A random maintenance scheduling model to reduce fault diagnosis time

Pritibhushan Sinha ()

Annals of Operations Research, 2012, vol. 201, issue 1, 447 pages

Abstract: We present a random model for a situation in which some tests of fault detection are to be scheduled to diagnose what type of fault, out of some possible types of faults, has occurred. There are two variants of the model. In the first, the objective is average total diagnosis time. In the second, the objective is a linear combination of average and standard deviation of the diagnosis time, where standard deviation is multiplied with a positive weight. We give an exact solution method for the first case and a heuristic method for the second. A numerical experiment with randomly generated instances is done for the heuristic method. The methods appear to be suitable for practical applications. Copyright Springer Science+Business Media, LLC 2012

Keywords: Fault detection; Scheduling; Random model; Solution method (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s10479-012-1180-8 (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:201:y:2012:i:1:p:441-447:10.1007/s10479-012-1180-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-012-1180-8

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 ().