Projects References: [1] Trauer, J., Schweigert-Recksiek, S., Engel, C., Spreitzer, K., Zimmermann, M. (2020): What is a Digital Twin? Definitions and insights from an industrial case study in technical product development. In Proceedings of the Design Society: DESIGN Conference, Vol. 1, pp. 757- 766 [2] Stark, R., Damerau, T. (2019): Digital Twin. In Chatti, S., Tolio, T. (Eds.): CIRP Encyclopedia of Production Engineering, Vol. 66, Springer Berlin Heidelberg, pp. 1-8. https://doi.org/10. 1007/978-3-642-35950-7_16870-1 [3] Grieves, M., Vickers, J. (2017): Digital Twin: Mitigating Unpredictable, Undesirable Emer- gent Behavior in Complex Systems. In Kahlen, F.-J., Flumerfelt, S., Alves, A. (Eds.): Transdisci- plinary perspectives on complex systems: New findings and approaches. Springer, pp. 85- 113. https://doi.org/10.1007/978-3-319- 38756-7_4 [4] Kritzinger, W., Karner, M., Traar, G., Henjes, J., Sihn, W. (2018): Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, Vol. 51 No. 11, pp. 1016- 1022. https://doi.org/10.1016/j.ifacol.2018. 08.474 [5] Zukunftsinstitut GmbH (2022): Die Megatrends. https://www.zukunftsinstitut.de, 12.12.2022 [6] Velosa A., Kutnick D., Lheureux B., Williams R. (2020): Hype Cycle for the Internet of Things. G00441743, Gartner Inc. [7] Trauer J., Mutschler M., Mörtl M., Zimmermann M. (2022): Challenges in Implementing Digital Twins – a Survey, Volume 2. 42nd Computers and Information in Engineering Conference (CIE), American Society of Mechanical Engineers [8] Stürken, M., Kirsch, M. (2021): Digital Data Package (DDP). ProduktDaten Journal 2021-2 [9] OASIS Open Projects (2021): OSLC Core Version 3.0. Part 1: Overview. OASIS Standard, 26 August 2021 [10] Catena-X Automotive Network e.V. (2022): Catena-X Operating Model Whitepaper. Release V2, 21.11.2022 [11] Haas, U. (2021): Management of Simulation Data within PLM@DC. Darmstadt, Engineering Process Day 2021 [12] Handschuh, S. (2022): Engineering IT Standards enabling Digital Twin Collaboration. Darmstadt, Engineering Process Day 2022 [13] Körte, P. (2022): Digitale Dekarbonisierung – Doppelte Chance für Europas Industrie. Indu- stry Forward Summit 2022 Contact Dr. Marcus Krastel :em engineering methods AG marcus.krastel@em.ag 2022-2 ProductDataJournal 17 Outlook – Collaborative Digital Twins Although, as described above, each company has challenges of its own to surmount, there are also issues that require collaboration across company boundaries. Therefore, the first associa- tions and interest groups are being created with the aim of developing the various aspects of the Digital Twin and drawing up standards. The Digital Twin will now also find a new home in the prostep ivip Association. In the future, the Collaborative Digital Twins (CDT) project group is where activities relevant to designing and implementing the Digital Twins will converge. The aim is to develop a definition of the term and a common understanding of the content of Digital Twins from the perspective of the prostep ivip Association and its member companies and to bundle activities currently being carried out. A common semantic data model for Digital Twins is crucial. The greatest benefit comes from integrating the data from the different Digital Twins through- out the product lifecycle. IT capabilities for linking data and for data integration/federation must be provided. Cross-departmental configura- tion management for the product during and after development and through to the use phase needs to be established. Advanced simulation and systems engineering methods can lead to a shorter time-to-market. They are also a prerequisite for safeguarding competitive capabilities by meeting higher customer requirements regarding data delivery for the Digital Twin (simulation models) and requirements for auditing suppliers (traceability of digital information, security standards). In addition to its importance in the con- text of achieving sustainability targets [13], an existing Digital Twin can at the same time give rise to new business models. The representation of a system and its environment, cross-enterprise Ddigital Twins and the use of the twin for environmental indicators (e.g. the carbon footprint) offer companies enormous potential.