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Justifying Maintenance Studying System Behavior: A Multipurpose Approach Using Multi-objective Optimization
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-8188-7288
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-0880-2572
2017 (English)In: 35th International Conference of the System Dynamics Society 2017: Cambridge, Massachusetts, USA 16 - 20 July 2017 / [ed] J. Sterman, N. Repenning, Curran Associates, Inc., 2017, Vol. 2, p. 1061-1081Conference paper, Published paper (Refereed)
Abstract [en]

Industrial maintenance includes rich internaldynamic complexity on how to deliver value. While the technical development hasprovided with applicable solutions in terms of reliability and condition basedmonitoring, managing maintenance is still an act of balancing, trying to pleasethe short-termism from the economic requirements and simultaneously address thenecessity of strategic and long-term thinking. By presenting an analysis tojustify maintenance studying system behavior, this paper exemplifies thecontribution of the combined approach of a system dynamics maintenanceperformance model and multi-objective optimization. The paper reveals howinsights from the investigation, of the near optimal Pareto-front solutions inthe objective space, can be drawn using visualization of performance ofselected parameters. According to our analysis, there is no return back to thesingle use of system dynamics; the contribution to the analysis of exploringsystem behavior, from applying multi-objective optimization, is extensive.However, for the practical application, the combined approach is not areplacement – but a complement. Where the interpretation of the visualizedPareto-fronts strongly benefits from the understanding of the model dynamics, inwhich important nonlinearities and delays can be revealed, and thus facilitateon the selected strategical path for implementation.

Place, publisher, year, edition, pages
Curran Associates, Inc., 2017. Vol. 2, p. 1061-1081
Keywords [en]
maintenance performance, strategic development, system dynamics, simulation, multi-objective optimization
National Category
Production Engineering, Human Work Science and Ergonomics Reliability and Maintenance
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-14707ISBN: 9781510851078 (print)OAI: oai:DiVA.org:his-14707DiVA, id: diva2:1179457
Conference
35th International Conference of the System Dynamics Society, Cambridge, Massachusetts, USA, July 16-20, 2017
Available from: 2018-02-01 Created: 2018-02-01 Last updated: 2018-05-23Bibliographically approved
In thesis
1. Towards strategic development of maintenance and its effects on production performance: A hybrid simulation-based optimization framework
Open this publication in new window or tab >>Towards strategic development of maintenance and its effects on production performance: A hybrid simulation-based optimization framework
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Managing maintenance in manufacturing within an economical short-termism framework and taking the consequential long-term cost effects into account is hard. The increasing complexity of managing maintenance and its impact on the business results calls for more advanced methods to support long-term development through effective activities in the production system environment. This problem-based design science research has evolved into the novel concept of a hybrid simulation-based optimization (SBO) framework which integrates multi-objective optimization (MOO) with system dynamics (SD) and discrete-event simulation (DES) respectively. The objective is to support managers in their decision-making on the strategic and operational levels for prioritizing activities to develop maintenance and production performance.

To exemplify the hybrid SBO framework this research presents an SD model for the study of the dynamic behaviors of maintenance performance and costs, which aims to illuminate insights for the support of the long-term strategic development of maintenance practices. The model promotes a system view of maintenance costs that includes the dynamic consequential costs as the combined result of several interacting maintenance levels throughout the constituent feedback structures. These levels range from the applied combination of maintenance methodologies to the resulting proactiveness in production, such as the ratio between planned and unplanned downtime, in continuous change based on the rate of improvements arising from root-cause analyses of breakdowns. The model creation and validation process have been supported by two large maintenance organizations operating in the Swedish automotive industry. Experimental results show that intended changes can have both short-term and longterm consequences, and that the system may show both obvious and hidden dynamic behavioral effects.

The application of MOO distinguishes this work from previous research efforts that have mixed SD and DES. It presents a unique methodology to support more quantitative and objective-driven decision making in maintenance management, in which the outcome of an SD+MOO strategy selection process forms the basis for performance improvements on the operations level. This is achieved by framing the potential gains in operations in the DES+MOO study, as a result of the applied strategy in the SD model. All in all, this hybrid SBO framework allows pinpointing maintenance activities based on the analysis of the feedback behavior that generates less reactive load on the maintenance organization.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2018. p. 226
Series
Dissertation Series ; 21
Keywords
Strategic development, maintenance behavior, maintenance management, sustainable change, tradeoff optimization, system dynamics, discrete event simulation, problem structuring, multi-objective optimization, decision support
National Category
Reliability and Maintenance Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15036 (URN)978-91-984187-3-6 (ISBN)
Public defence
2018-04-23, Insikten, Kanikegränd 3A, Skövde, 13:15 (English)
Opponent
Supervisors
Projects
IPSI Research School
Available from: 2018-04-16 Created: 2018-04-12 Last updated: 2018-04-16Bibliographically approved

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Linnéusson, GaryNg, Amos H. C.Aslam, Tehseen

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