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Informative experimental design for electronic circuits
Author(s) -
Malik Zahid,
Su Hua,
Nelder John
Publication year - 1998
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/(sici)1099-1638(199805/06)14:3<177::aid-qre153>3.0.co;2-n
Subject(s) - set (abstract data type) , monte carlo method , computer science , design of experiments , selection (genetic algorithm) , electronic circuit , circuit design , algorithm , mathematical optimization , reliability engineering , industrial engineering , engineering , machine learning , mathematics , statistics , electrical engineering , embedded system , programming language
This paper presents the case against two widespread practices in designing engineering experiments, which are (i) to vary one factor at a time (the OFAT approach) and (ii) to generate experimental points by random selection (the Monte Carlo approach). These approaches do not produce good experimental designs, defined as generating maximum information per run (IPR), and should be replaced by designs that do. These latter designs (i) vary many factors at a time and (ii) use a patterned set of experimental points rather than a random set. An example from circuit design is used to illustrate this approach. The limitations of the random approach are well known amongst statisticians but often not among engineers. © 1998 John Wiley & Sons, Ltd.