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Morshedzadeh, I., Ng, A. H. C., Jeusfeld, M. A. & Oscarsson, J. (2022). Managing virtual factory artifacts in the extended PLM context. Journal of Industrial Information Integration, 28, Article ID 100369.
Open this publication in new window or tab >>Managing virtual factory artifacts in the extended PLM context
2022 (English)In: Journal of Industrial Information Integration, ISSN 2467-964X, E-ISSN 2452-414X, Vol. 28, article id 100369Article in journal (Refereed) Published
Abstract [en]

Virtual engineering increases the rate of and diversity of models being created; hence requires maintenance in a product lifecycle management (PLM) system. This also induces the need to understand their creation contexts, known as historical or provenance information, to reuse the models in other engineering projects. PLM systems are specifically designed to manage product- and production-related data. However, they are less capable of handling the knowledge about the contexts of the models without an appropriate extension. Therefore, this research proposes an extension to PLM systems by designing a new information model to contain virtual models, their related data and knowledge generated from them through various engineering activities so that they can be effectively used to manage historical information related to all these virtual factory artifacts. Such an information model is designed to support a new Virtual Engineering ontology for capturing and representing virtual models and engineering activities, tightly integrated with an extended provenance model based on the W7 model. In addition, this paper presents how an application prototype, called Manage-Links, has been implemented with these extended PLM concepts and then used in several virtual manufacturing activities in an automotive company.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Virtual model, Product Lifecycle Management, Information model, knowledge management, Ontology
National Category
Production Engineering, Human Work Science and Ergonomics Information Systems
Research subject
Production and Automation Engineering; Information Systems; VF-KDO
Identifiers
urn:nbn:se:his:diva-21198 (URN)10.1016/j.jii.2022.100369 (DOI)000822941700006 ()2-s2.0-85136279404 (Scopus ID)
Funder
Knowledge Foundation, 20140330
Note

CC BY 4.0

Available online 2 June 2022, 100369

Corresponding author: Iman Morshedzadeh

This work was supported by the Knowledge Foundation (KKS) through the IPSI Research School at the University of Skövde [grant number 20140330], and VF-KDO Profile research project [grant number 20180011].

Available from: 2022-06-02 Created: 2022-06-02 Last updated: 2024-06-19Bibliographically approved
Senington, R., Baumeister, F., Ng, A. & Oscarsson, J. (2018). A linked data approach for the connection of manufacturing processes with production simulation models. Paper presented at 28th CIRP Design Conference, Nantes, France, May 23-25, 2018. Procedia CIRP, 70, 440-445
Open this publication in new window or tab >>A linked data approach for the connection of manufacturing processes with production simulation models
2018 (English)In: Procedia CIRP, E-ISSN 2212-8271, Vol. 70, p. 440-445Article in journal (Refereed) Published
Abstract [en]

This paper discusses the expected benefits of using linked data for the tasks of gathering, managing and understanding the data of smart factories. It has the further specific focus of using this data to maintaining a Digital Twin for the purposes of analysis and optimisation of such factories. The proposals are motivated by the use of an industrial example looking at the types of information required, the variation in data which is available and the requirements of an analysis platform to provide parameters for seamless, automated simulation and optimisation. 

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Smart Factory, Digital Twin, Linked Data
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer Systems
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16005 (URN)10.1016/j.procir.2018.03.243 (DOI)000437126800074 ()2-s2.0-85051264447 (Scopus ID)
Conference
28th CIRP Design Conference, Nantes, France, May 23-25, 2018
Projects
TWIN
Funder
Knowledge Foundation, 20160297
Note

CC BY-NC-ND 3.0

Edited by Florent Laroche, Alain Bernard

This paper is based on work performed within the research projects TWIN [20160297] sponsored by the Swedish Knowledge Foundation.

Available from: 2018-07-20 Created: 2018-07-20 Last updated: 2024-09-04Bibliographically approved
Barrera Diaz, C. A., Oscarsson, J., Lidberg, S. & Sellgren, T. (2018). Discrete Event Simulation Output Data-Handling System in an Automotive Manufacturing Plant. Paper presented at 8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018. Procedia Manufacturing, 25, 23-30
Open this publication in new window or tab >>Discrete Event Simulation Output Data-Handling System in an Automotive Manufacturing Plant
2018 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 8p. 23-30Article in journal (Refereed) Published
Abstract [en]

Discrete Event Simulation is a comprehensive tool for the analysis and design of manufacturing systems. Over the years, considerable efforts to improve simulation processes have been made. One step in these efforts is the standardisation of the output data through the development of an appropriate system which presents the results in a standardised way. This paper presents the results of a survey based on simulation projects undertaken in the automotive industry. In addition, it presents the implementation of an automated output data-handling system which aims to simplify the project’s documentation task for the simulation engineers and make the results more accessible for other stakeholders.

Place, publisher, year, edition, pages
Elsevier, 2018. p. 8
Keywords
Discrete Event Simulation, Manufacturing, Output Data-Handling System
National Category
Engineering and Technology Computer Systems
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15493 (URN)10.1016/j.promfg.2018.06.053 (DOI)000547903500004 ()2-s2.0-85059018196 (Scopus ID)
Conference
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Note

CC BY-NC-ND 4.0

Available from: 2018-06-11 Created: 2018-06-11 Last updated: 2024-05-16Bibliographically 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.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Discrete event simulation, Product lifecycle management, Multi-level simulation
National Category
Other Engineering and Technologies
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16074 (URN)10.1016/j.promfg.2018.06.059 (DOI)000547903500010 ()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: 2025-02-10Bibliographically approved
Morshedzadeh, I., Oscarsson, J., Ng, A. H. C., Jeusfeld, M. A. & Sillanpaa, J. (2018). Product lifecycle management with provenance management and virtual models: an industrial use-case study. Paper presented at 51st CIRP Conference on Manufacturing Systems (CIRP CMS 2018), 16-18 May 2018, Stockholm, Sweden. Procedia CIRP, 72, 1190-1195
Open this publication in new window or tab >>Product lifecycle management with provenance management and virtual models: an industrial use-case study
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2018 (English)In: Procedia CIRP, E-ISSN 2212-8271, Vol. 72, p. 6p. 1190-1195Article in journal (Refereed) Published
Abstract [en]

Saving and managing virtual models’ provenance information (models’ history) can increase the level of reusability of those models. This paper describes a provenance management system (PMS) that has been developed based on an industrial case study.

The product lifecycle management (PLM) system, as a main data management system, is responsible for receiving virtual models and their related data from Computer-Aided technologies (CAx) and providing this information for the PMS. In this paper, the management of discrete event simulation data with the PLM system will be demonstrated as the first link of provenance data management chain (CAx-PLM-PMS).

Place, publisher, year, edition, pages
Elsevier, 2018. p. 6
Keywords
Discrete event simulation, Provenance, Product lifecycle
National Category
Other Engineering and Technologies
Research subject
Production and Automation Engineering; Information Systems
Identifiers
urn:nbn:se:his:diva-15920 (URN)10.1016/j.procir.2018.03.157 (DOI)000526120800201 ()2-s2.0-85049581305 (Scopus ID)
Conference
51st CIRP Conference on Manufacturing Systems (CIRP CMS 2018), 16-18 May 2018, Stockholm, Sweden
Note

CC BY-NC-ND 4.0

Edited by Lihui Wang

Available from: 2018-07-03 Created: 2018-07-03 Last updated: 2025-02-10Bibliographically approved
Barrera Diaz, C. A., Oscarsson, J., Lidberg, S. & Sellgren, T. (2017). A Study of Discrete Event Simulation Project Data and Provenance Information Management in an Automotive Manufacturing Plant. In: W. K. V. Chan; A. D’Ambrogio; G. Zacharewicz; N. Mustafee; G. Wainer; E. Page (Ed.), Proceedings of the 2017 Winter Simulation Conference: . Paper presented at 2017 Winter Simulation Conference, Las Vegas, December 3-6, 2017 (pp. 4012-4023). IEEE
Open this publication in new window or tab >>A Study of Discrete Event Simulation Project Data and Provenance Information Management in an Automotive Manufacturing Plant
2017 (English)In: Proceedings of the 2017 Winter Simulation Conference / [ed] W. K. V. Chan; A. D’Ambrogio; G. Zacharewicz; N. Mustafee; G. Wainer; E. Page, IEEE, 2017, , p. 12p. 4012-4023Conference paper, Published paper (Refereed)
Abstract [en]

Discrete Event Simulation (DES) project data management is a complex and important engineering activity which impacts on an organization’s efficiency. This efficiency could be decreased by the lack of provenance information or the unreliability of existing information regarding previous simulation projects, all of which complicates the reusability of the existing data. This study presents an analysis of the management of simulation projects and their provenance data, according to the different types of scenarios usually found at a manufacturing plant. A survey based on simulation projects at an automotive manufacturing plant was conducted, in order to categorize the information regarding the studied projects, map the available provenance data and standardize its management. This study also introduces an approach that demonstrates how a structured framework based on the specific data involved in the different types of scenarios could allow an improvement of the management of DES projects.

Place, publisher, year, edition, pages
IEEE, 2017. p. 12
Series
Winter Simulation Conference (WSC), E-ISSN 1558-4305 ; 2017
National Category
Engineering and Technology Communication Systems Control Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14579 (URN)10.1109/WSC.2017.8248110 (DOI)000427768604020 ()2-s2.0-85044506370 (Scopus ID)978-1-5386-3428-8 (ISBN)978-1-5386-3429-5 (ISBN)978-1-5386-3430-1 (ISBN)
Conference
2017 Winter Simulation Conference, Las Vegas, December 3-6, 2017
Available from: 2017-12-14 Created: 2017-12-14 Last updated: 2023-07-19Bibliographically approved
Iriondo, A., Oscarsson, J. & Jeusfeld, M. A. (2017). Simulation Data Management in a Product Lifecycle Management Context. In: James Gao, Mohammed El Souri, Simeon Keates (Ed.), James Gao, Mohammed El Souri, Simeon Keates (Ed.), Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK. Paper presented at 15th International Conference on Manufacturing Research ICMR 2017. Incorporating the 32nd National Conference on Manufacturing Research. University of Greenwich, London, September 5-7, 2017 (pp. 476-481). Amsterdam: IOS Press
Open this publication in new window or tab >>Simulation Data Management in a Product Lifecycle Management Context
2017 (English)In: Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK / [ed] James Gao, Mohammed El Souri, Simeon Keates, Amsterdam: IOS Press, 2017, p. 476-481Conference paper, Published paper (Refereed)
Abstract [en]

Reuse of virtual engineering models and simulations improves engineering efficiency. Reuse requires preserving the information provenance. This paper suggests a framework based on the 7W data provenance model to be part of simulation data management implemented in product lifecycle management systems. The resulting provenance framework is based on a case study in which a product was re-engineered using finite element analysis.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2017
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 6
Keywords
Provenance, Virtual Engineering, Product Lifecycle Management
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; Information Systems; User Centred Product Design; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14502 (URN)10.3233/978-1-61499-792-4-476 (DOI)000440620700076 ()2-s2.0-85028424715 (Scopus ID)978-1-61499-792-4 (ISBN)978-1-61499-791-7 (ISBN)978-1-61499-439-8 (ISBN)
Conference
15th International Conference on Manufacturing Research ICMR 2017. Incorporating the 32nd National Conference on Manufacturing Research. University of Greenwich, London, September 5-7, 2017
Funder
Knowledge Foundation
Available from: 2017-11-21 Created: 2017-11-21 Last updated: 2020-12-16Bibliographically approved
Goienetxea Uriarte, A., Urenda Moris, M., Ng, A. H. C. & Oscarsson, J. (2016). Lean, Simulation and Optimization: A Win-Win combination. 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 2015 Winter Simulation Conference, December 6-9, Huntington Beach, California, USA (pp. 2227-2238). Piscataway, New Jersey: IEEE Computer Society
Open this publication in new window or tab >>Lean, Simulation and Optimization: A Win-Win combination
2016 (English)In: 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, New Jersey: IEEE Computer Society, 2016, p. 2227-2238Conference paper, Published paper (Refereed)
Abstract [en]

Lean and simulation analysis are driven by the same objective, how to better design and improve processes making the companies more competitive. The adoption of lean has been widely spread in companies from public to private sectors and simulation is nowadays becoming more and more popular. Several authors have pointed out the benefits of combining simulation and lean, however, they are still rarely used together in practice. Optimization as an additional technique to this combination is even a more powerful approach especially when designing and improving complex processes with multiple conflicting objectives. This paper presents the mutual benefits that are gained when combining lean, simulation and optimization and how they overcome each other´s limitations. A framework including the three concepts, some of the barriers for its implementation and a real-world industrial example are also described.

Place, publisher, year, edition, pages
Piscataway, New Jersey: IEEE Computer Society, 2016
Series
Proceedings - Winter Simulation Conference, ISSN 0891-7736, E-ISSN 1558-4305 ; 2016
Keywords
Lean, Simulation, Optimization, Decision making
National Category
Production Engineering, Human Work Science and Ergonomics Computer Systems
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-11766 (URN)10.1109/WSC.2015.7408335 (DOI)000399133902010 ()2-s2.0-84962838930 (Scopus ID)978-1-4673-9743-8 (ISBN)978-1-4673-9741-4 (ISBN)978-1-4673-9742-1 (ISBN)
Conference
2015 Winter Simulation Conference, December 6-9, Huntington Beach, California, USA
Projects
Simulation-based Multi-objective Optimization for Lean production and logistic Networks
Funder
Knowledge Foundation
Available from: 2015-12-17 Created: 2015-12-17 Last updated: 2019-07-02Bibliographically approved
Morshedzadeh, I., Oscarsson, J., Ng, A. H. .., Jeusfeld, M. A. & Jenefeldt, A. (2016). Real World Data Identification and Classification for Support of Virtual Confidence. In: : . Paper presented at 7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016.
Open this publication in new window or tab >>Real World Data Identification and Classification for Support of Virtual Confidence
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2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Shortening of the product development process time is one of the main approaches for all enterprises to offer their products to the market. Virtual manufacturing tools can help companies to reduce their time to market, by reduction of the engineering lead time. Extensive use of virtual engineering models results in a need for verification of the model’s accuracy. This virtual engineering usability and assessment have been named virtual confidence. The two main factors of the achievement of this confidence are the accuracy of the virtual models and the virtual engineering results.

For controlling of both above factors, a complete virtual model and related virtual model knowledge are needed. These knowledges can be tacit or explicit. For exploring explicit knowledge, a data and information collection from different disciplines in the organization is needed.

In this paper, a data map with focus on the manufacturing engineering scope will be presented. This data map is generated from different data sources at a manufacturing plant, and gives an overview of different data that exist at different data sources, in the area of manufacturing. Combining real world data from different sources with virtual engineering model data supports, amongst others, establishment of virtual confidence.

Keywords
Virtual confidence, manufacturing knowledge, data map, Product lifecycle management (PLM), explicit knowledge
National Category
Other Engineering and Technologies
Research subject
Production and Automation Engineering; Information Systems
Identifiers
urn:nbn:se:his:diva-13736 (URN)
Conference
7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016
Projects
KDDS
Funder
Knowledge Foundation
Available from: 2017-06-16 Created: 2017-06-16 Last updated: 2025-02-10Bibliographically approved
Oscarsson, J., Jeusfeld, M. A. & Jenefeldt, A. (2016). Towards Virtual Confidence - Extended Product Lifecycle Management. In: Abdelaziz Bouras, Benoit Eynard, Sebti Foufou & Klaus-Dieter Thoben (Ed.), Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers. Paper presented at 12th IFIP International Conference on Product Lifecycle Management (PLM 2015), Doha, Qatar, October 19-21, 2015 (pp. 708-717). Paper presented at 12th IFIP International Conference on Product Lifecycle Management (PLM 2015), Doha, Qatar, October 19-21, 2015. Springer, 467
Open this publication in new window or tab >>Towards Virtual Confidence - Extended Product Lifecycle Management
2016 (English)In: Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers / [ed] Abdelaziz Bouras, Benoit Eynard, Sebti Foufou & Klaus-Dieter Thoben, Springer, 2016, Vol. 467, p. 708-717Chapter in book (Refereed)
Abstract [en]

Product lifecycle management (PLM) systems maintain amongst others the specifications and designs of product, process and resource artefacts and thus serve as the basis for realizing the concept of Virtual Manufacturing, and play a vital role in shortening the leadtimes for the engineering processes. Design of new products requires numerous experiments and test-runs of new facilities that delays the product release and causes high costs if performed in the real world. Virtualization promises to reduce these costs by simulating the reality. However, the results of the simulation must predict the real results to be useful. This is called virtual confidence. We propose a knowledge base approach to capture and maintain the virtual confidence in simulation results. To do so, the provenance of results of real, experimental and simulated processes are recorded and linked via confirmation objects.

Place, publisher, year, edition, pages
Springer, 2016
Series
IFIP Advances in Information and Communication Technology, ISSN 1868-4238 ; 467
Keywords
Virtual confidence Simulation data management Provenance Ontology
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Technology; Production and Automation Engineering; Information Systems
Identifiers
urn:nbn:se:his:diva-12163 (URN)10.1007/978-3-319-33111-9_64 (DOI)000378549400064 ()2-s2.0-84964842018 (Scopus ID)978-3-319-33110-2 (ISBN)978-3-319-33111-9 (ISBN)
Conference
12th IFIP International Conference on Product Lifecycle Management (PLM 2015), Doha, Qatar, October 19-21, 2015
Funder
Knowledge Foundation
Available from: 2016-04-22 Created: 2016-04-22 Last updated: 2018-03-28
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9690-890X

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