his.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Alternative names
Publications (10 of 32) Show all publications
Linnéusson, G., Ng, A. H. C. & Aslam, T. (2019). 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
2019 (English)In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860Article in journal (Refereed) Epub ahead of print
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.

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
Identifiers
urn:nbn:se:his:diva-15064 (URN)10.1016/j.ejor.2019.08.036 (DOI)
Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2019-09-24Bibliographically approved
Lidberg, S., Aslam, T., Pehrsson, L. & Ng, A. H. C. (2019). Optimizing real-world factory flows using aggregated discrete event simulation modelling: Creating decision-support through simulation-based optimization and knowledge-extraction. Flexible Services and Manufacturing Journal
Open this publication in new window or tab >>Optimizing real-world factory flows using aggregated discrete event simulation modelling: Creating decision-support through simulation-based optimization and knowledge-extraction
2019 (English)In: Flexible Services and Manufacturing Journal, ISSN 1936-6582, E-ISSN 1936-6590Article in journal (Refereed) Epub ahead of print
Abstract [en]

Reacting quickly to changing market demands and new variants by improving and adapting industrial systems is an important business advantage. Changes to systems are costly; especially when those systems are already in place. Resources invested should be targeted so that the results of the improvements are maximized. One method allowing this is the combination of discrete event simulation, aggregated models, multi-objective optimization, and data-mining shown in this article. A real-world optimization case study of an industrial problem is conducted resulting in lowering the storage levels, reducing lead time, and lowering batch sizes, showing the potential of optimizing on the factory level. Furthermore, a base for decision-support is presented, generating clusters from the optimization results. These clusters are then used as targets for a decision tree algorithm, creating rules for reaching different solutions for a decision-maker to choose from. Thereby allowing decisions to be driven by data, and not by intuition. 

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Aggregation, Data mining, Decision support, Discrete event simulation, Industrial case study, Multi-objective optimization, Agglomeration, Decision making, Decision support systems, Decision trees, Digital storage, Multiobjective optimization, Trees (mathematics), Decision supports, Decision-tree algorithm, Industrial problem, Industrial systems, Knowledge extraction, Real-world optimization, Simulation-based optimizations
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17480 (URN)10.1007/s10696-019-09362-7 (DOI)2-s2.0-85068764729 (Scopus ID)
Available from: 2019-07-25 Created: 2019-07-25 Last updated: 2019-08-19Bibliographically approved
Rösiö, C., Aslam, T., Srikanth, K. B. & Shetty, S. (2019). Towards an assessment criterion of reconfigurable manufacturing systems within the automotive industry. Paper presented at 7th International conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2018), Nantes, France, 8 October 2018 through 10 October 2018. Procedia Manufacturing, 28, 76-82
Open this publication in new window or tab >>Towards an assessment criterion of reconfigurable manufacturing systems within the automotive industry
2019 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 28, p. 76-82Article in journal (Refereed) Published
Abstract [en]

To increase changeability and reconfigurability of manufacturing systems, while maintaining cost-efficiency and environmental sustainability they need to be designed in accordance to the need for change. Since companies often need to convert existing manufacturing systems to handle variation, implementation of reconfigurable manufacturing systems calls for an analysis of the current system to understand to what extent they fulfil reconfigurability characteristics. This requires an assessment of the needs for reconfigurability as well as assessment of the existing ability to reconfigure the manufacturing system. Although a lot of reconfigurable manufacturing system assessment models are proposed in theory there is an evident knowledge gap pertaining to what extent the existing systems in the industry are in achieving reconfigurability. The purpose with this paper is to propose an assessment criterion for existing manufacturing systems to measure reconfigurability and their readiness to change with respect to products and volume variations. Based on a literature review of existing reconfigurability assessment models and a case study within the automotive industry, a criterion is developed and tested to analyze how reconfigurable a system is and to decide which parameters that need more attention to achieve higher degree of reconfigurability. © 2019 The Authors.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Assessment model, Changeable manufacturing, Manufacturing system, Reconfigurable manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17755 (URN)10.1016/j.promfg.2018.12.013 (DOI)2-s2.0-85072558955 (Scopus ID)
Conference
7th International conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2018), Nantes, France, 8 October 2018 through 10 October 2018
Note

Edited by Catherine da Cunha, Alain Bernard, Michael Zäh, Hoda ElMaraghy, Waguih ElMaraghy

Available from: 2019-10-04 Created: 2019-10-04 Last updated: 2019-10-16Bibliographically 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)000462212700075 ()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: 2019-04-08Bibliographically 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
Show others...
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)2-s2.0-85065662579 (Scopus ID)
Conference
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Available from: 2018-08-24 Created: 2018-08-24 Last updated: 2019-06-03Bibliographically 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
Show others...
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)000462212700059 ()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: 2019-04-08Bibliographically 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 ()2-s2.0-85049595658 (Scopus ID)
Projects
IPSI
Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2019-09-04Bibliographically 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
Show others...
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: 2019-05-13Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0880-2572

Search in DiVA

Show all publications