A new warranty policy for heterogeneous items subject to monotone degradation processes

Author:

Cha Ji Hwan1ORCID,Finkelstein Maxim23ORCID

Affiliation:

1. Department of Statistics, Ewha Womans University, Seoul, Republic of Korea

2. Department of Mathematical Statistics, University of the Free State, Bloemfontein, South Africa

3. ITMO University, Petersburg, Russia

Abstract

A new renewable warranty policy is suggested that increases the probability of its success and can decrease the corresponding costs for certain ranges of parameters. It deals with heterogeneous populations of items from two subpopulations (‘weak’ and ‘strong’) and is aimed at elimination and further replacement of weak items after screening at some optimal time. This elimination is performed when degradation described by the corresponding mixed degradation process reaches some optimally predetermined level. Probabilistic and cost analyses of the model are performed and the illustrative example is presented. It is shown that the proposed warranty policy with inspection outperforms the conventional one in a probabilistic sense. Furthermore, the proposed policy becomes economically beneficial especially when the additional penalty cost caused by a sudden failure is large.

Funder

national research foundation of korea

Publisher

SAGE Publications

Subject

Safety, Risk, Reliability and Quality

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Non-renewable warranty cost analysis for dependent series configuration with distinct warranty periods;Reliability Engineering & System Safety;2024-06

2. Delay time model for determining the effectiveness of a system under adverse conditions of production and inspection;Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;2023-12-04

3. Imperfect maintenance policies for warranted products under stochastic performance degradation;European Journal of Operational Research;2023-07

4. Acceptance reliability sampling plan for items from heterogeneous populations;Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;2022-08-11

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