Probabilistic sequential methodology for designing a factorial system with multiple responses

I. Ben-Gal, D. Braha, O. Z. Maimon

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This paper addresses the problem of optimizing a factorial system with multiple responses. A heuristic termed probabilistic sequential methodology (PSM) is proposed. The PSM identifies those designs that maximize the likelihood of satisfying a given set of functional requirements. It is based on sequential experimentation, statistical inference and a probabilistic local search. The PSM comprises three main steps: (1) screening and estimating the main location and dispersion effects by applying fractional factorial experiments (FFE) techniques; (2) based on these effects, establishing probabilistic measures for different combinations of factorlevels; and (3) constructing a set of candidate designs from which the best solution is selected by applying a heuristic local search. The PSM is attractive when the exact analytic relationship between factor-level combinations and the system's responses is unknown; when the system involves qualitative factors; and when the number of experiments is limited. The PSM is illustrated by a detailed case study of a Flexible Manufacturing Cell (FMC) design.

Original languageEnglish
Pages (from-to)2703-2724
Number of pages22
JournalInternational Journal of Production Research
Volume37
Issue number12
DOIs
StatePublished - 1 Jan 1999

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