A partitioning method of experimental levels for low failure probability estimation problems

Kunling Song, Yugang Zhang, Xinshui Yu, Bifeng Song

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Failure boundaries are always far away from the center of the design space of variables for low failure probability problems. In order to make full use of samples, a partitioning method of experimental levels is proposed for improving general design of experiments in this paper. The method is implemented by non-uniformly partitioning experimental levels according to the probability density function of variables, which leads to a wide interval of adjacent experimental levels at the high probability density value, while a narrow one at the low. The translational propagation latin hypercube design was improved by using the non-uniformly partitioning experimental levels method. To validate the practicability and effectiveness of the proposed method, two numerical examples are presented and the results show that the improved translational propagation latin hypercube design is more effective than the previous.

Original languageEnglish
Title of host publication2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
PublisherIEEE Computer Society
Pages1387-1391
Number of pages5
ISBN (Electronic)9781509036653
DOIs
StatePublished - 27 Dec 2016
Event2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 - Bali, Indonesia
Duration: 4 Dec 20167 Dec 2016

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2016-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
Country/TerritoryIndonesia
CityBali
Period4/12/167/12/16

Keywords

  • density function
  • design of experiments
  • experimental levels
  • low failure probability

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