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 language | English |
|---|---|
| Pages (from-to) | 1159-1178 |
| Number of pages | 20 |
| Journal | Statistics |
| Volume | 51 |
| Issue number | 5 |
| DOIs | |
| State | Published - 3 Sep 2017 |
Bibliographical note
Funding Information:This work was supported by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology [No. 2009-0093827]. This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) [No. 2016R1A2B2014211].
Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Variables sampling plan
- generalized Polya process
- intensity function
- repairable item
- stochastic order