An information management paradigm for statistical experiments

Abstract

Optimization of engineering processes and products via statistical design of experiments is an approach well known to statisticians but still not popularly used by technical personnel. This paper sets out a pattern of reasoning that would facilitate the appreciation, on the part of non-mathematicians, of the principles and advantages of using statistical experimental design for process and product modeling and optimization. Use is made of the concepts of information transformation and conservation in a language that is familiar to those of purely technical background, leading to better understanding, acceptance and application of the efficiency and effectiveness of statistical experiments. In today's environment of the prevalence of software and hardware for statistical analysis, engineers concerned with quality and reliability would particularly benefit from such a paradigm for process and product performance improvement. Copyright © 2009 John Wiley & Sons, Ltd.