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A failure process model with the exponential smoothing of intensity functions

Wu, Shaomin (2019) A failure process model with the exponential smoothing of intensity functions. European Journal of Operational Research, 275 (2). pp. 502-513. ISSN 0377-2217. (doi:10.1016/j.ejor.2018.11.045) (KAR id:70299)


This paper proposes a new model and investigates its special case model, both of which model the failure process of a series system composed of multiple components. We make the following assumption: (1) once the system fails, the failed component can be immediately identified and replaced with a new identical one, and (2) once the system fails, only the time of the failure is recorded; but the component that causes the system to fail is not known. The paper derives a parameter estimation method and compares the performance of the proposed models with nine other models on artificially generated data and fifteen real-world datasets. The results show that the two new models outperform the nine models in terms of the three most commonly used penalised model selection criteria, the Akaike's information criterion (AIC), corrected Akaike's information criterion (AICc) and Bayesian information criterion (BIC), respectively.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2018.11.045
Uncontrolled keywords: Maintenance, non-homogeneous Poisson process, superimposed renewal process, Akaike information criterion, higher order Markov process
Subjects: 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: 23 Nov 2018 08:02 UTC
Last Modified: 09 Dec 2022 05:51 UTC
Resource URI: (The current URI for this page, for reference purposes)

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