A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · Flexible and Reconfigurable Manufacturing Systems · Technology Assessment and Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
AIRBUS CyberSecurity, 78996 Elancourt Cedex, France
School of Engineering, Polytechnic of Porto (ISEP/IPP)/GECAD, 4249-015 Porto, Portugal
OFFIS e.V.-Institut für Informatik, 26121 Oldenburg, Germany
Funding
ITEA3 · Bundesministerium für Bildung und Forschung · ANI|P2020 · FCT
References (100+)
Show source-provided references
1. Eisenstein, P.A. (2020, June 11). European Car Plants Halted by WannaCry Ransomware Attack. Available online: https://www.nbcnews.com/business/autos/european-car-plants-halted-wannacry-ransomware-attack-n759496.
2. Saint-Gobain (2020, June 11). Press Release-Cyber-Attack Update. Available online: https://www.saint-gobain.com/sites/sgcom.master/files/03-07-2017_cp_va.pdf.
3. (2020, June 11). Rosneft, Maersk Hit by Petya Cyber Attack. Available online: https://www.oedigital.com/news/446237-rosneft-maersk-hit-by-petya-cyber-attack.
4. Guide to industrial control systems (ics) security
5. The European Commission (2020, June 11). Industry 4.0. Available online: https://ec.europa.eu/growth/tools-databases/dem/monitor/sites/.
6. The First Industrial Revolution: Creation of a New Global Human Era
7. Adam Smith on the Division of Labor and Relative Factor Prices10.1017/S1042771600004038 ↗
8. From Shafts to Wires: Historical Perspective on Electrification10.1017/S0022050700029673 ↗
9. Kranzberg, M., and Hannan, M.T. (2017). History of the Organization of Work, Encyclopædia Britannica, Inc.
10. Frederick Winslow Taylor: Reflections on the Relevance of the Principles of Scientific Management 100 Years Later
11. Analysis of Henry Ford’s contribution to production and Management
12. 50 Years of Industrial Automation [History]
13. Ohno, T. (1988). Toyota Production System: Beyond Large-Scale Production, Productivity Press.
14. Lean manufacturing: Context, practice bundles, and performance10.1016/S0272-6963(02)00108-0 ↗
15. Kocovic, P. (2017). History of Additive Manufacturing. 3D Printing and Its Impact on the Production of Fully Functional Components: Emerging Research and Opportunities, IGI Global.10.4018/978-1-5225-2289-8 ↗
16. Mikhak, B., Lyon, C., Gorton, T., Gershenfeld, N., McEnnis, C., and Taylor, J. (2020, June 11). Fab Lab: An Alternate Model of Ict for Development. Available online: https://www.researchgate.net/profile/Bakhtiar_Mikhak/publication/228600651_Fab_Lab_An_alternate_model_of_ICT_for_development/links/09e41510730d663e59000000/Fab-Lab-An-alternate-model-of-ICT-for-development.pdf.
17. The industrial internet of things (IIoT): An analysis framework10.1016/j.compind.2018.04.015 ↗
18. International Federation of Robotics (IFR) (2018). Robots and the Workplace of the Future, International Federation of Robotics.
19. Human–robot collaboration in industrial applications: Safety, interaction and trust10.1177/1729881417716010 ↗
20. The Future of Manufacturing: A New Perspective10.1016/j.eng.2018.07.020 ↗
21. Gorecky, D., Khamis, M., and Mura, K. (2015). Introduction and establishment of virtual training in the factory of the future. Int. J. Comp. Int. Man., 1–9.10.1080/0951192X.2015.1067918 ↗
22. Augmented Reality Smart Glasses in the Smart Factory: Product Evaluation Guidelines and Review of Available Products
23. Big Data Analysis in Smart Manufacturing: A Review
24. Cloud Manufacturing: A state-of-the-art survey of current issues10.1016/j.procir.2018.03.055 ↗
25. Industrial Communication Systems and Their Future Challenges: Next-Generation Ethernet, IIoT, and 5G10.1109/JPROC.2019.2913443 ↗
26. France, A.C.S. (2020, June 11). CyberFactory#1—Addressing Opportunities and Threats for the Factory of the Future (FoF). Available online: https://www.cyberfactory-1.org/en/project-description/.
27. Exploring the Opportunities of System of Systems Engineering to Complement Sustainable Manufacturing and Life Cycle Engineering10.1016/j.procir.2019.01.026 ↗
28. Cybersecurity for Digital Manufacturing10.1016/j.jmsy.2018.03.006 ↗
29. Multi-paradigm modelling of Cyber-Physical Systems10.1016/j.ifacol.2018.08.334 ↗
30. Hameed, B., Minguez, J., Wörner, M., Hollstein, P., Zor, S., Silcher, S., Dürr, F., and Rothemel, K. (2011, January 5–6). The Smart Real-Time Factory as a Product Service System. Proceedings of the 3rd CIRP International Conference on Industrial Product Service Systems, Braunschweig, Germany.10.1007/978-3-642-19689-8_57 ↗
31. Lee, E.-K., Lim, J.-H., and Kim, J. (2017). Prioritized access control enabling weighted, fine-grained protection in cyber-physical systems. Int. J. Distrib. Sens. Netw., 13.10.1177/1550147717748908 ↗
32. Ma, Z. (2019). Business ecosystem modeling- the hybrid of system modeling and ecological modeling: An application of the smart grid. Energy Inform., 35.10.1186/s42162-019-0100-4 ↗
33. Building an Industry 4.0 Analytics Platform10.1007/s13222-018-0273-1 ↗
34. Huang, L., Joseph, A.D., Nelson, B., Rubinstein, B.I.P., and Tygar, J.D. (2011). Adversarial machine learning. AISec ’11: Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence, ACM.10.1145/2046684.2046692 ↗
35. Dynamic Digital Human Models for Ergonomic Analysis Based on Humanoid Robotics Techniques10.1504/IJDH.2015.067135 ↗
36. Human-machine collaborative optimization via apprenticeship scheduling
37. Digital Twin in Industry: State-of-the-Art10.1109/TII.2018.2873186 ↗
38. Digital twin-driven product design, manufacturing and service with big data10.1007/s00170-017-0233-1 ↗
39. Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing10.1109/ACCESS.2017.2756069 ↗
40. Machines as teammates: A research agenda on AI in team collaboration10.1016/j.im.2019.103174 ↗
41. Unpredictability and Indeterminism in Human Behavior: Arguments and Implications for Educational Research10.2307/1174887 ↗
42. Digital twin-driven smart manufacturing: Connotation, reference model, applications and research issues10.1016/j.rcim.2019.101837 ↗
43. Importance of Simulation in Manufacturing
44. Supply chain optimization in context of production flow network10.1007/s11518-016-5304-6 ↗
45. Limits to decision-making ability in direct multiattribute alternative evaluation10.1016/0749-5978(88)90013-1 ↗
46. A Case Study for Blockchain in Manufacturing: “FabRec”: A Prototype for Peer-to-Peer Network of Manufacturing Nodes10.1016/j.promfg.2018.07.154 ↗
47. Schellenberger, C., and Zhang, P. (2017, January 12–15). Detection of covert attacks on cyber-physical systems by extending the system dynamics with an auxiliary system. Proceedings of the 56th IEEE Conference on Decision and Control (CDC), Melbourne, Australia.10.1109/CDC.2017.8263846 ↗
48. Hearn, M., and Rix, S. (2019). Cybersecurity Considerations for Digital Twin Implementations. IIC J. Innov.
49. Bécue, A., Fourastier, Y., Praça, I., Savarit, A., Baron, C., Gradussofs, B., Pouille, E., and Thomas, C. (2018, January 13–15). CyberFactory#1—Securing the industry 4.0 with cyber-ranges and digital twins. Proceedings of the 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy.10.1109/WFCS.2018.8402377 ↗
50. Van Zadelhoff, M. (2020, June 11). The Biggest Cybersecurity Threats Are Inside Your Company. Available online: https://hbr.org/2016/09/the-biggest-cybersecurity-threats-are-inside-your-company.
51. Slevin, B. (2020, April 28). How do you create a digital twin?. Available online: https://blogs.opentext.com/how-do-you-create-a-digital-twin/.
52. A Review of the Roles of Digital Twin in CPS-based Production Systems10.1016/j.promfg.2017.07.198 ↗
53. Vachálek, J., Bartalský, L., Rovný, O., Šišmišová, D., Morháč, M., and Lokšík, M. (2017, January 6–9). The digital twin of an industrial production line within the industry 4.0 concept. Proceedings of the 2017 21st International Conference on Process Control (PC), Strbske Pleso, Slovakia.10.1109/PC.2017.7976223 ↗
54. A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line10.1109/ACCESS.2017.2766453 ↗
55. The modelling and operations for the digital twin in the context of manufacturing10.1080/17517575.2018.1526324 ↗
56. Schluse, M., Atorf, L., and Rossmann, J. (2017, January 24–27). Experimentable digital twins for model-based systems engineering and simulation-based development. Proceedings of the 2017 Annual IEEE International Systems Conference (SysCon), Montreal, QC, Canada.10.1109/SYSCON.2017.7934796 ↗
57. Graessler, I., and Poehler, A. (2017, January 10–13). Integration of a digital twin as human representation in a scheduling procedure of a cyber-physical production system. Proceedings of the 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, Singapore.10.1109/IEEM.2017.8289898 ↗
58. Rovere, D., Pedrazzoli, P., dal Maso, G., Alge, M., and Ciavotta, M. (2019). A Centralized Support Infrastructure (CSI) to Manage CPS Digital Twin, towards the Synchronization between CPS Deployed on the Shopfloor and Their Digital Representation. The Digital Shopfloor: Industrial Automation in the Industry 4.0 Era, River Publishers.
59. Malakuti, S., van Schalkwyk, P., Boss, B., Sastry, C.R., Runkana, V., Lin, S.-W., Rix, S., Green, G., Beachle, K., and Nath, S.V. (2020, April 27). Digital Twins for Industrial Applications 2020. Available online: https://www.iiconsortium.org/pdf/IIC_Digital_Twins_Industrial_Apps_White_Paper_2020-02-18.pdf.
60. Boschert, S., and Rosen, R. (2016). Digital Twin—the Simulation Aspect. Mechatronic Futures, Springer International Publishing.10.1007/978-3-319-32156-1_5 ↗
61. Digital Twin for rotating machinery fault diagnosis in smart manufacturing10.1080/00207543.2018.1552032 ↗
62. About The Importance of Autonomy and Digital Twins for the Future of Manufacturing10.1016/j.ifacol.2015.06.141 ↗
63. Jain, S., and Lechevalier, D. (2016, January 11–14). Standards based generation of a virtual factory model. Proceedings of the 2016 Winter Simulation Conference (WSC), Washington, DC, USA.10.1109/WSC.2016.7822313 ↗
64. Defining a digital twin-based cyber-physical production system for autonomous manufacturing in smart shop floors10.1080/00207543.2019.1566661 ↗
65. An open source approach to the design and implementation of Digital Twins for Smart Manufacturing10.1080/0951192X.2019.1599436 ↗
66. Elias, M., Lazaro, O., Sepulcre, M., Gozalvez, J., Passarella, A., Raptis, T.P., Ude, A., Nemec, B., Rooker, M., and Kirstein, F. (2017). The AUTOWARE Framework and Requirements for the Cognitive Digital Automation, Springer International Publishing AG.
67. Gaspar, T., Denisa, M., and Ude, A. (2004). A reconfigurable robot workcell for quick set-up of assembly processes. arXiv.
68. Digital twins and cyber-physical systems toward smart manufacturing and Industry 4.0: Correlation and comparison10.1016/j.eng.2019.01.014 ↗
69. Digital Twin in manufacturing: A categorical literature review and classification10.1016/j.ifacol.2018.08.474 ↗
70. Digital Twin: Values, Challenges and Enablers from a Modeling Perspective
71. Post-processing and visualization techniques for isogeometric analysis results10.1016/j.cma.2016.10.040 ↗
72. Hrvoje, J., Jemcov, A., and Tukovic, Z. (2007, January 19–21). OpenFOAM: A C++ library for complex physics simulations. Proceedings of the International Workshop on Coupled Methods in Numerical Dynamics IUC, Dubrovnik, Croatia.
73. Wisniewski, M., Demartini, G., Malatras, A., and Cudé-Mauroux, P. (2013). NoizCrowd: A Crowd-Based Data Gathering and Management System for Noise Level Data, Springer.10.1007/978-3-642-40276-0_14 ↗
74. Security Services Using Blockchains: A State of the Art Survey10.1109/COMST.2018.2863956 ↗
75. A survey of machine learning for big data processing
76. A Survey on Deep Learning: Algorithms, Techniques, and Applications
77. Tripathi, S., Lipton, Z.C., and Nguyen, T.Q. (2018). Correction by Projection: Denoising Images with Generative Adversarial Networks. arXiv.
78. Rasheed, A., San, O., and Kvamsdal, T. (2019, January 24–25). Hybrid analysis and modeling as an enabler for big data cybernetics. Proceedings of the 32nd Nordic Seminar on Computational Mechanics, At Oulu, Finland.
79. Sensor fusion for mobile robot navigation10.1109/JPROC.1997.554212 ↗
80. A short review on model order reduction based on proper generalized decomposition10.1007/s11831-011-9064-7 ↗
81. Electric, G. (2020, June 09). GE Digital Twin. Available online: https://www.ge.com/digital/sites/default/files/download_assets/Digital-Twin-for-the-digital-power-plant-.pdf.
82. (2020, June 09). Core PLM Meets IoT and Augmented Reality. Available online: https://www.ptc.com/pt/products/plm/plm-products/windchill.
83. Karin (2020, June 09). What is a 3DEXPERIENCE Twin?. Available online: https://blogs.3ds.com/exalead/2019/07/01/what-is-3dexperience-digital-twin-part-1-12-2/.
84. (2020, June 09). Azure Digital Twins. Available online: https://azure.microsoft.com/en-gb/services/digital-twins/.
85. (2020, June 09). Seebo Industrial IoT Platform. Available online: https://www.seebo.com/iot-platform/.
86. (2020, June 09). AnyLogic Simulation Software. Available online: https://www.anylogic.com/.
87. (2020, June 09). Digital Twin. Available online: https://www.ansys.com/en-gb/products/systems/digital-twin.
88. (2020, June 09). Digital Twin: Helping Machines Tell Their Story. Available online: https://www.ibm.com/internet-of-things/trending/digital-twin.
89. (2020, June 10). Factoriy I/O Next-Gen PLC Training. Real Games. Available online: https://realgames.co/.
90. Wang, L., and Canedo, A.M. (2020, June 10). Human Programming Interfaces for Machine-Human Interfaces. Available online: https://patents.google.com/patent/US10416614B2/en.
91. SIEMENS (2020, June 10). The Comprehensive Digital Twin for Intralogistics. Available online: https://press.siemens.com/global/en/feature/intralogistics.
92. (2020, April 28). CPS Twinning. Available online: https://github.com/sbaresearch/cps-twinning.
93. Eckhart, M., and Ekelhart, A. (2018, January 15–19). A Specification-Based State Replication Approach for Digital Twins. Proceedings of the CCS '18: 2018 ACM SIGSAC Conference on Computer and Communications Security, Toronto, ON, Canada.10.1145/3264888.3264892 ↗
94. (2020, April 28). Wrld3d. Available online: https://www.wrld3d.com/.
95. Shin, S. (2020, April 28). Introduction to mago3D, an Open Source Based Digital Twin Platform. Available online: https://pt.slideshare.net/endofcap/introduction-to-mago3d-an-open-source-based-digital-twin-platform.
96. Strohmeier, F., Schranz, C., and Güntner, G. (2020, April 28). i-Maintenance: A Digital Twin for Smart Maintenance. Available online: https://ercim-news.ercim.eu/en115/special/2095-i-maintenance-a-digital-twin-for-smart-maintenance.
97. Roest, M. (2020, April 28). An Open Source Platform for Digital Twins?. Available online: https://www.linkedin.com/pulse/open-source-platform-digital-twins-mark-roest/.
98. (2020, April 28). Eclipse Ditto. Available online: https://www.eclipse.org/ditto/.
99. (2020, April 28). Create Immersive Connections with your Infrastructure Digital Twin. Available online: https://www.imodeljs.org/.
100. AUTODESK (2020, June 09). Finite Element Analysis Software. Available online: https://www.autodesk.co.uk/solutions/finite-element-analysis.