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Linnéusson, G., Ng, A. H. C. & Aslam, T. (2018). A hybrid simulation-based optimization framework for supporting strategic maintenance to improve production performance. European Journal of Operational Research
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: 2019-03-19Bibliographically approved
Lidberg, S., Aslam, T., Pehrsson, L. & Ng, A. H. C. (2018). Evaluating the impact of changes on a global supply chain using an iterative approach in a proof-of-concept model. In: Peter Thorvald, Keith Case (Ed.), Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden. Paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (pp. 467-472). Amsterdam: IOS Press
Open this publication in new window or tab >>Evaluating the impact of changes on a global supply chain using an iterative approach in a proof-of-concept model
2018 (English)In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, p. 467-472Conference paper, Published paper (Refereed)
Abstract [en]

Analyzing networks of supply-chains, where each chain is comprised of several actors with different purposes and performance measures, is a difficult task. There exists a large potential in optimizing supply-chains for many companies and therefore the supply-chain optimization problem is of great interest to study. To be able to optimize the supply-chain on a global scale, fast models are needed to reduce computational time. Previous research has been made into the aggregation of factories, but the technique has not been tested against supply-chain problems. When evaluating the configuration of factories and their inter-transportation on a global scale, new insights can be gained about which parameters are important and how the aggregation fits to a supply-chain problem. The paper presents an interactive proof-of-concept model enabling testing of supply chain concepts by users and decision makers.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords
Aggregated modeling, Discrete Event Simulation, Manufacturing, Proof-of-concept, Supply-chain management, Decision making, Iterative methods, Manufacture, Supply chain management, Computational time, Global supply chain, Interactive proofs, Iterative approach, Performance measure, Proof of concept, Supply chain optimization, Industrial research
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; INF203 Virtual Machining
Identifiers
urn:nbn:se:his:diva-16496 (URN)10.3233/978-1-61499-902-7-467 (DOI)2-s2.0-85057354809 (Scopus ID)978-1-61499-901-0 (ISBN)978-1-61499-902-7 (ISBN)
Conference
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden
Funder
Knowledge Foundation
Available from: 2018-12-13 Created: 2018-12-13 Last updated: 2019-02-14Bibliographically approved
Morshedzadeh, I., Oscarsson, J., Ng, A. H. C., Aslam, T. & Frantzén, M. (2018). Multi-level management of discrete event simulation models in a product lifecycle management framework. Paper presented at 8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018. Procedia Manufacturing, 25, 74-81
Open this publication in new window or tab >>Multi-level management of discrete event simulation models in a product lifecycle management framework
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2018 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 74-81Article in journal (Refereed) Published
Abstract [en]

Discrete event simulation (DES) models imitates the behavior of a production system. Models can be developed to reflect different levels of the production system, e.g supply chain level or manufacturing line level. Product Lifecycle Management (PLM) systems have been developed in order to manage product and manufacturing related data. DES models is one kind of product lifecycle’s data which can be managed by a PLM system. This paper presents a method and its implementation for management of interacting multi-level models utilizing a PLM system.

Keywords
Discrete event simulation, Product lifecycle management, Multi-level simulation
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16074 (URN)10.1016/j.promfg.2018.06.059 (DOI)
Conference
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2018-10-31Bibliographically approved
Linnéusson, G., Ng, A. H. C. & Aslam, T. (2018). Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation. Journal of Simulation, 12(2), 171-189
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: 2018-10-04Bibliographically approved
Linnéusson, G., Ng, A. H. C. & Aslam, T. (2018). Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study. Paper presented at 51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018. Procedia CIRP, 72, 1293-1298
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)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: 2018-10-31Bibliographically approved
Aslam, T., Syberfeldt, A., Ng, A., Pehrsson, L. & Urenda-Moris, M. (2018). Towards an industrial testbed for holistic virtual production development. In: Peter Thorvald, Keith Case (Ed.), Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden. Paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (pp. 369-374). Amsterdam: IOS Press
Open this publication in new window or tab >>Towards an industrial testbed for holistic virtual production development
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2018 (English)In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, p. 369-374Conference paper, Published paper (Refereed)
Abstract [en]

Virtual production development is adopted by many companies in the production industry and digital models and virtual tools are utilized for strategic, tactical and operational decisions in almost every stage of the value chain. This paper suggest a testbed concept that aims the production industry to adopt a virtual production development process with integrated tool chains that enables holistic optimizations, all the way from the overall supply chain performance down to individual equipment/devices. The testbed, which is fully virtual, provides a mean for development and testing of integrated digital models and virtual tools, including both technical and methodological aspects.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords
Virtual production development, testbed, integrated tool chains, simulation, optimization
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16375 (URN)10.3233/978-1-61499-902-7-369 (DOI)2-s2.0-85057415907 (Scopus ID)978-1-61499-901-0 (ISBN)978-1-61499-902-7 (ISBN)
Conference
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-02-05Bibliographically approved
Linnéusson, G., Ng, A. H. C. & Aslam, T. (2018). Towards strategic development of maintenance and its effects on production performance by using system dynamics in the automotive industry. International Journal of Production Economics, 200, 151-169
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
Holm, M., Frantzén, M., Aslam, T., Moore, P. & Wang, L. (2017). A methodology facilitating knowledge transfer to both research experienced companies and to novice SMEs. International Journal of Enterprise Network Management, 8(2), 123-140, Article ID IJENM0080202.
Open this publication in new window or tab >>A methodology facilitating knowledge transfer to both research experienced companies and to novice SMEs
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2017 (English)In: International Journal of Enterprise Network Management, ISSN 1748-1252, Vol. 8, no 2, p. 123-140, article id IJENM0080202Article in journal (Refereed) Published
Abstract [en]

In this paper, knowledge transfer is defined as a process of disseminating both technological and theoretical understanding as well as enhancing both industrial and academic knowledge through conducted research to project partners collaborating within a research project. To achieve this, a new methodology called 'user groups' is introduced. It facilitates knowledge transfer between project participants in collaborative research programs engaging both experienced and unexperienced partners regardless of level of input. The introduced methodology 'user groups' provides tools for collaborating with several research partners even though their levels of engagement in the project and prior research experience may vary without dividing them into separate groups. It enables all project partners to gain new knowledge and by so doing extending the knowledge society. The case study shows that the eight engaged companies are able to cooperate, achieve their own objectives and, both jointly and individually, contribute to the overall project goals.

Place, publisher, year, edition, pages
InderScience Publishers, 2017
Keywords
methodology facilitating knowledge transfer, technology transfer, SME, small and medium enterprises, knowledge society
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-13999 (URN)10.1504/IJENM.2017.10006499 (DOI)2-s2.0-85027189530 (Scopus ID)
Funder
Knowledge Foundation, 20130303VINNOVA, 2014-05220
Available from: 2017-08-17 Created: 2017-08-17 Last updated: 2019-01-24Bibliographically approved
Linnéusson, G., Ng, A. H. C. & Aslam, T. (2017). Justifying Maintenance Studying System Behavior: A Multipurpose Approach Using Multi-objective Optimization. In: J. Sterman, N. Repenning (Ed.), 35th International Conference of the System Dynamics Society 2017: Cambridge, Massachusetts, USA 16 - 20 July 2017. Paper presented at 35th International Conference of the System Dynamics Society, Cambridge, Massachusetts, USA, July 16-20, 2017 (pp. 1061-1081). Curran Associates, Inc., 2
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
Aslam, T. & Ng, A. H. C. (2016). Combining system dynamics and multi-objective optimization with design space reduction. Industrial management + data systems, 116(2), 291-321
Open this publication in new window or tab >>Combining system dynamics and multi-objective optimization with design space reduction
2016 (English)In: Industrial management + data systems, ISSN 0263-5577, E-ISSN 1758-5783, Vol. 116, no 2, p. 291-321Article in journal (Refereed) Published
Abstract [en]

Purpose 

The purpose of this study is to introduce an effective methodology for obtaining Pareto-optimal solutions, when combining System Dynamics (SD) and Multi-Objective Optimization (MOO) for supply chain problems.

Design/methodology/approach 

This paper proposes a new approach that combines SD and MOO within a simulation-based optimization framework to generate the efficient frontier that supports decision- making in SupplyChain Management (SCM). It also addresses the issue of the curse of dimensionality, commonly found in practical optimization problems, through design space reduction.

Findings 

The integrated MOO and SD approach has been shown to be very useful in revealing how the decision variables in the Beer Game affect the optimality of the three common SCM objectives, namely, the minimization of inventory, backlog, and the bullwhip effect. The results of the in-depth Beer Game study clearly show that these three optimization objectives are in conflict with each other, in the sense that a supply chain manager cannot minimize the bullwhip effect without increasing the total inventory and total backlog levels.

Practical implications

Having a methodology that enables the effective generation of optimal trade-off solutions, in terms of computational cost, time, as well as solution diversity and intensification, not only assists decision makers to make decisions on time, but also presents a diverse and intense solution set to choose from.

Originality/value 

This paper presents a novel supply chain MOO methodology that helps to find Pareto-optimal solutions in a more effective manner. In order to do so, the methodology tackles the so-called curse of dimensionality, by reducing the design space and focusing the search of the optimization to regions of interest. Together with design space reduction, it is believed that the integrated SD and MOOapproach can provide an innovative and efficient method for the design and analysis of manufacturing supply chain systems in general.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2016
Keywords
Multi-objective optimization, System Dynamics, Supply Chain
National Category
Engineering and Technology
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-11989 (URN)10.1108/IMDS-05-2015-0215 (DOI)000374152600006 ()2-s2.0-84960390024 (Scopus ID)
Available from: 2016-03-03 Created: 2016-02-29 Last updated: 2018-05-07Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0880-2572

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