UNCERTAINTY ANALYSIS FOR A PERIODIC REPLACEMENT PROBLEM WITH MINIMAL REPAIR: PARAMETRIC BOOTSTRAPPING APPROACH

Authors

  • Yasuhiro Saito
  • Tadashi Dohi
  • Wonyoung Yun

DOI:

https://doi.org/10.23055/ijietap.2014.21.6.1253

Keywords:

statistical estimation, parametric bootstrapping method, periodic replacement problem, minimal repair, non-homogeneous Poisson process

Abstract

In this paper we consider a statistical estimation problem for a periodic replacement problem with minimal repair which is one of the mostfundamental maintenance models in practice, and proposetwo parametric bootstrapping methods which are categorizedinto the simulation-based approach and re-sampling-basedapproach, respectively. Especially, we concern two data analysis techniques: direct data analysis of the minimalrepair data which obeys a non-homogeneous Poisson process and indirect data analysis after data transformation to a homogeneous Poisson process. Through simulationexperiments, we investigate statistical features of the proposedparametric bootstrapping methods. Also, we analyze the realminimal repair data to demonstrate the proposedmethods in practice.

Author Biography

Yasuhiro Saito

Published

2014-10-20

How to Cite

Saito, Y., Dohi, T., & Yun, W. (2014). UNCERTAINTY ANALYSIS FOR A PERIODIC REPLACEMENT PROBLEM WITH MINIMAL REPAIR: PARAMETRIC BOOTSTRAPPING APPROACH. International Journal of Industrial Engineering: Theory, Applications and Practice, 21(6). https://doi.org/10.23055/ijietap.2014.21.6.1253

Issue

Section

Special Issue: 2013 IJIE Conference at Busan, Korea