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Maintenance optimization with duration-dependent costs
Swedish Institute of Computer Science, Sweden. (IS)ORCID iD: 0000-0003-1597-6738
Siemens Industrial Turbomachinery AB, Sweden.
2015 (English)In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 224, no 1, p. 1-23Article in journal (Refereed) Published
Abstract [en]

High levels of availability and reliability are essential in many industries where production is subject to high costs due to downtime. Examples include the mechanical drive in natural gas pipelines and power generation on oil platforms, where gas turbines are commonly used as a power source. To mitigate the effects of service outages and increase overall reliability, it is also possible to use one or more redundant units serving as cold standby backup units. In this paper, we consider preventive maintenance optimization for parallel k-out-of-n multi-unit systems, where production at a reduced level is possible when some of the units are still operational. In such systems, there are both positive and negative effects of grouping activities together. The positive effects come from parallel execution of maintenance activities and shared setup costs, while the negative effects come from the limited number of units which can be maintained at the same time. To show the possible economic effects, we evaluate the approach on models of two production environments under a no-fault assumption. We conclude that savings were substantial in our experiments on preventive maintenance, compared to a traditional preventive maintenance plan. For single-unit systems, costs were on average 39 % lower when using optimization. For multi-unit systems, average savings were 19 %. We also used the optimization models to evaluate the effects of re-planning at breakdown and effects due to modeling of inclusion relations. Breakdown re-planning saved between 0 and 11 % of the maintenance costs, depending on which component failed, while inclusion relation modeling resulted in an 7 % average cost reduction.

Place, publisher, year, edition, pages
2015. Vol. 224, no 1, p. 1-23
National Category
Engineering and Technology Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-17452DOI: 10.1007/s10479-012-1179-1Scopus ID: 2-s2.0-84863222844OAI: oai:DiVA.org:mdh-17452DiVA, id: diva2:579783
Funder
VINNOVA, P32551-1Available from: 2012-12-20 Created: 2012-12-20 Last updated: 2018-01-11Bibliographically approved

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Bohlin, Markus

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CiteExportLink to record
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