A review of robust design methods for multiple responses

Terrence E. Murphy, Kwok Leung Tsui, Janet K. Allen

Research output: Contribution to journalReview articlepeer-review

68 Scopus citations


Problems in engineering design often involve determining design variable settings to optimize individual product performance for multiple criteria, which are often in conflict. We review mathematically rigorous techniques from the statistical literature for finding a vector x of design variable settings, which produces an optimal compromise solution among a group of prioritized response variables. The best compromise solution is typically gained by optimizing an objective function, which incorporates the prioritized demands of multiple responses. Since most multi-response objective functions are constructed by combining the functions used to optimize univariate responses, a review of the prominent univariate approaches is presented first. A multivariate approach from the engineering literature called the compromise Decision Support Problem is also reviewed. Finally a table comparing the relative merits of the different multivariate approaches summarizes the article in a concise and user-friendly fashion.

Original languageEnglish (US)
Pages (from-to)118-132
Number of pages15
JournalResearch in Engineering Design
Issue number3
StatePublished - Dec 2005

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Architecture
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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