Enhancing product robustness in reliability-based design optimization

Xiaotian Zhuang, Rong Pan, Xiaoping Du

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example.

Original languageEnglish (US)
Pages (from-to)145-153
Number of pages9
JournalReliability Engineering and System Safety
StatePublished - Jun 2015


  • Kriging metamodel
  • Robust design
  • Sequential optimization and reliability assessment Sequential sampling
  • optimization

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


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