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A hybrid simulation-based optimization framework for supporting strategic maintenance to improve production performance
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0001-8188-7288
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0003-0111-1776
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0002-0880-2572
2020 (engelsk)Inngår i: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 281, nr 2, s. 402-414Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Managing maintenance and its impact on business results is increasingly complex, calling for more advanced operational research methodologies to address the challenge of sustainable decision-making. This problem-based research has identified a framework of methods to supplement the operations research/management science literature by contributing a hybrid simulation-based optimization framework (HSBOF), extending previously reported research.

Overall, it is the application of multi-objective optimization (MOO) with system dynamics (SD) and discrete-event simulation (DES) respectively which allows maintenance activities to be pinpointed in the production system based on analyzes generating less reactive work load on the maintenance organization. Therefore, the application of the HSBOF informs practice by a multiphase process, where each phase builds knowledge, starting with exploring feedback behaviors to why certain near-optimal maintenance behaviors arise, forming the basis of potential performance improvements, subsequently optimized using DES+MOO in a standard software, prioritizing the sequence of improvements in the production system for maintenance to implement.

Studying literature on related hybridizations using optimization the proposed work can be considered novel, being based on SD+MOO industrial cases and their application to a DES+MOO software.

sted, utgiver, år, opplag, sider
Elsevier, 2020. Vol. 281, nr 2, s. 402-414
Emneord [en]
Problem structuring, Decision support, System dynamics, Multi-objective optimization, Discrete-event simulation
HSV kategori
Forskningsprogram
Produktion och automatiseringsteknik
Identifikatorer
URN: urn:nbn:se:his:diva-15064DOI: 10.1016/j.ejor.2019.08.036ISI: 000497593000012Scopus ID: 2-s2.0-85071569509OAI: oai:DiVA.org:his-15064DiVA, id: diva2:1198165
Tilgjengelig fra: 2018-04-16 Laget: 2018-04-16 Sist oppdatert: 2019-12-06bibliografisk kontrollert
Inngår i avhandling
1. Towards strategic development of maintenance and its effects on production performance: A hybrid simulation-based optimization framework
Åpne denne publikasjonen i ny fane eller vindu >>Towards strategic development of maintenance and its effects on production performance: A hybrid simulation-based optimization framework
2018 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Skövde: University of Skövde, 2018. s. 226
Serie
Dissertation Series ; 21
Emneord
Strategic development, maintenance behavior, maintenance management, sustainable change, tradeoff optimization, system dynamics, discrete event simulation, problem structuring, multi-objective optimization, decision support
HSV kategori
Forskningsprogram
Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-15036 (URN)978-91-984187-3-6 (ISBN)
Disputas
2018-04-23, Insikten, Kanikegränd 3A, Skövde, 13:15 (engelsk)
Opponent
Veileder
Prosjekter
IPSI Research School
Tilgjengelig fra: 2018-04-16 Laget: 2018-04-12 Sist oppdatert: 2018-04-16bibliografisk kontrollert

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