2022 Fiscal Year Annual Research Report
Non-parametric Bayesian approach to modelling system reliability
Project/Area Number |
18K04621
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Research Institution | Waseda University |
Principal Investigator |
早川 有 早稲田大学, 国際学術院, 教授 (80398916)
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Project Period (FY) |
2018-04-01 – 2023-03-31
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Keywords | System reliability / Bayesian non-parametrics / Gammpa process / Bathtub hazard rate / Warranty analysis / Geometric-like process / Alpha-Series process |
Outline of Annual Research Achievements |
Richard Arnold, Stefanka Chukova (both from Victoria University of Wellington) and Yu Hayakawa have carried out a foundational work on modelling system from a Bayesian non-parametric perspective. Hazard rate functions of natural and manufactured systems often show a bathtub shaped failure rate. Parametric modelling of such hazard rate functions can lead to unnecessarily restrictive assumptions on the function shape, however the most common non-parametric estimator (the Kaplan-Meier estimator) does not allow specification of the requirement that it be bathtub shaped. We have extended Lo and Weng (1989) approach and specified four non-parametric bathtub hazard rate functions drawn from Gamma Process Priors. We use a gamma-scaled Diriclet Process prior to implement the Gamma Process Prior and demonstrate simulation for these four models. We and our colleague Sarah Marshall (from Auckland University of Technology) also worked on other project on geometric-like processes with their applications such as the alternating alpha-series process. This project is complementary to our original goals. Sarah Marshall presented a paper on the alternating alpha series process at the 10th Asia-Pacific International Symposium on Advanced Reliability and Maintenance (APARM 2022). Also, a paper on modelling warranty claims for ageing repairable systems at 2023 Mathematical Modelling and Analytics Summer Symposium was presented by Sarah Marshall.
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Research Products
(4 results)