THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The purpose of this article is to provide a survey of the various stages in the development of response surface methodology RSM. The coverage of these stages is organized in three parts that describe the evolution of RSM since its introduction in the early 1950s. Part I covers the period, 1951-1975, during which the so-called classical RSM was developed. This includes a review of basic experimental designs for fitting linear response surface models, in addition to a description of methods for the determination of optimum operating conditions. Part II, which covers the period, 1976-1999, discusses more recent modeling techniques in RSM, in addition to a coverage of Taguchi's robust parameter design and its response surface alternative approach. Part III provides a coverage of further extensions and research directions in modern RSM. This includes discussions concerning response surface models with random effects, generalized linear models, and graphical techniques for comparing response surface designs. Copyright © 2010 John Wiley & Sons, Inc.

Response Surface Methodology.

Response surface methodology

Introduction to quality engineering : designing quality into products and processes

Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.

Introduction to quality engineering. designing quality into products a

A new method of construction of multi-level supersaturated designs

A class of composite designs for response surface methodology

Screening is the first stage of many industrial experiments and is used to determine efficiently and effectively a small number of potential factors among a large number of factors which may affect a particular response. In a recent paper, Jones and Nachtsheim [A class of three-level designs for definitive screening in the presence of second-order effects. J. Qual. Technol. 2011;43:1–15] have given a class of three-level designs for screening in the presence of second-order effects using a variant of the coordinate exchange algorithm as it was given by Meyer and Nachtsheim [The coordinate-exchange algorithm for constructing exact optimal experimental designs. Technometrics 1995;37:60–69]. Xiao et al. [Constructing definitive screening designs using conference matrices. J. Qual. Technol. 2012;44:2–8] have used conference matrices to construct definitive screening designs with good properties. In this paper, we propose a method for the construction of efficient three-level screening designs based on weighin...

Efficient three-level screening designs using weighing matrices

Wu and Ding (1991) have given a systematic method for constructing the response surface designs for qualitative and quantitative factors when all the quantitative factors are controllable. In most of the experiments all the quantitative factors are not controllable some of them are uncontrollable or noise factors. In this paper we have given a method for constructing designs involving qualitative and quantitative factors using the technique given by Wu and Ding (1991) when the quantitative factors are divided into controllable and uncontrollable factors. We have also applied dual response surface optimization technique given by Lin and Tu (1995) to find the optimal setting for a set of design variables involving qualitative and quantitative factors.

Robust response surface design for quantitative and qualitative factors

SYNOPTIC ABSTRACTDraper and John (1988) gave some specific response-surface designs for quantitative and qualitative factors. Wu and Ding (1998) gave a systematic method for constructing such designs. Aggarwal and Bansal (1998) gave robust response surface design for quantitative and qualitative factors using central composite designs. In this paper, we give a method for constructing robust response-surface designs for quantitative and qualitative factors using the small response-surface optimization approach given by Lin and Tu (1995) for finding the optimal setting for a set of design variables involving qualitative and quantitative factors.

M.L. Aggarwal

Papers

A new method of construction of multi-level supersaturated designs

A class of composite designs for response surface methodology

Efficient three-level screening designs using weighing matrices

Robust response surface design for quantitative and qualitative factors

Small robust response-surface designs for quantitative and qualitative factors