We review major developments in the design of experiments, offer our thoughts on important directions for the future, and make specific recommendations for experimenters and statisticians who are students and teachers of experimental design, practitioners of experimental design, and researchers jointly exploring new frontiers. Specific topics covered are optimal design, computer-aided design, robust design, response surface design, mixture design, factorial design, block design, and designs for nonlinear models.

Experimental Design: Review and Comment

In this paper we describe the off-line quality control method and its application in optimizing the process for forming contact windows in 3.5-μm complementary metal-oxide semiconductor circuits. The offline quality control method is a systematic method of optimizing production processes and product designs. It is widely used in Japan to produce high-quality products at low cost. The key steps of off-line quality control are: (i) Identify important process factors that can be manipulated and their potential working levels; (ii) perform fractional factorial experiments on the process using orthogonal array designs; (iii) analyze the resulting data to determine the optimum operating levels of the factors (both the process mean and the process variance are considered in this analysis; (iv) conduct an additional experiment to verify that the new factor levels indeed improve the quality control.

Off-line quality control in integrated circuit fabrication using experimental design

Whenever the observations in an experimrnt must be made in somr time order sequence, there is a substantial likelihood that there may bc somo time order dcpendency in the results. In addition, it is frequently cxprnsivr to change levels for one or more of the factors in thr study. In this paper these two facts are documcntcd with personal case histories and a general method is proposed for taking these difficulties into consideration when planning an expcrimrnt. The method introduces Monte Carlo like techniques into the design of cxperimcnts.

Designing Experiments When Run Order is Important

Computer packages have long been available to aid in the analysis of data. Only recently has the value of the computer in the data collection phase been recognized. This recognition has led to a proliferation of programs for the design of experiments. I..

Tools for Computer-Aided Design of Experiments

The design of an experiment involves much more than deciding on a matrix of experimental points. This is demonstrated by six recent experiments, dealing with such diverse subjects as evaluating the reaction of birds to different noises, comparing computer programming methods, and optimizing a chemical reaction. These experiences and others are generalized in some basic guidelines for designing experiments. Some technical challenges and educational programs are also discussed.

Experimental Design in the Complex World

Practical considerations and constraints frequently lead to the abandonment of standard experimental designs and necessitate custom-tailoring the design to the given test situation. In such cases, especially, the investigator is interested in determining the properties of alternative, and sometimes unbalanced, test plans. A computer program, named EXPLOR, for evaluating and comparing the properties of proposed experimental designs has been developed for this purpose. EXPLOR may be used to:

A Computer Program for Evaluating and Comparing Experimental Designs and Some Applications

The analysis of variance is a technique for comparing treatment means or for estimating components of variation. The former is called fixed effects analysis of variance and the latter is called random effects analysis of variance. Many nonstatisticians ..

Some Differences Between Fixed, Mixed, and Random Effects Analysis of Variance Models

New Bias Evaluation Features of EXPLOR-A Program for Assessing Experimental Design Properties

Designed experiments are frequently used in industry to identify those process variables that most strongly affect product quantity and quality. Hahn, Meeker, and Feder [3] demonstrated that it is possible to learn many things about the adequacy of a pr..

Paul I. Feder

Papers

A Computer Program for Evaluating and Comparing Experimental Designs and Some Applications

Some Differences Between Fixed, Mixed, and Random Effects Analysis of Variance Models

New Bias Evaluation Features of EXPLOR-A Program for Assessing Experimental Design Properties

Evaluating the Effect of Incorrect Specification of a Regression Model