his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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.

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 ()
Projects
IPSI
Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2018-07-06Bibliographically 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
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: 2018-08-08Bibliographically 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
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: 2018-05-23Bibliographically 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: 51st CIRP Conference on Manufacturing Systems / [ed] Lihui Wang, Elsevier, 2018, Vol. 72, p. 1293-1298Conference paper, Published paper (Refereed)
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
Series
Procedia CIRP, ISSN 2212-8271 ; 72
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)2-s2.0-85049594037 (Scopus ID)
Conference
51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018
Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2018-07-30Bibliographically approved
5. A hybrid simulation-based optimization framework for supporting strategic maintenance to improve production performance
Open this publication in new window or tab >>A hybrid simulation-based optimization framework for supporting strategic maintenance to improve production performance
2018 (English)In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860Article in journal (Refereed) Submitted
National Category
Production Engineering, Human Work Science and Ergonomics Reliability and Maintenance
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15064 (URN)
Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2018-07-31

Open Access in DiVA

fulltext(8856 kB)113 downloads
File information
File name FULLTEXT01.pdfFile size 8856 kBChecksum SHA-512
1acf208a3b52eca3fe064de2bd548185fb9001a40c1270ff63a460bc274b9b54a3e1ef8a091672bb4757e629bce0f808969407a5c200991fda01ce7bff084ffc
Type fulltextMimetype application/pdf

Authority records BETA

Linnéusson, Gary

Search in DiVA

By author/editor
Linnéusson, Gary
By organisation
School of Engineering ScienceThe Virtual Systems Research Centre
Reliability and MaintenanceProduction Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar
Total: 113 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 805 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf