DOE References

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Chapter Appendix H: DOE References


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Chapter Appendix H  
DOE References  

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  1. AIAG (2010), Measurement Systems Analysis (MSA), Automotive Industry Action Group, 4th edition.
  2. Box, G. E. P., and Behnken, D. W. (1960), Some New Three Level Designs for the Study of Quantitative Variables, Technometrics, Vol. 2, No. 4, pp. 455-475.
  3. Box, G. E. P., and Draper, N. R. (1987), Empirical Model Building and Response Surfaces, John Wiley & Sons, Inc., New York.
  4. Box, G. E. P., Hunter, W. G., and Hunter, J. S. (1978), Statistics for Experimenters, John Wiley & Sons, Inc., New York.
  5. Cook, R. D. and Nachtsheim, C. J. (1980), “A Comparison of Algorithms for Constructing Exact D-Optimal Designs,” Technometrics, vol. 22, no. 3, 315-324.
  6. Derringer, G., and Suich, R. (1980), Simultaneous Optimization of Several Response Variables, Journal of Quality Technology, Vol. 12, pp. 214-219.
  7. Draper, N., and Smith H. (1998), Applied Regression Analysis, John Wiley & Sons, Inc., New York.
  8. Dykstra, O. (1971), “The augmentation of experimental data to maximize |X’X|," Technometrics, vol. 13, no. 3, 682-688.
  9. Fisher, R. A. (1966), The Design of Experiments, Hafner Publishing Company, New York.
  10. Fedorov, V. V. (1972), “Theory of Optimal Experiments (Review)”, Biometrika, cvol. 59, no. 3, 697-698. Translated and edited by W. J. Studden and E. M. Klimko.
  11. Fries, A., and Hunter, W. G. (1980), Minimum Aberration 2k-p Designs, Technometrics, Vol. 22, pp. 601-608.
  12. Galil, Z. and Kiefer, J. (1980), “Time and Space Saving Computer Methods, Related to Mitchell’s DETMAX, for Finding D-Optimal Designs”, Technometrics, vol. 22, no. 3, 301-313.
  13. Guo, H., Niu, P., and Szidarovszky, F. (2012), "A Simple Method for Power Calculation in Experiments for Treatment Comparison," The IEEE International Conference on Industrial Engineering and Engineering Management, Dec, 2012.
  14. Hamada, M., and Balakrishnan N. (1998), Analyzing Unreplicated Factorial Experiments: A Review with Some New Proposals, Statistica Sinica, Vol. 8, pp. 1-41.
  15. Johnson, M. E. and Nachtsheim, C. J. (1983), “Some Guidelines for Constructing Exact D-Optimal Designs on Convex Design Spaces,” Technometrics , vol. 25, no. 3, 271-277.
  16. Khuri, A. I., and Cornell, J. A. (1996), Response Surfaces: Designs and Analyses, Dekker, New York.
  17. Kutner, M. H., Nachtsheim, C.J., Neter, J., and Li, W. (2005), Applied Linear Statistical Models, McGraw-Hill/Irwin, New York.
  18. Lenth, R. V. (1989), "Quick and Easy Analysis of Unreplicated Factorials," Technometrics, Vol. 31, pp. 469-473.
  19. Meeker, William Q., and Escobar, Luis A. (1998), Statistical Methods for Reliability Data, John Wiley & Sons, Inc., New York.
  20. Montgomery, Douglas C. (2001), Design and Analysis of Experiments, John Wiley & Sons, Inc., New York.
  21. Montgomery, Douglas C., and Peck, E. A. (1992), Introduction to Linear Regression Analysis, John Wiley & Sons, Inc., New York.
  22. Montgomery, Douglas C., and Runger, George C. (1991), Applied Statistics and Probability for Engineers, John Wiley & Sons, Inc., New York.
  23. Montgomery, Douglas C., and Runger, George C. (1993a), Gauge capability analysis and designed experiments. Part I: Basic methods. Quality Engineering, 6, 1, 115-135.
  24. Montgomery, Douglas C., and Runger, George C.(1993b), Gauge capability analysis and designed experiments. Part II: Experimental design models and variance component estimation, 6, 2, 289-305.
  25. Myers, R. H., and Montgomery, D. C. (1995), Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley & Sons, Inc., New York.
  26. Plackett, R. L., and Burman, J. P. (1946), The Design of Optimum Multifactorial Experiments, Biometrika, Vol. 33, No. 4, pp. 305-325.
  27. ReliaSoft Corporation (2007a), Accelerated Life Testing Reference, ReliaSoft Publishing, Tucson, AZ.
  28. ReliaSoft Corporation (2007b), Life Data Analysis Reference, ReliaSoft Publishing, Tucson, AZ.
  29. Ross, S. (1987), Introduction to Probability and Statistics for Engineers and Scientists, John Wiley & Sons, Inc., New York.
  30. Sahai, Hardeo, and Ageel, Mohammed I. (2000), The Analysis of Variance, Birkhauser, Boston.
  31. Searle, S. R. (1997), Linear Models, John Wiley & Sons, Inc., New York.
  32. Searle, S. R. (1971), Topics in Variance Component Estimation, Biometrics, Vol. 27, No. 1, pp. 1-76.
  33. Taguchi, G. (1991), Introduction to Quality Engineering, Asian Productivity Organization, UNIPUB, White Plains, New York.
  34. Taguchi, G. (1987), System of Experimental Design, UNIPUB/Kraus International, White Plains, New York.
  35. Taguchi, Genichi, Chowdhury, Subir, and Wu, Yuin. (2005), Taguchi's Quality Engineering Handbook, John Wiley & Sons, Inc., Hoboken, New Jersey.
  36. Tukey, J. W. (1951), Quick and Dirty Methods in Statistics, Part II, Simple Analysis for Standard Designs, Proceedings of the Fifth Annual Convention, American Society for Quality Control, pp. 189-197.
  37. Wu, C. F. Jeff, and Hamada, Michael (2000), Experiments: Planning, Analysis and Parameter Design Optimization, John Wiley & Sons, Inc., New York.
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