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Maintenance plan optimization for a train fleet
Swedish Institute of Computer Science, SICS.ORCID iD: 0000-0003-2234-1255
Swedish Institute of Computer Science, SICS.ORCID iD: 0000-0003-1597-6738
2010 (English)In: WIT Transactions on the Built Environment Volume 114, 2010, p. 349-358Conference paper, Published paper (Refereed)
Abstract [sv]

Maintenance planning is an important problem for railways, as well as other application domains that employ machinerywith expensive replacements and high downtime costs. In a previous paper, we have developed methods for efficiently finding optimized maintenance schedules for a single unit, and proposed that the maintenance plan should be continuously re-optimized based on the condition of components. However, fleet-level resources, such as the availability of expensive spare parts, have largely been ignored. In this paper, we extend our previous approach by proposing a solution for the fleet level maintenance scheduling problem with spare parts optimization. The new solution is based on a mixed integer linear programming formulation of the problem. We demonstrate the merits of our approach by optimizing instances of maintenance schedules based on maintenancedata from railway companies operating in Sweden.

Place, publisher, year, edition, pages
2010. p. 349-358
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-21314DOI: 10.2495/CR100331ISBN: 9781845644680 (print)OAI: oai:DiVA.org:mdh-21314DiVA, id: diva2:650368
Conference
12th International Conference on Computer System Design and Operation in the Railways and other Transit Systems, COMPRAIL 2010; Beijing; China; 31 August 2010 through 2 September 2010
Available from: 2013-09-20 Created: 2013-09-11 Last updated: 2014-09-15Bibliographically approved
In thesis
1. Applications of Optimization Methods in Industrial Maintenance Scheduling and Software Testing
Open this publication in new window or tab >>Applications of Optimization Methods in Industrial Maintenance Scheduling and Software Testing
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

As the world is getting more and more competitive, efficiency has become a bigger concern than ever for many businesses. Certain efficiency concerns can naturally be expressed as optimization problems, which is a well studied field in the academia. However, optimization algorithms are not as widely employed in industrial practice as they could. There are various reasons for the lack of widespread adoption. For example, it can be difficult or even impossible for non-experts to formulate a detailed mathematical model of the problem. On the other hand, a scientist usually does not have a deep enough understanding of critical business details, and may fail to capture enough details of the real- world phenomenon of concern. While a model at an arbitrary abstraction level is often good enough to demonstrate the optimization approach, ignoring relevant aspects can easily render the solution impractical for the industry. This is an important problem, because applicability concerns hinder the possible gains that can be achieved by using the academic knowledge in industrial practice. In this thesis, we study the challenges of industrial optimization problems in the form of four case studies at four different companies, in the domains of maintenance schedule optimization and search-based software testing. Working with multiple case studies in different domains allows us to better understand the possible gains and practical challenges in applying optimization methods in an industrial setting. Often there is a need to trade precision for applicability, which is typically very context dependent. Therefore, we compare our results against base values, e.g., results from simpler algorithms or the state of the practice in the given context, where applicable. Even though we cannot claim that optimization methods are applicable in all situations, our work serves as an empirical evidence for the usability of optimization methods for improvements in different industrial contexts. We hope that our work can encourage the adoption of optimization techniques by more industrial practitioners.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2014
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 180
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-25944 (URN)978-91-7485-163-2 (ISBN)
Presentation
2014-10-14, R3-131, Mälardalens högskola, Västerås, 13:30 (English)
Opponent
Supervisors
Available from: 2014-09-15 Created: 2014-09-14 Last updated: 2018-01-11Bibliographically approved

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Doganay, KivancBohlin, Markus

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Citation style
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