A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future
In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Di...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/13/4482 |
| _version_ | 1827714107652964352 |
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| author | Adrien Bécue Eva Maia Linda Feeken Philipp Borchers Isabel Praça |
| author_facet | Adrien Bécue Eva Maia Linda Feeken Philipp Borchers Isabel Praça |
| author_sort | Adrien Bécue |
| collection | DOAJ |
| description | In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing. |
| first_indexed | 2024-03-10T18:50:08Z |
| format | Article |
| id | doaj.art-2be0baaa7aed4a2899063843420519cc |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T18:50:08Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2be0baaa7aed4a2899063843420519cc2023-11-20T05:12:40ZengMDPI AGApplied Sciences2076-34172020-06-011013448210.3390/app10134482A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the FutureAdrien Bécue0Eva Maia1Linda Feeken2Philipp Borchers3Isabel Praça4AIRBUS CyberSecurity, 78996 Elancourt Cedex, FranceSchool of Engineering, Polytechnic of Porto (ISEP/IPP)/GECAD, 4249-015 Porto, PortugalOFFIS e.V.-Institut für Informatik, 26121 Oldenburg, GermanyOFFIS e.V.-Institut für Informatik, 26121 Oldenburg, GermanySchool of Engineering, Polytechnic of Porto (ISEP/IPP)/GECAD, 4249-015 Porto, PortugalIn the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.https://www.mdpi.com/2076-3417/10/13/4482Factory of the FutureDigital TwinCyber-Rangeprocess optimizationcyber-resiliencemodeling and simulation |
| spellingShingle | Adrien Bécue Eva Maia Linda Feeken Philipp Borchers Isabel Praça A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future Applied Sciences Factory of the Future Digital Twin Cyber-Range process optimization cyber-resilience modeling and simulation |
| title | A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future |
| title_full | A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future |
| title_fullStr | A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future |
| title_full_unstemmed | A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future |
| title_short | A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future |
| title_sort | new concept of digital twin supporting optimization and resilience of factories of the future |
| topic | Factory of the Future Digital Twin Cyber-Range process optimization cyber-resilience modeling and simulation |
| url | https://www.mdpi.com/2076-3417/10/13/4482 |
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