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Reliability assessment of discrete-time k/n (G) retrial system based on different failure types and the δ-shock model

Hu, Zebin, Hu, Linmin, Wu, Shaomin, Yu, Xiaoyun (2024) Reliability assessment of discrete-time k/n (G) retrial system based on different failure types and the δ-shock model. Reliability Engineering and System Safety, 251 . Article Number 110371. ISSN 0951-8320. (doi:10.1016/j.ress.2024.110371) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:106652)

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Official URL:
https://doi.org/10.1016/j.ress.2024.110371

Abstract

The k/n (G) system is a typical reliability system in engineering practice. However, research on this system under discrete-time and retrial conditions is still limited. This paper establishes a k/n (G) retrial system model under a discrete-time condition based on different failure types and the δ-shock model, whose objective is to investigate its various reliability measures and the relationship between measures and parameters. Two methodologies are utilized in this paper to evaluate the system’s various measures: the analytical method for the discrete-time Markov process and the Monte Carlo simulation method. The two methodologies are compared, and optimization is performed on certain measures concerning system parameters. A discrete PH distribution representation method for component lifetime under the δ-shock is presented, the relationship between various reliability measures of the system and various parameters is determined, and a novel approach for system reliability research based on the discrete PH distribution and the δ-shock is provided in this paper.

Item Type: Article
DOI/Identification number: 10.1016/j.ress.2024.110371
Uncontrolled keywords: discrete time; PH distributionδ-shock; different failure types, retrial
Subjects: H Social Sciences
H Social Sciences > HA Statistics
H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 22 Jul 2024 07:18 UTC
Last Modified: 29 Jul 2024 13:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/106652 (The current URI for this page, for reference purposes)

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