Training and repair policies for stand-by systems
Yeek-Hyun Kim and
Lyn Thomas ()
Annals of Operations Research, 2013, vol. 208, issue 1, 469-487
Abstract:
This research is concerned with developing repair and training strategies for stand-by equipment which maximise the time until the equipment is unable to respond when it is needed. Equipment can only be used if it is in an operable state and the users have had sufficient recent training on it. Thus it is necessary to decide when to maintain/repair the equipment and when to use the equipment for training. Both actions mean the equipment is not readily available for use in an emergency. We develop discrete time Markov decision process formulations of this problem in order to investigate the form of the optimal policies which maximise the expected survival time until a catastrophic event when an emergency occurs and the equipment cannot respond. We also calculate the solution in a number of numerical examples. Copyright Springer Science+Business Media, LLC 2013
Keywords: Maintenance and repair; Training action; Markov decision processes; Stand-by equipment (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1007/s10479-012-1185-3 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:208:y:2013:i:1:p:469-487:10.1007/s10479-012-1185-3
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1007/s10479-012-1185-3
Access Statistics for this article
Annals of Operations Research is currently edited by Endre Boros
More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().