Optimal design for multifactor life testing experiments for exponentially distributed lifetimes

Brandon R. Englert, Steven E. Rigdon, Connie M. Borror, Douglas Montgomery, Rong Pan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Life testing experiments differ from most experiments in a number of ways. Instead of assuming a normal distribution for the response, we often assume a distribution such as the exponential or Weibull. Also, censoring, the termination of a life test before all units have failed, is common in life testing experiments. We investigate algorithms to obtain optimal, or near-optimal designs for multifactor experiments assuming an exponential distribution for the lifetimes.

Original languageEnglish (US)
Title of host publicationFrontiers in Statistical Quality Control 10
PublisherKluwer Academic Publishers
Pages303-317
Number of pages15
DOIs
StatePublished - 2012
Event2010 10th International Workshop on Intelligent Statistical Quality Control - Seattle, WA, United States
Duration: Aug 18 2010Aug 20 2010

Other

Other2010 10th International Workshop on Intelligent Statistical Quality Control
CountryUnited States
CitySeattle, WA
Period8/18/108/20/10

Keywords

  • A-optimality
  • Bayesian optimal design
  • D-optimality
  • Genetic algorithm

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Englert, B. R., Rigdon, S. E., Borror, C. M., Montgomery, D., & Pan, R. (2012). Optimal design for multifactor life testing experiments for exponentially distributed lifetimes. In Frontiers in Statistical Quality Control 10 (pp. 303-317). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-7908-2846-7-20