Myers, R. H.; Khuri, A. I.; and Vining, G. G. (1992). “Response Surface Alternatives to the Taguchi Robust Parameter Design Approach”. American Statistician 46, pp. 131–139.
  • Myers, R. H. and Montgomery, D. C. (2002). Response Surface Methodology, 2nd ed. New York, NY: John Wiley & Sons.
  • Piepel, G. F. and Cornell, J. A. (1985). “Models for Mixture Experiments When the Response Depends on the Total Amount”. Technometrics 27, pp. 219–227.
  • Piepel, G. F. and Cornell, J. A. (1987). “Designs for Mixture-Amount Experiments”. Journal of Quality Technology 26, pp. 177–196.
  • Steiner, S. H. and Hamada, M. (1997). “Making Mixtures Robust to Noise and Mixing Measurement Errors”. Journal of Quality Technology 29, pp. 441–450.
  • Taguchi, G. (1986). Introduction to Quality Engineering. Quality Resources. White Plains, NJ.
  • Taguchi, G. (1987). System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Cost. White Plains, NJ: Quality Resources.

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