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Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study
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. Jönköping University, Sweden. (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
2018 (engelsk)Inngår i: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, s. 1293-1298Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Identifying sustainable strategies to develop maintenance performance within the short-termism framework is indeed challenging. It requires reinforcing long-term capabilities while managing short-term requirements. This study explores differently applied time horizons when optimizing the tradeoff between conflicting objectives, in maintenance performance, which are: maximize availability, minimize maintenance costs, and minimize maintenance consequence costs. The study has applied multi-objective optimization on a maintenance performance system dynamics model that contains feedback structures that explains reactive and proactive maintenance behavior on a general level. The quantified results provide insights on how different time frames are conditional to enable more or less proactive maintenance behavior in servicing production.

sted, utgiver, år, opplag, sider
Elsevier, 2018. Vol. 72, s. 1293-1298
Emneord [en]
strategic development, maintenance performance, proactive maintenance, multi-objective optimization, system dynamics, simulation
HSV kategori
Forskningsprogram
Produktion och automatiseringsteknik
Identifikatorer
URN: urn:nbn:se:his:diva-15066DOI: 10.1016/j.procir.2018.03.219ISI: 000526120800218Scopus ID: 2-s2.0-85049594037OAI: oai:DiVA.org:his-15066DiVA, id: diva2:1198167
Konferanse
51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018
Forskningsfinansiär
Knowledge Foundation
Merknad

CC BY-NC-ND 4.0

Edited by Lihui Wang

This work was partially financed by Knowledge Foundation (KKS), Sweden, through the IPSI Research School. The authors gratefully acknowledge their provision of the research funding and the support of industrial partners, including Volvo Car Corporation and Volvo Group Trucks Operations.

Tilgjengelig fra: 2018-04-16 Laget: 2018-04-16 Sist oppdatert: 2022-07-15bibliografisk 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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