Two Approaches for Improving the Dual Response Method in Robust Parameter Design

References

• Arnold, S. F. (1990). Mathematical Statistics. Prentice Hall, Englewood Cliffs, NJ.
   Google Scholar
• Arnold, S. F. (1981). The Theory of Linear Models and Multivariate Analysis. Wiley, New York, NY.
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• Borror, C. M. and Montgomery, D. C. (2000). “Mixed Resolution Designs as Alternatives to Taguchi Inner/Outer Array Designs for Robust Design Problems”. Quality and Reliability Engineering International 16, pp. 117–127.
   Web of Science ®Google Scholar
• Borkowski, J. J. and Lucas, J. M. (1997). “Design of Mixed Resolution for Process Robustness Studies”. Technometrics 39, pp. 63–70.
   Web of Science ®Google Scholar
• Cantell, B.; Ramírez, J.; and Gadson, W. (1997). “Optimization of a Wafer Stepper Alignment System Using Robust Design” in Statistical Case Studies for Industrial Process Improvement edited by V. Czitrom and P. D. Spagon, SIAM, Philadelphia, PA.
   Google Scholar
• Box, G. E. P. and Jones, S. (1990). “Designing Products That Are Robust To The Environment”. Report Series in Quality and Productivity. CPQI, University of Wisconsin, Number 56.
   Google Scholar
• Engel, J. and Huele, F. (1996). “A Generalized Linear Modeling Approach to Robust Design”. Technometrics 38, pp. 365–373.
   Web of Science ®Google Scholar
• Giovannitti-Jensen, A. and Myers, R. H. (1989). “Graphical Assessment of the Prediction Capability of Response Surface Designs”. Technometrics 31, pp. 159–171.
   Web of Science ®Google Scholar
• Khatree, R. (1996). “Robust Parameter Design: A Response Surface Approach”. Journal of Quality Technology 28, pp. 187–198.
   Google Scholar
• Lucas, J. M. (1994). “How to Achieve a Robust Process Using Response Surface Methodology”. Journal of Quality Technology 26, pp. 248–260.
   Web of Science ®Google Scholar
• Myers, R. H. (1991). “Response Surface Methodology in Quality Improvement”. Communications in Statistics Theory and Methods 20, pp. 457–476.
   Web of Science ®Google Scholar
• Myers, R. H.; Khuri, A. I.; and Vining G. (1992). “Response Surface Alternatives to the Taguchi Robust Parameter Design”. The American Statistician 46, pp. 131–139.
   Web of Science ®Google Scholar
• Myers, R. H.; Vining, G. G.; Giovannitti-Jensen, A.; and Myers, S. L. (1992). “Variance Dispersion Properties of Second-Order Response Surface Designs”. Journal of Quality Technology 24, pp. 1–11.
   Web of Science ®Google Scholar
• Myers, R. H.; Kim, Y.; and Griffiths, K. L. (1997). “Response Surface Methods and the use of Noise Variables. Journal of Quality Technology 29, pp. 429–440.
   Web of Science ®Google Scholar
• Myers, R. H. and Montgomery, D. C. (2002). Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Wiley, New York, NY.
   Google Scholar
• Neff, A. R. and myers, R. H. (1999). “Recent Developments in Response Surface Methodology and its Applications in Industry” in Statistical Process Monitoring and Optimization edited by Sung H. Park and G.G. Vining, Marcel Dekker, New York, NY, pp. 457–481.
   Google Scholar
• Neter, J.; Kutner, M. H.; and Nachtsheim, C. J. (1996). Applied Linear Statistical Models. WCB-McGraw-Hill, New York, NY.
   Google Scholar
• Shoemaker, A. C.; Tsui, K.-L.; and Wu, C. F. J. (1991). “Economical Experimentation Methods for Robust Design”. Technometrics 33, pp. 415–427.
   Web of Science ®Google Scholar
• Taguchi, G. (1986). Introduction to Quality Engineering. Quality Resources, White Plains, NJ.
   Google Scholar
• Taguchi, G. (1987). System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Cost. Quality Resources, White Plains, NJ.
   Google Scholar
• Vining, G. G. and Myers, R. H. (1990). “Combining Taguchi and Response Surface philosophies: A dual response approach”. Journal of Quality Technology 22, pp. 38–45.
   Web of Science ®Google Scholar
• Vining, G. G. (1993). “A Computer Program for Generating Variance Dispersion Graphs”. Journal of Quality Technology 25, pp. 45–58.
   Web of Science ®Google Scholar