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

Statistics for Spatial Data.

https://homepages.fhv.at/hgb/New-Papers/CMAME07_BS07b.pdf

Robust Optimization - A Comprehensive Survey

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

Robust design has been developed with the expectation that an insensitive design can be obtained. That is, a product designed by robust design should be insensitive to external noises or tolerances. An insensitive design has more probability to obtain a target value, although there are uncertain noises. Theories of robust design have been developed by adopting the theories of other fields. Based on the theories, robust design can be classified into three methods: 1) the Taguchi method, 2) robust optimization, and 3) robust design with the axiomatic approach. Each method is reviewed and investigated. The methods are examined from a theoretical viewpoint and are discussed from an application viewpoint. The advantages and drawbacks of each method are discussed, and future directions for development are proposed.

Robust Design: An Overview

A sampling technique enhancing accuracy and efficiency of metamodel-based RBDO: Constraint boundary sampling

The manufacturing tolerance of the permanent magnets (PMs) is inherent in the produce of the machine. These tolerances influence back electromotive force (EMF), which is an important response of the motor. In order to enhance the quality of the product, the authors need to reduce these tolerances, but it is very difficult and involves a number of costs. Therefore, this study presents a robust design of the EMF characteristic analysis considering the manufacturing tolerances of PM in the interior PM synchronous motor (IPMSM). Among the robust optimisation method, Taguchi robust design based on orthogonal array was applied. Finally, the validity of the analysis result is verified by comparing the optimum design model with present design model (mass production model) ones.

Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

Tae Hee Lee

Papers

Robust Design: An Overview

A sampling technique enhancing accuracy and efficiency of metamodel-based RBDO: Constraint boundary sampling

Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design

Kriging interpolation methods in geostatistics and DACE model

Watts-level road-compatible piezoelectric energy harvester for a self-powered temperature monitoring system on an actual roadway