Investigating the necessity of acceleration in a degradation test

Lanqing Hong, Zhisheng Ye, Xingqiu Zhao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

When using acceleration in a degradation test, additional parameters are needed to incorporate the accelerating variables into the degradation process, requiring more statistical information to achieve the same level of estimation precision. When the increase of statistical information due to acceleration fails to compensate the information consumption caused by the additional parameters, acceleration is statistically inefficient. This paper identifies situations where acceleration is unnecessary in a degradation test when common stochastic process models are used, including the Wiener, gamma and inverse Gaussian (IG) processes. An acceleration relation index is introduced to unify different kinds of acceleration relations. It is shown that when this acceleration relation index is greater or equal to one, acceleration is always unnecessary. Otherwise, the necessity of acceleration depends on values of the model parameters and the acceleration relation index. The procedure to identify the necessity of acceleration is illustrated by a numerical example.
Original languageEnglish
Title of host publication2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
PublisherIEEE Computer Society
Pages546-550
Number of pages5
Volume2016-December
ISBN (Electronic)9781509036653
DOIs
Publication statusPublished - 27 Dec 2016
Event2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 - Bali, Indonesia
Duration: 4 Dec 20167 Dec 2016

Conference

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

Keywords

  • Acceleration Relation Index
  • Degradation Tests
  • Necessity of Acceleration
  • Stochastic Process Models

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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