Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

The signal model : a model for competing risks of opportunistic maintenance

Bedford, Tim and Dewan, Isha and Meilijson, Isaac and Zitrou, Athena (2011) The signal model : a model for competing risks of opportunistic maintenance. European Journal of Operational Research, 214 (3). pp. 665-673. ISSN 0377-2217

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

This paper presents a competing risks reliability model for a system that releases signals each time its condition deteriorates. The released signals are used to inform opportunistic maintenance. The model provides a framework for the determination of the underlying system lifetime from right-censored data, without requiring explicit assumptions about the type of censoring to be made. The parameters of the model are estimated from observational data by using maximum likelihood estimation. We illustrate the estimation process through a simulation study. The proposed signal model can be used to support decision-making in optimising preventive maintenance: at a component level, estimates of the underlying failure distribution can be used to identify the critical signal that would trigger maintenance of the individual component; at a multi-component system level, accurate estimates of the component underlying lifetimes are important when making general maintenance decisions. The benefit of good estimation from censored data, when adequate knowledge about the dependence structure is not available, may justify the additional data collection cost in cases where full signal data is not available.

Item type: Article
ID code: 33568
Keywords: reliability, maintenance, competing risks, statistical inference, Management. Industrial Management, Modelling and Simulation, Management Science and Operations Research, Information Systems and Management
Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Department: Strathclyde Business School > Management Science
Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 22 Sep 2011 09:57
    Last modified: 11 Apr 2014 08:21
    URI: http://strathprints.strath.ac.uk/id/eprint/33568

    Actions (login required)

    View Item