his.sePublikationer
Ändra sökning
Länk till posten
Permanent länk

Direktlänk
BETA
Alternativa namn
Publikationer (10 of 23) Visa alla publikationer
Lidberg, S., Pehrsson, L. & Frantzén, M. (2018). Applying Aggregated Line Modeling Techniques to Optimize Real World Manufacturing Systems. Paper presented at 8th Swedish Production Symposium, SPS, Stockholm, Sweden May 16-18, 2018. Procedia Manufacturing, 25, 89-96
Öppna denna publikation i ny flik eller fönster >>Applying Aggregated Line Modeling Techniques to Optimize Real World Manufacturing Systems
2018 (Engelska)Ingår i: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, s. 89-96Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The application of discrete event simulation methodology in the analysis of higher level manufacturing systems has been limited due to model complexity and the lack of aggregation techniques for manufacturing lines. Recent research has introduced new aggregation methods preparing for new approaches in the analysis of higher level manufacturing systems or networks. In this paper one of the new aggregated line modeling techniques is successfully applied on a real world manufacturing system, solving a real-world problem. The results demonstrate that the aggregation technique is adequate to be applied in plant wide models. Furthermore, in this particular case, there is a potential to reduce storage levels by over 25 %, through leveling the production flow, without compromising deliveries to customers.

Ort, förlag, år, upplaga, sidor
Elsevier, 2018
Nyckelord
Discrete event simulation, Aggregated line modeling, Multi-objective optimization, Manufacturing systems
Nationell ämneskategori
Produktionsteknik, arbetsvetenskap och ergonomi
Forskningsämne
INF203 Virtual Machining; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-16476 (URN)10.1016/j.promfg.2018.06.061 (DOI)2-s2.0-85062632645 (Scopus ID)
Konferens
8th Swedish Production Symposium, SPS, Stockholm, Sweden May 16-18, 2018
Forskningsfinansiär
KK-stiftelsen
Tillgänglig från: 2019-01-15 Skapad: 2019-01-15 Senast uppdaterad: 2019-09-04Bibliografiskt granskad
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
Öppna denna publikation i ny flik eller fönster >>Multi-level management of discrete event simulation models in a product lifecycle management framework
Visa övriga...
2018 (Engelska)Ingår i: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, s. 74-81Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
Elsevier, 2018
Nyckelord
Discrete event simulation, Product lifecycle management, Multi-level simulation
Nationell ämneskategori
Övrig annan teknik
Forskningsämne
Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-16074 (URN)10.1016/j.promfg.2018.06.059 (DOI)2-s2.0-85065662579 (Scopus ID)
Konferens
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Tillgänglig från: 2018-08-24 Skapad: 2018-08-24 Senast uppdaterad: 2019-11-20Bibliografiskt granskad
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.
Öppna denna publikation i ny flik eller fönster >>A methodology facilitating knowledge transfer to both research experienced companies and to novice SMEs
Visa övriga...
2017 (Engelska)Ingår i: International Journal of Enterprise Network Management, ISSN 1748-1252, Vol. 8, nr 2, s. 123-140, artikel-id IJENM0080202Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
InderScience Publishers, 2017
Nyckelord
methodology facilitating knowledge transfer, technology transfer, SME, small and medium enterprises, knowledge society
Nationell ämneskategori
Produktionsteknik, arbetsvetenskap och ergonomi
Forskningsämne
Produktion och automatiseringsteknik; INF201 Virtual Production Development
Identifikatorer
urn:nbn:se:his:diva-13999 (URN)10.1504/IJENM.2017.10006499 (DOI)2-s2.0-85027189530 (Scopus ID)
Forskningsfinansiär
KK-stiftelsen, 20130303Vinnova, 2014-05220
Tillgänglig från: 2017-08-17 Skapad: 2017-08-17 Senast uppdaterad: 2019-05-13Bibliografiskt granskad
Frantzén, M., Holm, M., Syberfeldt, A., Ng, A. H. C., Karlsson, V. & Bremert, M. (2016). Dynamic maintenance priority of a real-world machining line. In: Proceedings of the 7th Swedish Production Symposium: . Paper presented at 7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016.
Öppna denna publikation i ny flik eller fönster >>Dynamic maintenance priority of a real-world machining line
Visa övriga...
2016 (Engelska)Ingår i: Proceedings of the 7th Swedish Production Symposium, 2016Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

To support the shop-floor operators, decision support systems (DSS) are becoming more and more vital to the success of manufacturing systems in industry today. In order to get a DSS able to adapt to disturbances in a production system, on-line data are needed to be able to make optimal or near-optimal decisions in real-time (soft real-time). This paper investigates one part of such a system, i.e. how different priorities of maintenance activities (planned and unplanned) affect the productivity of a production system. A discrete-event simulation model has been built for a real-world machining line in order to simulate the decisions made in subject to disturbances. This paper presents a way of prioritizing operators and machines based on multiple criteria such as competence, utilization, distance, bottleneck, and Work-In-Process. An experimental study based on the real-world production system has shown promising results and given insights of how to prioritize the operators in a good way. Another novelty introduced in this paper is the use of simulation-based optimization to generate composite dispatching rules in order to find good tradeoffs when taking a decision of which machine or operator to select.

Nyckelord
maintenance, simulation, optimization, genetic programming
Nationell ämneskategori
Övrig annan teknik
Forskningsämne
Teknik; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-13232 (URN)
Konferens
7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016
Projekt
Young Operator2020 (YOU2)Interactive Decision Support using Simulation-based Innovization (IDSS)
Forskningsfinansiär
KK-stiftelsen
Tillgänglig från: 2016-12-15 Skapad: 2016-12-14 Senast uppdaterad: 2018-03-28
Ng, A. H. .., Bandaru, S. & Frantzén, M. (2016). Innovative Design and Analysis of Production Systems by Multi-objective Optimization and Data Mining. Paper presented at 26th CIRP Design Conference. Procedia CIRP, 50, 665-671
Öppna denna publikation i ny flik eller fönster >>Innovative Design and Analysis of Production Systems by Multi-objective Optimization and Data Mining
2016 (Engelska)Ingår i: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 50, s. 665-671Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper presents an innovative approach for the design and analysis of production systems using multi-objective optimization and data mining. The innovation lies on how these two methods using different computational intelligence algorithms can be synergistically integrated and used interactively by production systems designers to support their design decisions. Unlike ordinary optimization approaches for production systems design which several design objectives are linearly combined into a single mathematical function, multi-objective optimization that can generate multiple design alternatives and sort their performances into an efficient frontier can enable the designer to have a more complete picture about how the design decision variables, like number of machines and buffers, can affect the overall performances of the system. Such kind of knowledge that can be gained by plotting the efficient frontier cannot be sought by single-objective based optimizations. Additionally, because of the multiple optimal design alternatives generated, they constitute a dataset that can be fed into some data mining algorithms for extracting the knowledge about the relationships among the design variables and the objectives. This paper addresses the specific challenges posed by the design of discrete production systems for this integrated optimization and data mining approach and then outline a new interactive data mining algorithm developed to meet these challenges, illustrated with a real-world production line design example.

Ort, förlag, år, upplaga, sidor
Elsevier, 2016
Nyckelord
Production Systems, Multi-Objective Optimization, Data Mining
Nationell ämneskategori
Produktionsteknik, arbetsvetenskap och ergonomi
Forskningsämne
Teknik; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-12815 (URN)10.1016/j.procir.2016.04.159 (DOI)000387666600112 ()2-s2.0-84986608440 (Scopus ID)
Konferens
26th CIRP Design Conference
Tillgänglig från: 2016-08-25 Skapad: 2016-08-25 Senast uppdaterad: 2018-03-28Bibliografiskt granskad
Pehrsson, L., Frantzén, M., Aslam, T. & Ng, A. H. C. (2015). Aggregated line modeling for simulation and optimization of manufacturing systems. In: L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti (Ed.), Proceedings of the 2015 Winter Simulation Conference: . Paper presented at WSC '15 Winter Simulation Conference, Huntington Beach, CA, USA — December 06 - 09, 2015 (pp. 3632-3643). Piscataway, NJ, USA: IEEE Press
Öppna denna publikation i ny flik eller fönster >>Aggregated line modeling for simulation and optimization of manufacturing systems
2015 (Engelska)Ingår i: Proceedings of the 2015 Winter Simulation Conference / [ed] L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, Piscataway, NJ, USA: IEEE Press, 2015, s. 3632-3643Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In conceptual analysis of higher level manufacturing systems, for instance, when the constraint on system level is sought, it may not be very practical to use detailed simulation models. Developing detailed models on supply chain level or plant wide level may be very time consuming and might also be computationally costly to execute, especially if optimization techniques are to be applied. Aggregation techniques, simplifying a detailed system into fewer objects, can be an effective method to reduce the required computational resources and to shorten the development time. An aggregated model can be used to identify the main system constraints, dimensioning inter-line buffers, and focus development activities on the critical issues from a system performance perspective. In this paper a novel line aggregation technique suitable for manufacturing systems optimization is proposed, analyzed and tested in order to establish a proof of concept while demonstrating the potential of the technique.

Ort, förlag, år, upplaga, sidor
Piscataway, NJ, USA: IEEE Press, 2015
Serie
Winter Simulation Conference. Proceedings, ISSN 0891-7736
Nyckelord
Simulation, Modeling, Manufacturing, Optimization
Nationell ämneskategori
Annan maskinteknik
Forskningsämne
Teknik; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-11899 (URN)10.1109/WSC.2015.7408522 (DOI)000399133903069 ()2-s2.0-84962829106 (Scopus ID)978-1-4673-9743-8 (ISBN)
Konferens
WSC '15 Winter Simulation Conference, Huntington Beach, CA, USA — December 06 - 09, 2015
Tillgänglig från: 2016-02-12 Skapad: 2016-02-11 Senast uppdaterad: 2018-05-07Bibliografiskt granskad
Frantzén, M. & Ng, A. H. C. (2015). Production simulation education using rapid modeling and optimization: Successful studies. In: L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti (Ed.), Proceedings of the 2015 Winter Simulation Conference: . Paper presented at WSC '15 Winter Simulation Conference, Huntington Beach, CA, USA — December 06 - 09, 2015 (pp. 3526-3537). Piscataway, NJ: IEEE Press
Öppna denna publikation i ny flik eller fönster >>Production simulation education using rapid modeling and optimization: Successful studies
2015 (Engelska)Ingår i: Proceedings of the 2015 Winter Simulation Conference / [ed] L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, Piscataway, NJ: IEEE Press, 2015, s. 3526-3537Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

A common issue facing many simulation educators is that students usually spend excessive time to struggle with the programming and statistic parts of the simulation courses, and simply very little time to learn running systems analysis. If the students are coming from industry, and not the campus, then the problem becomes even worse. We observed this problem around 2005 and started to develop a new simulation software, a factory conceptual design toolset, partly aimed to address this problem. A new set of educational courses has since then been developed around the software for teaching production systems analysis, with both the campus students and managers/engineers from industry in mind. In this paper, we briefly introduce the software and share our experiences and some representative, successful studies conducted by the students in the past years.

Ort, förlag, år, upplaga, sidor
Piscataway, NJ: IEEE Press, 2015
Serie
Winter Simulation Conference. Proceedings, ISSN 0891-7736
Nyckelord
Optimization, Production, Simulation, FACTS
Nationell ämneskategori
Annan maskinteknik
Forskningsämne
Teknik; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-11900 (URN)10.1109/WSC.2015.7408512 (DOI)000399133903059 ()2-s2.0-84962921246 (Scopus ID)978-1-4673-9743-8 (ISBN)
Konferens
WSC '15 Winter Simulation Conference, Huntington Beach, CA, USA — December 06 - 09, 2015
Tillgänglig från: 2016-02-12 Skapad: 2016-02-11 Senast uppdaterad: 2018-05-07Bibliografiskt granskad
Pehrsson, L., Lidberg, S., Frantzén, M., Aslam, T. & Ng, A. (2014). Aggregated Discrete Event Modelling for Simulation and Optimisation of Manufacturing Systems. In: Industrial Simulation Conference, Skövde, June 11-13, 2014, Eurosis, 2014: . Paper presented at 12th Annual Industrial Simulation Conference, ISC'2014, June 11-13, 2014, University of Skövde, Skövde, Sweden (pp. 83-90).
Öppna denna publikation i ny flik eller fönster >>Aggregated Discrete Event Modelling for Simulation and Optimisation of Manufacturing Systems
Visa övriga...
2014 (Engelska)Ingår i: Industrial Simulation Conference, Skövde, June 11-13, 2014, Eurosis, 2014, 2014, s. 83-90Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In many simulation studies for factory analysis, for example, to locate the constraint of an entire factory that consists of multiple production lines, it may not be effective to put every process detail into a single model. Firstly, to develop such a factory-wide model would be very time-consuming. Secondly, it can be very computational costly to run the model, especially if simulation-based optimisation is applied to find the optimal setting from such a complex model that possesses all the details of the processes. In this regard, aggregation, with which multiple process steps are aggregated into some simpler simulation objects, is an effective method to reduce both the development and computational times. On one hand, based on the initial analysis, the simulation expert can pinpoint the sub-system that restrains the performance of the entire factory and decide if a more detailed model is needed. On the other hand, interline buffers/storages can be readily optimised by using such an aggregated model. Through an application study with data from a real-world factory, this paper introduces a novel aggregation method and illustrates the potential of the abovesaid concepts.

Nyckelord
Simulation, aggregation, discrete event systems, manufacturing systems, multi-objective optimisation
Nationell ämneskategori
Produktionsteknik, arbetsvetenskap och ergonomi
Forskningsämne
Teknik; Produktion och automatiseringsteknik
Identifikatorer
urn:nbn:se:his:diva-10478 (URN)2-s2.0-84922126480 (Scopus ID)978-90-77381-83-0 (ISBN)
Konferens
12th Annual Industrial Simulation Conference, ISC'2014, June 11-13, 2014, University of Skövde, Skövde, Sweden
Tillgänglig från: 2014-12-22 Skapad: 2014-12-22 Senast uppdaterad: 2018-05-23Bibliografiskt granskad
Frantzén, M. (2013). A real-time simulation-based optimisation environment for industrial scheduling. (Doctoral dissertation). Leicester: De Montfort University
Öppna denna publikation i ny flik eller fönster >>A real-time simulation-based optimisation environment for industrial scheduling
2013 (Engelska)Doktorsavhandling, monografi (Övrigt vetenskapligt)
Abstract [en]

In order to cope with the challenges in industry today, such as changes in product diversity and production volume, manufacturing companies are forced to react more flexibly and swiftly. Furthermore, in order for them to survive in an ever-changing market, they also need to be highly competitive by achieving near optimal efficiency in their operations. Production scheduling is vital to the success of manufacturing systems in industry today, because the near optimal allocation of resources is essential in remaining highly competitive.

 

The overall aim of this study is the advancement of research in manufacturing scheduling through the exploration of more effective approaches to address complex, real-world manufacturing flow shop problems. The methodology used in the thesis is in essence a combination of systems engineering, algorithmic design and empirical experiments using real-world scenarios and data. Particularly, it proposes a new, web services-based, industrial scheduling system framework, called OPTIMISE Scheduling System (OSS), for solving real-world complex scheduling problems. OSS, as implemented on top of a generic web services-based simulation-based optimisation (SBO) platform called OPTIMISE, can support near optimal and real-time production scheduling in a distributed and parallel computing environment. Discrete-event simulation (DES) is used to represent and flexibly cope with complex scheduling problems without making unrealistic assumptions which are the major limitations of existing scheduling methods proposed in the literature.  At the same time, the research has gone beyond existing studies of simulation-based scheduling applications, because the OSS has been implemented in a real-world industrial environment at an automotive manufacturer, so that qualitative evaluations and quantitative comparisons of scheduling methods and algorithms can be made with the same framework.

 

Furthermore, in order to be able to adapt to and handle many different types of real-world scheduling problems, a new hybrid meta-heuristic scheduling algorithm that combines priority dispatching rules and genetic encoding is proposed. This combination is demonstrated to be able to handle a wider range of problems or a current scheduling problem that may change over time, due to the flexibility requirements in the real-world.  The novel hybrid genetic representation has been demonstrated effective through the evaluation in the real-world scheduling problem using real-world data.

Ort, förlag, år, upplaga, sidor
Leicester: De Montfort University, 2013. s. 250
Nyckelord
Scheduling system, Simulation, Scheduling, simulation-based optimisation
Nationell ämneskategori
Produktionsteknik, arbetsvetenskap och ergonomi
Forskningsämne
Teknik
Identifikatorer
urn:nbn:se:his:diva-9059 (URN)978-91-628-8818-3 (ISBN)
Disputation
2013-04-19, Leicester, 10:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
KK-stiftelsen
Tillgänglig från: 2014-05-13 Skapad: 2014-05-08 Senast uppdaterad: 2017-11-27Bibliografiskt granskad
Frantzén, M., Ng, A. H. C. & Moore, P. (2011). A simulation-based scheduling system for real-time optimization and decision making support. Paper presented at 20th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), California State Univ, Oakland, CA, 2010. Robotics and Computer-Integrated Manufacturing, 27(4), 696-705
Öppna denna publikation i ny flik eller fönster >>A simulation-based scheduling system for real-time optimization and decision making support
2011 (Engelska)Ingår i: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 27, nr 4, s. 696-705Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper presents an industrial application of simulation-based optimization (SBO) in the scheduling and real-time rescheduling of a complex machining line in an automotive manufacturer in Sweden. Apart from generating schedules that are robust and adaptive, the scheduler must be able to carry out rescheduling in real time in order to cope with the system uncertainty effectively. A real-time scheduling system is therefore needed to support not only the work of the production planner but also the operators on the shop floor by re-generating feasible schedules when required. This paper describes such a real-time scheduling system, which is in essence a SBO system integrated with the shop floor database system. The scheduling system, called OPTIMISE scheduling system (OSS), uses real-time data from the production line and sends back expert suggestions directly to the operators through Personal Digital Assistants (PDAs). The user interface helps in generating new schedules and enables the users to easily monitor the production progress through visualization of production status and allows them to forecast and display target performance measures. Initial results from this industrial application have shown that such a novel scheduling system can help both in improving the line throughput efficiently and simultaneously supporting real-time decision making.

Ort, förlag, år, upplaga, sidor
Elsevier, 2011
Nyckelord
Scheduling system, Simulation, Scheduling, Simulation-based optimization
Nationell ämneskategori
Teknik och teknologier
Forskningsämne
Teknik
Identifikatorer
urn:nbn:se:his:diva-4866 (URN)10.1016/j.rcim.2010.12.006 (DOI)000291458900006 ()2-s2.0-79955656034 (Scopus ID)
Konferens
20th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM), California State Univ, Oakland, CA, 2010
Tillgänglig från: 2011-05-03 Skapad: 2011-05-03 Senast uppdaterad: 2017-12-11Bibliografiskt granskad
Organisationer
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-4086-3877

Sök vidare i DiVA

Visa alla publikationer