Reliability sampling plan for repairable items following general failure process and its statistical analysis

Hyunju Lee, Ji Hwan Cha

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Acceptance sampling plan has become an essential tool in the statistical quality control. Traditionally, most acceptance sampling plans have been developed for non-repairable items. Recently in Cha [Variables acceptance reliability sampling plan for repairable items. Statistics. 2015;49:1141–1156], variables acceptance reliability sampling plan for repairable items has been developed assuming that the failure process follows the non-homogeneous Poisson process (NHPP). In this paper, we assume that the failure process follows a new counting process which is a generalized version of the NHPP. Furthermore, it is shown that the developed sampling plan improves the reliability characteristic of the population of items which have passed the testing procedure. An illustrative example is also provided.

Original languageEnglish
Pages (from-to)1159-1178
Number of pages20
JournalStatistics
Volume51
Issue number5
DOIs
StatePublished - 3 Sep 2017

Keywords

  • Variables sampling plan
  • generalized Polya process
  • intensity function
  • repairable item
  • stochastic order

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