Response Surface Methodology: A Retrospective and Literature Survey

Response surface methodology (RSM) is a collection of statistical design and numerical optimization techniques used to optimize processes and product designs. The original work in this area dates from the 1950s and has been widely used, especially in the chemical and process industries. The last 15 years have seen the widespread application of RSM and many new developments. In this review paper we focus on RSM activities since 1989. We discuss current areas of research and mention some areas for future research.

[1]  G. Box,et al.  On the Experimental Attainment of Optimum Conditions , 1951 .

[2]  F. E. Satterthwaite Random Balance Experimentation , 1959 .

[3]  Robert Hooke,et al.  `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.

[4]  K. H. Booth,et al.  Some Systematic Supersaturated Designs , 1962 .

[5]  William J. Hill,et al.  A Review of Response Surface Methodology: A Literature Survey* , 1966 .

[6]  H. F. Dodge Notes on the Evolution of Acceptance Sampling Plans: Part I , 1969 .

[7]  O. Dykstra The Augmentation of Experimental Data to Maximize [X′X] , 1971 .

[8]  Van Schalkwyk,et al.  On the design of mixture experiments , 1971 .

[9]  W. J. Studden,et al.  Optimal Designs for Estimating the Slope of a Polynomial Regression , 1972 .

[10]  R. H. Myers,et al.  Response Surface Techniques for Dual Response Systems , 1973 .

[11]  Leon S. Lasdon,et al.  Nonlinear optimization using the generalized reduced gradient method , 1974 .

[12]  R. H. Myers,et al.  A Generalization of the Response Surface Mean Square Error Criterion with a Specific Application to the Scope , 1975 .

[13]  R Mead,et al.  A review of response surface methodology from a biometric viewpoint. , 1975, Biometrics.

[14]  R. Hader,et al.  Slope-Rotatable Central Composite Designs , 1978 .

[15]  G. Derringer,et al.  Simultaneous Optimization of Several Response Variables , 1980 .

[16]  A. Khuri,et al.  Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions , 1981 .

[17]  W. Welch Branch-and-Bound Search for Experimental Designs Based on D Optimality and Other Criteria , 1982 .

[18]  L. S. Nelson What Do LowFRatios Tell You , 1985 .

[19]  J. Pignatiello,et al.  Discussion: Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[20]  L. S. Nelson Column: Technical Aids: What Do Low F Ratios Tell You? , 1985 .

[21]  N. Draper Small Composite Designs , 1985 .

[22]  J. Lucas Discussion: Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[23]  R. Mukerjee,et al.  Minimax second- and third-order designs to estimate the slope of a response surface , 1985 .

[24]  George E. P. Box,et al.  Empirical Model‐Building and Response Surfaces , 1988 .

[25]  田口 玄一,et al.  System of experimental design : engineering methods to optimize quality and minimize costs , 1987 .

[26]  L. Haines The application of the annealing algorithm to the construction of exact optimal designs for linear-regression models , 1987 .

[27]  Sung H. Park A class of multifactor designs for estimating the slope of response surfaces , 1987 .

[28]  J. Rice Mathematical Statistics and Data Analysis , 1988 .

[29]  J. Cornell Analyzing Data from Mixture Experiments Containing Process Variables: A Split-Plot Approach , 1988 .

[30]  N. Draper,et al.  Response-surface designs for quantitative and qualitative variables , 1988 .

[31]  Neil R. Ullman,et al.  Signal-to-noise ratios, performance criteria, and transformations , 1988 .

[32]  D. Ruppert,et al.  [Signal-to-Noise Ratios, Performance Criteria, and Transformations]: Discussion , 1988 .

[33]  Michael P. Meredith,et al.  Covariance Analysis for Split Plot and Split Block Designs and Computer Packages , 1988 .

[34]  A. Khuri A measure of rotatability for response-surface designs , 1988 .

[35]  Conrad A. Fung,et al.  An explanation and critique of taguchi's contributions to quality engineering , 1988 .

[36]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[37]  P. McCullagh,et al.  Generalized Linear Models , 1992 .

[38]  André I. Khuri,et al.  Response surface methodology: 1966–1988 , 1989 .

[39]  Jerome Sacks,et al.  Designs for Computer Experiments , 1989 .

[40]  R. H. Myers,et al.  Graphical assessment of the prediction capability of response surface designs , 1989 .

[41]  G. Geoffrey Vining,et al.  Combining Taguchi and Response Surface Philosophies: A Dual Response Approach , 1990 .

[42]  L. Kalish Efficient design for estimation of median lethal dose and quantal dose-response curves. , 1990, Biometrics.

[43]  Jerome Sacks,et al.  Computer Experiments for Quality Control by Parameter Design , 1990 .

[44]  P. McCullagh,et al.  Generalized Linear Models, 2nd Edn. , 1990 .

[45]  Dennis K. J. Lin,et al.  Small response-surface designs , 1990 .

[46]  D. Montgomery USING FRACTIONAL FACTORIAL DESIGNS FOR ROBUST PROCESS DEVELOPMENT , 1990 .

[47]  E. Ziegel Statistical Design and Analysis of Industrial Experiments , 1990 .

[48]  M. E. Johnson,et al.  Minimax and maximin distance designs , 1990 .

[49]  Norman R. Draper,et al.  Another look at rotatability , 1990 .

[50]  John A. Nelder,et al.  Generalized linear models for the analysis of Taguchi-type experiments , 1991 .

[51]  Kwok-Leung Tsui,et al.  Economical experimentation methods for robust design , 1991 .

[52]  Joseph J. Pignatiello,et al.  TOP TEN TRIUMPHS AND TRAGEDIES OF GENICHI TAGUCHI , 1991 .

[53]  Raymond H. Myers,et al.  Response surface methodology in quality improvement , 1991 .

[54]  F. Pukelsheim,et al.  First and second order rotatability of experimental designs, moment matrices, and information surfaces , 1991 .

[55]  I. Ford,et al.  The Use of a Canonical Form in the Construction of Locally Optimal Designs for Non‐Linear Problems , 1992 .

[56]  A. I. Khuri Diagnostic Results Concerning a Measure of Rotatability , 1992 .

[57]  Stephen Jones,et al.  Split-plot designs for robust product experimentation , 1992 .

[58]  Dennis K. J. Lin,et al.  Projection properties of Plackett and Burman designs , 1992 .

[59]  J. M. Lucas,et al.  Split Plotting and Randomization in Industrial Experiments , 1992 .

[60]  R. H. Myers,et al.  Variance dispersion properties of second-order response surface designs , 1992 .

[61]  G. Geoffrey Vining,et al.  Taguchi's parameter design: a panel discussion , 1992 .

[62]  R. Sitter Robust designs for binary data , 1992 .

[63]  Subir Ghosh,et al.  Determination of optimum experimental conditions using dispersion main effects and interactions of factors in replicated factorial experiments , 1992 .

[64]  J. H. Schuenemeyer,et al.  Generalized Linear Models (2nd ed.) , 1992 .

[65]  T. Mathew,et al.  Exact and Optimum Tests in Unbalanced Split-Plot Designs under Mixed and Random Models , 1992 .

[66]  R. H. Myers,et al.  Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , 1992 .

[67]  J. Engel,et al.  Modelling Variation in Industrial Experiments , 1992 .

[68]  Henry P. Wynn,et al.  Screening, predicting, and computer experiments , 1992 .

[69]  Douglas C. Montgomery,et al.  The use of statistical process control and design of experiments in product and process improvement , 1992 .

[70]  O. Krafft,et al.  D-optimal designs for a multivariate regression model , 1992 .

[71]  Dennis K. J. Lin,et al.  A new class of supersaturated designs , 1993 .

[72]  Douglas C. Montgomery,et al.  A Nonlinear Programming Solution to the Dual Response Problem , 1993 .

[73]  K. Tsui,et al.  Response model analysis for robust design experiments , 1993 .

[74]  R. H. Myers,et al.  A Graphical Approach for Evaluating Mixture Designs , 1993 .

[75]  Dennis K. J. Lin Another Look at First-Order Saturated Designs: The p-efficient Designs , 1993 .

[76]  F. Pukelsheim,et al.  Rotatability of variance surfaces and moment matrices , 1993 .

[77]  Joseph J. Pignatiello,et al.  STRATEGIES FOR ROBUST MULTIRESPONSE QUALITY ENGINEERING , 1993 .

[78]  K. Chaloner,et al.  Optimum experimental designs for properties of a compartmental model. , 1993, Biometrics.

[79]  Changbao Wu,et al.  Construction of supersaturated designs through partially aliased interactions , 1993 .

[80]  C. Spargo,et al.  Chemiluminescent detection of strand displacement amplified DNA from species comprising the Mycobacterium tuberculosis complex. , 1993, Molecular and cellular probes.

[81]  G. Geoffrey Vining,et al.  A Computer Program for Generating Variance Dispersion Graphs , 1993 .

[82]  A. Ferrer,et al.  Small samples estimation of dispersion effects from unreplicated data , 1993 .

[83]  J. Grego Generalized Linear Models and Process Variation , 1993 .

[84]  C. F. Wu,et al.  Optimal designs for binary response experiments: Fieller, D, and A criteria , 1993 .

[85]  Dennis K. J. Lin,et al.  Generating alias relationships for two-level Plackett and Burman designs , 1993 .

[86]  David M. Steinberg,et al.  NOISE FACTORS, DISPERSION EFFECTS, AND ROBUST DESIGN , 1993 .

[87]  W. Näther Optimum experimental designs , 1994 .

[88]  R. H. Myers,et al.  Some alphabetic optimal designs for the logistic regression model , 1994 .

[89]  N. Draper,et al.  A note on slope rotatability over all directions , 1994 .

[90]  N. Draper,et al.  Isolation of Degrees of Freedom for Box—Behnken Designs , 1994 .

[91]  Jose Ramirez,et al.  Robust design of a polysilicon deposition process using split-plot analysis , 1994 .

[92]  P. Rosenbaum DISPERSION EFFECTS FROM FRACTIONAL FACTORIALS IN TAGUCHI'S METHOD OF QUALITY DESIGN , 1994 .

[93]  James M. Lucas,et al.  How to Achieve a Robust Process Using Response Surface Methodology , 1994 .

[94]  F. Pukelsheim,et al.  On third order rotatability , 1994 .

[95]  David M. Steinberg,et al.  Dispersion Effects in Robust-Design Experiments with Noise Factors , 1994 .

[96]  Yurii Nesterov,et al.  Interior-point polynomial algorithms in convex programming , 1994, Siam studies in applied mathematics.

[97]  Joan M. Donohue Experimental designs for simulation , 1994, Proceedings of Winter Simulation Conference.

[98]  W. DuMouchel,et al.  A simple Bayesian modification of D-optimal designs to reduce dependence on an assumed model , 1994 .

[99]  Dennis K. J. Lin,et al.  Characterizing projected designs: repeat and mirror-image runs , 1995 .

[100]  Wanzhu Tu,et al.  Dual response surface optimization , 1995 .

[101]  Rafael Romero,et al.  A SIMPLE METHOD TO STUDY DISPERSION EFFECTS FROM NON- NECESSARILY REPLICATED DATA IN INDUSTRIAL CONTEXTS , 1995 .

[102]  P. Laycock,et al.  Optimum Experimental Designs , 1995 .

[103]  Dallas Johnson,et al.  A comparison of inference procedures in unbalanced split-plot designs , 1995 .

[104]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[105]  F. Pukelsheim,et al.  Slope rotatability over all directions designs for k = 4 , 1995 .

[106]  Sarah W. Hardy,et al.  Nonparametric Regression, Kriging and Process Optimization , 1995 .

[107]  Jan Engel,et al.  Taguchi parameter design by second order response surfaces , 1996 .

[108]  Dennis K. J. Lin Generating Systematic Supersaturated Designs , 1995 .

[109]  Ching-Shui Cheng,et al.  Some Projection Properties of Orthogonal Arrays , 1995 .

[110]  K. Chaloner,et al.  Bayesian Experimental Design: A Review , 1995 .

[111]  Anne E. Freeny,et al.  Graphical Analysis for a Large Designed Experiment , 1995 .

[112]  F. Pukelsheim,et al.  Slope rotatability over all directions designs , 1995 .

[113]  J. Borkowski Spherical prediction-variance properties of central composite and Box-Behnken designs , 1995 .

[114]  S. Bisgaard,et al.  Standard errors for the eigenvalues in second-order response surface models , 1996 .

[115]  Linda M. Haines,et al.  14 Designs for nonlinear and generalized linear models , 1996, Design and analysis of experiments.

[116]  Dennis K. J. Lin,et al.  Marginally oversaturated designs , 1996 .

[117]  Norman R. Draper,et al.  An overview of design of experiments , 1996 .

[118]  Dennis K. J. Lin,et al.  11 Response surface designs , 1996, Design and analysis of experiments.

[119]  R. H. Myers,et al.  Optimal Designs for Bivariate Logistic Regression , 1996 .

[120]  Peter R. Nelson,et al.  Dual Response Optimization via Direct Function Minimization , 1996 .

[121]  Raymond H. Myers,et al.  Response Surface Methods for Bi-Randomization Structures , 1996 .

[122]  Michael S. Hamada,et al.  Discussion: factor-based or effect-based modeling? Implications for design , 1996 .

[123]  Arden Miller,et al.  Parameter Design for Signal-Response Systems: A Different Look at Taguchi's Dynamic Parameter Design , 1996 .

[124]  D. Montgomery,et al.  Foldovers of 2k-p Resolution IV Experimental Designs , 1996 .

[125]  P. Rosenbaum Some useful compound dispersion experiments in quality design , 1996 .

[126]  G. Geoffrey Vining,et al.  EXPERIMENTAL DESIGNS FOR ESTIMATING BOTH MEAN AND VARIANCE FUNCTIONS , 1996 .

[127]  Enrique Del Castillo,et al.  Multiresponse Process Optimization via Constrained Confidence Regions , 1996 .

[128]  George E. P. Box,et al.  Quality Quandaries* : Split Plot Experiments , 1996 .

[129]  J. C. Lu,et al.  Combined Generalized Linear Modelling–Non‐Linear Programming Approach to Robust Process Design—A Case‐Study in Circuit Board Quality Improvement , 1996 .

[130]  Megan Pledger Observable Uncontrollable Factors in Parameter Design , 1996 .

[131]  A. Khuri,et al.  Quantile plots of the prediction variance for response surface designs , 1996 .

[132]  F. Pukelsheim,et al.  On optimal third order rotatable designs , 1996 .

[133]  K. Tsui A critical look at Taguchi's modelling approach for robust design , 1996 .

[134]  Douglas C. Montgomery,et al.  Modified Desirability Functions for Multiple Response Optimization , 1996 .

[135]  R. H. Myers,et al.  Bayesian approach for the design and analysis of a two level factorial experiment in the presence of dispersion effects , 1996 .

[136]  G. Box,et al.  Projective properties of certain orthogonal arrays , 1996 .

[137]  Nam-Ky Nguyen An algorithmic approach to constructing supersaturated designs , 1996 .

[138]  Ravindra Khattree,et al.  ROBUST PARAMETER DESIGN : A RESPONSE SURFACE APPROACH , 1996 .

[139]  George E. P. Box,et al.  Follow-up designs to resolve confounding in multifactor experiments , 1996 .

[140]  Dennis K. J. Lin,et al.  A measurement of multi-factor orthogonality , 1996 .

[141]  B. Bergman,et al.  Dispersion Effects From 7 Unreplicated Designs in the 2 k—p Series , 1997 .

[142]  J. Lucas,et al.  Bias in test statistics when restrictions in randomization are caused by factors , 1997 .

[143]  S. Steiner,et al.  Making Mixtures Robust to Noise and Mixing Measurement Errors , 1997 .

[144]  D. Hawkins,et al.  Quality Loss Functions for Optimization across Multiple Response Surfaces , 1997 .

[145]  Eric R. Ziegel,et al.  Statistical Case Studies for Industrial Process Improvement , 1997 .

[146]  S. Yamada,et al.  Supersaturated design including an orthogonal base , 1997 .

[147]  Gary S. Wasserman,et al.  Graphical methods for robust design with dynamic characteristics , 1997 .

[148]  Ola Blomkvist,et al.  A METHOD TO IDENTIFY DISPERSION EFFECTS FROM UNREPLICATED MULTILEVEL EXPERIMENTS , 1997 .

[149]  E. Schoen,et al.  Design and analysis of a fractional 413125 split-plot experiment , 1997 .

[150]  Arden Miller Strip-plot configurations of fractional factorials , 1997 .

[151]  James M. Lucas,et al.  Designs of mixed resolution for process robustness studies , 1997 .

[152]  B. Bergman,et al.  Dispersion effects from unreplicated designs in the 2 k-p series , 1997 .

[153]  William Li,et al.  Columnwise-pairwise algorithms with applications to the construction of supersaturated designs , 1997 .

[154]  Raymond H. Myers,et al.  Response Surface Methods and the Use of Noise Variables , 1997 .

[155]  Douglas C. Montgomery,et al.  Design of Mixture Experiments Using Bayesian D-Optimality , 1997 .

[156]  Ramón V. León,et al.  17. Using Fewer Wafers to Resolve Confounding in Screening Experiments , 1997 .

[157]  D. Steinberg,et al.  The design and analysis of 2 k−p × s prototype experiments , 1997 .

[158]  T. Santner,et al.  Selection and screening procedures to determine optimal product designs , 1998 .

[159]  Dennis K. J. Lin,et al.  FORWARD SELECTION ERROR CONTROL IN THE ANALYSIS OF SUPERSATURATED DESIGNS , 1998 .

[160]  Robert W. Mee,et al.  Split-lot designs: experiments for multistage batch processes , 1998 .

[161]  Changbao Wu,et al.  Construction of response surface designs for qualitative and quantitative factors , 1998 .

[162]  G. Geoffrey Vining,et al.  A Compromise Approach to Multiresponse Optimization , 1998 .

[163]  J. Nelder,et al.  JOINT MODELING OF MEAN AND DISPERSION , 1998 .

[164]  L. Trinca,et al.  Variance Dispersion Graphs for Comparing Blocked Response Surface Designs , 1998 .

[165]  G. Vining,et al.  Response Surfaces for the Mean and Variance Using a Nonparametric Approach , 1998 .

[166]  M. Aggarwal,et al.  Robust response surface design for quantitative and qualitative factors , 1998 .

[167]  Dennis K. J. Lin,et al.  Dual Response Surface Optimization: A Fuzzy Modeling Approach , 1998 .

[168]  G. Montepiedra Application of genetic algorithms to the construction of exact D-optimal designs , 1998 .

[169]  Hugh A. Chipman,et al.  HANDLING UNCERTAINTY IN ANALYSIS OF ROBUST DESIGN EXPERIMENTS , 1998 .

[170]  Vijayan N. Nair,et al.  EXPLOITING THE INHERENT STRUCTURE IN ROBUST PARAMETER DESIGN EXPERIMENTS , 1998 .

[171]  R. Wolfinger,et al.  Joint estimation of location, dispersion, and random effects in robust design , 1998 .

[172]  N. Draper,et al.  Theory & Methods: Response Surface Designs Where Levels of Some Factors are Difficult to Change , 1998 .

[173]  F. Pukelsheim,et al.  Polynomial representations for response surface modeling , 1998 .

[174]  Dennis K. J. Lin,et al.  A graphical comparison of supersaturated designs , 1998 .

[175]  Joseph O. Voelkel,et al.  Minimum-aberration two-level split-plot designs , 1998 .

[176]  H. Chipman,et al.  Some risks in the construction and analysis of supersaturated designs , 1999 .

[177]  R. H. Myers,et al.  THE ANALYSIS OF DESIGNED EXPERIMENTS WITH NON-NORMAL RESPONSES , 1999 .

[178]  R. Sitter OPTIMAL DESIGNS FOR BINARY RESPONSE EXPERIMENTS WITH TWO DESIGN VARIABLES , 1999 .

[179]  D. Bingham,et al.  Minimum-aberration two-level fractional factorial split-plot designs , 1999 .

[180]  A. Khuri,et al.  Using quantile plots of the prediction variance for comparing designs for a constrained mixture region: an application involving a fertilizer experiment , 1999 .

[181]  D. Bingham,et al.  Some theoretical results for fractional factorial split-plot designs , 1999 .

[182]  Robert W. Mee Three-Level Simplex Designs and Their Use in Second-Order Composite Designs , 1999 .

[183]  Enrique del Castillo,et al.  Optimization of dual response systems: A comprehensive procedure for degenerate and nondegenerate problems , 1999, Eur. J. Oper. Res..

[184]  Raymond H. Myers,et al.  Response Surface Methodology--Current Status and Future Directions , 1999 .

[185]  Douglas C. Montgomery,et al.  Experimental Design for Product and Process Design and Development , 1999 .

[186]  J. Lucas,et al.  Detecting randomization restrictions caused by factors , 1999 .

[187]  George E. P. Box,et al.  Statistics as a catalyst to learning by scientific method , 1999 .

[188]  Randy R. Sitter,et al.  Minimum-Aberration Two-Level Fractional Factorial Split-Plot Designs , 1999, Technometrics.

[189]  George E. P. Box,et al.  Statistics as a Catalyst to Learning by Scientific Method Part I—An Example , 1999 .

[190]  E. Schoen Designing Fractional Two-Level Ex-periments With Nested Error Structures , 1999 .

[191]  Douglas C. Montgomery,et al.  Optimization Problems and Methods in Quality Control and Improvement , 2000 .

[192]  Shu-Kai S. Fan A Generalized Global Optimization Algorithm for Dual Response Systems , 2000 .

[193]  Alejandro Heredia-Langner,et al.  Optimization of a bonded leads process using statistically designed experiments , 2000 .

[194]  Connie M. Borror,et al.  Mixed resolution designs as alternatives to Taguchi inner/outer array designs for robust design problems , 2000 .

[195]  M. Aggarwal,et al.  Small Robust Response-Surface Designs for Quantitative and Qualitative Factors , 2000 .

[196]  Stephen Jones,et al.  SPLIT PLOTS FOR ROBUST PRODUCT AND PROCESS EXPERIMENTATION , 2000 .

[197]  Kwang-Jae Kim,et al.  Simultaneous optimization of mechanical properties of steel by maximizing exponential desirability functions , 2000 .

[198]  Max D. Morris,et al.  A Class of Three-Level Experimental Designs for Response Surface Modeling , 2000, Technometrics.

[199]  William Li,et al.  Model-Robust Factorial Designs , 2000, Technometrics.

[200]  D. Montgomery,et al.  Optimal assignment of samples to treatments for robust design , 2000 .

[201]  Robert W. Mee,et al.  Semifolding 2 k–P Designs , 2000, Technometrics.

[202]  S. Bisgaard The Design and Analysis of 2k–p × 2q–r Split Plot Experiments , 2000 .

[203]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[204]  R. H. Myers,et al.  Bayesian two-stage optimal design for mixture models , 2000 .

[205]  Douglas C. Montgomery,et al.  A comparison of several design augmentation strategies , 2000 .

[206]  Yong Zhang,et al.  Uniform Design: Theory and Application , 2000, Technometrics.

[207]  Andrew M. Kuhn,et al.  Incorporating Noise Factors Into Experiments With Censored Data , 2000, Technometrics.

[208]  Changbao Wu,et al.  FACTOR SCREENING AND RESPONSE SURFACE EXPLORATION , 2001 .

[209]  R. H. Myers,et al.  Confidence Interval Coverage for Designed Experiments Analyzed with GLMs , 2001 .

[210]  Steven G. Gilmour,et al.  Multistratum Response Surface Designs , 2001, Technometrics.

[211]  Vijayan N. Nair,et al.  Methods for Identifying Dispersion Effects in Unreplicated Factorial Experiments , 2001, Technometrics.

[212]  Connie M. Borror,et al.  Generalized linear models in the analysis of industrial experiments , 2001 .

[213]  G. Box,et al.  SIXTEEN RUN DESIGNS OF HIGH PROJECTIVITY FOR FACTOR SCREENING , 2001 .

[214]  M. Hamada,et al.  Analyzing Experiments with Correlated Multiple Responses , 2001 .

[215]  Dennis K. J. Lin,et al.  Testing Multiple Dispersion Effects in Unreplicated Fractional Factorial Designs , 2001, Technometrics.

[216]  Karen A. F. Copeland Design and Analysis of Experiments, 5th Ed. , 2001 .

[217]  R. H. Myers,et al.  Examples of Designed Experiments with Nonnormal Responses , 2001 .

[218]  R. H. Myers Generalized Linear Models: With Applications in Engineering and the Sciences , 2001 .

[219]  Elsie S. Valeroso,et al.  Comparison of Design Optimality Criteria of Reduced Models for Response Surface Designs in the Hypercube , 2001, Technometrics.

[220]  R. Sitter,et al.  Design Issues in Fractional Factorial Split-Plot Experiments , 2001 .

[221]  Dennis K. J. Lin,et al.  Confounding of Location and Dispersion Effects in Unreplicated Fractional Factorials , 2001 .

[222]  Robert W. Mee,et al.  Noncentral Composite Designs , 2001, Technometrics.

[223]  Øyvind Langsrud Identifying Significant Effects in Fractional Factorial Multiresponse Experiments , 2001, Technometrics.

[224]  P. Goos,et al.  Optimal Split-Plot Designs , 2001 .

[225]  Alyson G. Wilson,et al.  Finding Near-Optimal Bayesian Experimental Designs via Genetic Algorithms , 2001 .

[226]  Julie Zhou,et al.  A Robust Criterion for Experimental Designs for Serially Correlated Observations , 2001, Technometrics.

[227]  S. Bisgaard,et al.  Quality Quandaries ROBUST PRODUCT DESIGN: SAVING TRIALS WITH SPLIT-PLOT CONFOUNDING , 2001 .

[228]  S. Lewis,et al.  Detection of interactions in experiments on large numbers of factors , 2001 .

[229]  Connie M. Borror,et al.  Evaluation of Statistical Designs for Experiments Involving Noise Variables , 2002 .

[230]  Robert W. Mee Three-Level Simplex Designs and Their Use in Sequential Experimentation , 2002 .

[231]  Eric R. Ziegel,et al.  Generalized Linear Models , 2002, Technometrics.

[232]  Don R. Holcomb,et al.  Some notes on the construction and evaluation of supersaturated designs , 2002 .

[233]  Arden Miller,et al.  Analysis of Parameter Design Experiments for Signal-Response Systems , 2002 .

[234]  William Li,et al.  A Class of Optimal Robust Parameter Designs , 2002 .

[235]  Scott M. Kowalski 24 Run Split-Plot Experiments for Robust Parameter Design , 2002 .

[236]  Hui Liu,et al.  A Class of Experimental Designs for Estimating a Response Surface and Variance Components , 2002, Technometrics.

[237]  G. Geoffrey Vining,et al.  Split-Plot Designs and Estimation Methods for Mixture Experiments With Process Variables , 2002, Technometrics.

[238]  Dennis K. J. Lin,et al.  A Two-Stage Bayesian Model Selection Strategy for Supersaturated Designs , 2002, Technometrics.

[239]  Robert W. Mee,et al.  Better Foldover Fractions for Resolution III 2k-p Designs , 2002, Technometrics.

[240]  Heidi B. Goldfarb Experiments with Mixtures, 3rd Ed. , 2002 .

[241]  R. H. Myers,et al.  Fraction of Design Space to Assess Prediction Capability of Response Surface Designs , 2003 .

[242]  Heidi B. Goldfarb,et al.  Mixture-Process Variable Experiments with Noise Variables , 2003 .

[243]  J. Lawson One-Step Screening and Process Optimization Experiments , 2003 .

[244]  Connie M. Borror,et al.  Genetic Algorithms for the Construction of D-Optimal Designs , 2003 .

[245]  Douglas C. Montgomery,et al.  Analysis of Supersaturated Designs , 2003 .

[246]  William A. Brenneman,et al.  Robust Parameter Design with Categorical Noise Variables , 2003 .

[247]  John A. Nelder,et al.  Robust Design via Generalized Linear Models , 2003 .

[248]  J. Borkowski Using a Genetic Algorithm to Generate Small Exact Response Surface Designs , 2003 .

[249]  J. Borkowski A Comparison of Prediction Variance Criteria for Response Surface Designs , 2003 .

[250]  Connie M. Borror,et al.  Model-Robust Optimal Designs: A Genetic Algorithm Approach , 2004 .

[251]  N. Draper Response Surface Designs , 2006 .