Comparison of optimal accelerated life tests with competing risks model under exponential distribution

Tsai Hung Fan, Yi Fu Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Accelerated life testing (ALT) is the process of testing products by subjecting them to strict conditions in order to observe more failure data in a short time period. In this study, we compare the methods of two-level constant-stress ALT (CSALT) and simple step-stress ALT (SSALT) based on competing risks of two or more failure modes with independent exponential lifetime distributions. Optimal sample size allocation during CSALT and the optimal stress change-time in SSALT are considered based on V- and D-optimality, respectively. Under Type-I censoring, numerical results show that the optimal SSALT outperforms the optimal CSALT in a wide variety of settings. We theoretically also show that the optimal SSALT is better than the optimal CSALT under a set of conditions. A real data example is analyzed to demonstrate the performance of the optimal plans for both ALTs.

Original languageEnglish
Pages (from-to)902-919
Number of pages18
JournalQuality and Reliability Engineering International
Volume37
Issue number3
DOIs
StatePublished - Apr 2021

Keywords

  • competing risks
  • constant-stress ALT
  • optimal design
  • step-stress ALT
  • Type-I censoring

Fingerprint

Dive into the research topics of 'Comparison of optimal accelerated life tests with competing risks model under exponential distribution'. Together they form a unique fingerprint.

Cite this