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Towards strategic development of maintenance and its effects on production performance: A hybrid simulation-based optimization framework
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
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 [en]
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: urn:nbn:se:his:diva-15036ISBN: 978-91-984187-3-6 (print)OAI: oai:DiVA.org:his-15036DiVA, id: diva2:1197136
Public defence
2018-04-23, Insikten, Kanikegränd 3A, Skövde, 13:15 (English)
Opponent
Supervisors
Projects
IPSI Research SchoolAvailable from: 2018-04-16 Created: 2018-04-12 Last updated: 2018-04-16Bibliographically approved
List of papers
1. Towards strategic development of maintenance and its effects on production performance by using system dynamics in the automotive industry
Open this publication in new window or tab >>Towards strategic development of maintenance and its effects on production performance by using system dynamics in the automotive industry
2018 (English)In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 200, p. 151-169Article in journal (Refereed) Published
Abstract [en]

Managing maintenance within an economical short-termism framework, without considering the consequential long-term cost effect, is very common in industry. This research presents a novel conceptual system dynamics 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 manufacturing maintenance. By novel, we claim the model promotes a system's view of maintenance costs that include its dynamic consequential costs as the combined result of several interacting maintenance levels throughout the constituent feedback structures. These range from the applied combination of maintenance methodologies to the resulting proactiveness in production, which is based on the rate of continuous improvements arising from the root cause analyses of breakdowns. The purpose of using system dynamics is to support the investigations of the causal relationships between strategic initiatives and performance results, and to enable analyses that take into consideration the time delays between different actions, in order to support the sound formulation of policies to develop maintenance and production performances. The model construction and validation process has been supported by two large maintenance organizations operating in the Swedish automotive industry. Experimental results show that intended changes can have both short and long-term consequences, and that obvious and hidden dynamic behavioral effects, which have not been reported in the literature previously, may be in the system. We believe the model can help to illuminate the holistic value of maintenance on the one hand and support its strategic development as well as the organizational transformation into proactiveness on the other.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Maintenance performance, Strategic development, System dynamics, Simulation
National Category
Engineering and Technology Reliability and Maintenance Other Mechanical Engineering Mechanical Engineering
Research subject
INF201 Virtual Production Development; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15002 (URN)10.1016/j.ijpe.2018.03.024 (DOI)000434889900012 ()2-s2.0-85049595658 (Scopus ID)
Projects
IPSI
Note

©2018 Elsevier B.V. All rights reserved. The RightsLink Digital Licensing and Rights Management Service (including RightsLink for Open Access) is available (A) to users of copyrighted works found at the websites of participating publishers who are seeking permissions or licenses to use those works, and (B) to authors of articles and other manuscripts who are seeking to pay author publication charges in connection with the submission of their works to publishers.

Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2021-01-07Bibliographically approved
2. Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation
Open this publication in new window or tab >>Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation
2018 (English)In: Journal of Simulation, ISSN 1747-7778, E-ISSN 1747-7786, Vol. 12, no 2, p. 171-189Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Taylor & Francis, 2018
National Category
Reliability and Maintenance Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15063 (URN)10.1080/17477778.2018.1467849 (DOI)000432552700008 ()2-s2.0-85047239919 (Scopus ID)
Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2020-04-28Bibliographically approved
3. Justifying Maintenance Studying System Behavior: A Multipurpose Approach Using Multi-objective Optimization
Open this publication in new window or tab >>Justifying Maintenance Studying System Behavior: A Multipurpose Approach Using Multi-objective Optimization
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
Keywords
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; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14707 (URN)9781510851078 (ISBN)
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: 2019-01-24Bibliographically approved
4. Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study
Open this publication in new window or tab >>Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study
2018 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1293-1298Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
strategic development, maintenance performance, proactive maintenance, multi-objective optimization, system dynamics, simulation
National Category
Reliability and Maintenance Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15066 (URN)10.1016/j.procir.2018.03.219 (DOI)000526120800218 ()2-s2.0-85049594037 (Scopus ID)
Conference
51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018
Funder
Knowledge Foundation
Note

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.

Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2022-07-15Bibliographically approved
5. A hybrid simulation-based optimization framework supporting strategic maintenance to improve production performance
Open this publication in new window or tab >>A hybrid simulation-based optimization framework supporting strategic maintenance to improve production performance
2020 (English)In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 281, no 2, p. 402-414Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
Elsevier, 2020
Keywords
Problem structuring, Decision support, System dynamics, Multi-objective optimization, Discrete-event simulation
National Category
Production Engineering, Human Work Science and Ergonomics Reliability and Maintenance
Research subject
Production and Automation Engineering; VF-KDO
Identifiers
urn:nbn:se:his:diva-15064 (URN)10.1016/j.ejor.2019.08.036 (DOI)000497593000012 ()2-s2.0-85071569509 (Scopus ID)
Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2023-03-02Bibliographically approved

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Linnéusson, Gary

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