Maintenance optimization with duration-dependent costs

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 mit...

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Bibliographic Details
Published in:Annals of operations research Vol. 224; no. 1; pp. 1 - 23
Main Authors: Bohlin, Markus, Wärja, Mathias
Format: Journal Article
Language:English
Published: Boston Springer US 01.01.2015
Springer
Springer Nature B.V
Subjects:
Breakdown
Breakdowns
Business and Management
Combinatorics
Cost control
Costs
Economics
Engineering research
Gas pipelines
Gas turbines
Inclusions
Integer programming
Maintenance
Maintenance costs
Maintenance management
Mathematical optimization
Mathematical research
Operations research
Operations Research/Decision Theory
Optimization
Planning
Preventive maintenance
Stochastic analysis
Studies
Theory of Computation
Turbines
Water flooding
Working hours
Integer programming
Multi-unit maintenance
Maintenance optimization
ISSN:0254-5330, 1572-9338, 1572-9338
Online Access:Get full text
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Summary: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.
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ISSN:0254-5330
1572-9338
1572-9338
DOI:10.1007/s10479-012-1179-1