Premium
Strategies for planning experiments using orthogonal arrays and confounding tables
Author(s) -
Tsui KwokLeung
Publication year - 1988
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.4680040206
Subject(s) - taguchi methods , confounding , design of experiments , orthogonal array , set (abstract data type) , computer science , representation (politics) , process (computing) , quality (philosophy) , industrial engineering , engineering , data mining , machine learning , statistics , mathematics , philosophy , epistemology , politics , political science , law , programming language , operating system
Genichi Taguchi has popularized a robust design method which employs experimental design techniques to help identify the levels of design factors to improve the quality of products and manufacturing processes. Experimental design techniques are extremely effective for identifying improved factor levels in problems that involve a large number of factors. Taguchi's success in getting engineers to use experimental design techniques is due, at least in large part, to his use of tools and techniques that simplify the experiment planning process. Recognizing the advantages of this approach, this paper proposes a new set of tools, confounding tables, which offer more guidance to experimenters. Confounding tables provide a clear and systematic representation of confounding relationships. They are simple and useful tools for constructing experiment plans, and they enable users easily to evaluate the confounding patterns of a completed plan. We show how confounding tables provide more information than Taguchi's linear graphs, and are useful for a large class of experiment plans.