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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 26, 1994 - Issue 4
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How to Achieve a Robust Process Using Response Surface Methodology

James M. LucasJ. M. Lucas and Associates, 5120 New Kent Road, Wilmington, DE19808View further author information
Pages 248-260 | Published online: 21 Feb 2018

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Melis Zeybek. (2020) Interval robust design under contaminated and non normal data. Communications in Statistics - Theory and Methods 49:22, pages 5406-5418.
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P. Angelopoulos, K. Drosou & C. Koukouvinos. (2013) An orthogonal arrays approach to robust parameter designs methodology. Journal of Applied Statistics 40:2, pages 429-437.
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Eduardo Santiago. (2012) Design of robust parameter experiments in a continuous space using an evolutionary optimization algorithm. Journal of Statistical Computation and Simulation 82:6, pages 825-847.
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DanielW. Apley & Jeongbae Kim. (2011) A cautious approach to robust design with model parameter uncertainty. IIE Transactions 43:7, pages 471-482.
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P. Angelopoulos & C. Koukouvinos. (2008) Some robust parameter designs from orthogonal arrays. Journal of Applied Statistics 35:12, pages 1399-1408.
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Daniel D. Frey & Xiang Li. (2008) Using Hierarchical Probability Models to Evaluate Robust Parameter Design Methods. Journal of Quality Technology 40:1, pages 59-77.
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Enrique Del Castillo, María Jesús Alvarez, Laura Ilzarbe & Elizabeth Viles. (2007) A New Design Criterion for Robust Parameter Experiments. Journal of Quality Technology 39:3, pages 279-295.
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Peter J. Chung, Heidi B. Goldfarb & Douglas C. Montgomery. (2007) Optimal Designs for Mixture-Process Experiments with Control and Noise Variables. Journal of Quality Technology 39:3, pages 179-190.
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William R. Myers, William A. Brenneman & Raymond H. Myers. (2005) A Dual-Response Approach to Robust Parameter Design for a Generalized Linear Model. Journal of Quality Technology 37:2, pages 130-138.
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Heidi B. Goldfarb, Connie M. Borror, Douglas C. Montgomery & Christine M. Anderson-Cook. (2005) Using Genetic Algorithms to Generate Mixture-Process Experimental Designs Involving Control and Noise Variables. Journal of Quality Technology 37:1, pages 60-74.
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H. Evangelaras & C. Koukouvinos. (2004) Combined Arrays with Minimum Number of Runs and Maximum Estimation Efficiency. Communications in Statistics - Theory and Methods 33:7, pages 1621-1628.
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Guillermo Miró Quesada & Enrique Del Castillo. (2004) A Dual-Response Approach to the Multivariate Robust Parameter Design Problem. Technometrics 46:2, pages 176-187.
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Guillermo Miró-Quesada, Enrique Del Castillo & John J. Peterson. (2004) A Bayesian Approach for Multiple Response Surface Optimization in the Presence of Noise Variables. Journal of Applied Statistics 31:3, pages 251-270.
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Guillermo Miró-Quesada & Enrique Del Castillo. (2004) Two Approaches for Improving the Dual Response Method in Robust Parameter Design. Journal of Quality Technology 36:2, pages 154-168.
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Raymond H. Myers, Douglas C. Montgomery, G. Geoffrey Vining, Connie M. Borror & Scott M. Kowalski. (2004) Response Surface Methodology: A Retrospective and Literature Survey. Journal of Quality Technology 36:1, pages 53-77.
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Heidi B. Goldfarb, Connie M. Borror & Douglas C. Mongomery. (2003) Mixture-Process Variable Experiments with Noise Variables. Journal of Quality Technology 35:4, pages 393-405.
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William A. Brenneman & William R. Myers. (2003) Robust Parameter Design with Categorical Noise Variables. Journal of Quality Technology 35:4, pages 335-341.
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Onur Köksoy & Necip Doganaksoy. (2003) Joint Optimization of Mean and Standard Deviation Using Response Surface Methods. Journal of Quality Technology 35:3, pages 239-252.
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Andrew M. Kuhn. (2003) Optimizing Response Surface Experiments with Noise Factors Using Confidence Regions. Quality Engineering 15:3, pages 419-426.
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Connie M. Borror, Douglas C. Montgomery & Raymond H. Myers. (2002) Evaluation of Statistical Designs for Experiments Involving Noise Variables. Journal of Quality Technology 34:1, pages 54-70.
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Jose LuisDuarte Ribeiro, FlavioS. Fogliatto & CarlaS. ten Caten. (2001) MINIMIZING MANUFACTURING AND QUALITY COSTS IN MULTIRESPONSE OPTIMIZATION. Quality Engineering 13:4, pages 559-569.
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DouglasC. Montgomery. (2001) Opportunities and challenges for industrial statisticians. Journal of Applied Statistics 28:3-4, pages 427-439.
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Jose Luis Duarte Ribeiro, FlavioS. Fogliatto & CarlaS. ten Caten. (2000) MINIMIZING MANUFACTURING AND QUALITY COSTS IN MULTIRESPONSE OPTIMIZATION. Quality Engineering 13:2, pages 191-201.
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Søren Bisgaard. (2000) The Design and Analysis of 2 × 2 Split Plot Experiments. Journal of Quality Technology 32:1, pages 39-56.
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M.L. Aggrawal & Renu Kaul. (1999) Combined array approach for optimal designs. Communications in Statistics - Theory and Methods 28:11, pages 2655-2670.
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Raymond H. Myers. (1999) Response Surface Methodology—Current Status and Future Directions. Journal of Quality Technology 31:1, pages 30-44.
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R. I. Whitfield. (1998) A Robust Design Methodology Suitable for Application to One-off Products. Journal of Engineering Design 9:4, pages 373-387.
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Raymond H. Myers, Yoon Kim & Kristi L. Griffiths. (1997) Response Surface Methods and the Use of Noise Variables. Journal of Quality Technology 29:4, pages 429-440.
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Allan E. Ames, Neil Mattucci, Stephen Macdonald, Geza Szonyi & Douglas M. Hawkins. (1997) Quality Loss Functions for Optimization across Multiple Response Surfaces. Journal of Quality Technology 29:3, pages 339-346.
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JohnJ. Borkowski & JamesM. Lucas. (1997) Designs of Mixed Resolution for Process Robustness Studies. Technometrics 39:1, pages 63-70.
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JamesM. Lucas. (1996) Comments on Computer Experiments. Technometrics 38:2, pages 197-199.
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G. Geoffrey Vining & Diane Schaub. (1996) Experimental Designs for Estimating Both Mean and Variance Functions. Journal of Quality Technology 28:2, pages 135-147.
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