Tolerance allocation via simulation embedded sequential quadratic programming

Chiang Kao, Chang Chung Li, Shih Pin Chen

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Tolerance allocation is an important problem frequently encountered in the synthesis process, for designers as well as manufacturing engineers. Under the objective of minimizing the manufacturing cost while attaining an acceptable yield, the problem can be formulated as a stochastic program. Owing to the nonlinear nature of the stochastic program, a sequential quadratic programming algorithm is developed to solve the problem. The cumbersome multivariate integration in calculating the yield is approximated by a Monte Carlo simulation and the highly nonlinear yield constraint is supported by some auxiliary constraints. In limited experiments, the proposed method has performed efficiently and robustly. Compared with some previous studies, the designs solved in this paper have smaller manufacturing costs and higher yields, indicating that the proposed method is very promising in solving tolerance allocation problems.

Original languageEnglish
Pages (from-to)4345-4355
Number of pages11
JournalInternational Journal of Production Research
Issue number17
Publication statusPublished - 2000 Nov

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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