Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T12:42:22.609Z Has data issue: false hasContentIssue false
  • English
  • Français

PRODUCT LIFE CYCLE MANAGEMENT WITH DIGITAL TWINS FOR PRODUCT GENERATION DEVELOPMENT

Published online by Cambridge University Press:  19 June 2023

Lars Arnemann ,
Sven Winter ,
Niklas Quernheim  and
Benjamin Schleich
Lars Arnemann*
Affiliation:
Product Life Cycle Management (PLCM), TU Darmstadt
Sven Winter
Affiliation:
Product Life Cycle Management (PLCM), TU Darmstadt
Niklas Quernheim
Affiliation:
Product Life Cycle Management (PLCM), TU Darmstadt
Benjamin Schleich
Affiliation:
Product Life Cycle Management (PLCM), TU Darmstadt
*
Arnemann, Lars, TU Darmstadt, Germany, arnemann@plcm.tu-darmstadt.de

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Digital Twins are virtual representations of a product-service-instance and, as a technology, represent an important part of the realization of Industry 4.0. They manage data of the associat-ed product instance and can also have functions for simulation to achieve cost and resource savings while simultaneously increasing product quality. In this paper, a need for action for the implementation of a systematic approach for the returning of data of Digital Twins into the product design is identified and a methodology is developed as an answer. This methodology realizes an information management, which supports holistic data and information flows. It de-fines necessary steps for the implementation of data and information transport, starting from a data management up to information provision in product design. Based on a performed potential analysis for the identification of intended uses in the context of product design, the overall ap-plication focus is narrowed down to the development of new product generations to support the requirements development. The concept structure consists of Digital Twins, a data mining sys-tem for the transformation of data into information and a presentation system for managing the information provided.

Keywords

Product Lifecycle Management (PLM)Design engineeringDesign methods
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2955 - 2964
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Czwick, C., Martin, G., Anderl, R. and Kirchner, E. (2020), “Cyber-Physische Zwillinge”, Zeitschrift für wirtschaftlichen Fabrikbetrieb, No. s1, pp. 90–93.CrossRefGoogle Scholar
Grieves, M. (2014), Digital Twin: Manufacturing Excellence through Virtual Factory Replication.Google Scholar
Lim, K.Y.H., Zheng, P. and Chen, C.-H. (2020), “A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives”, Journal of Intelligent Manufacturing, Vol. 31 No. 6, pp. 1313–1337.CrossRefGoogle Scholar
Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.-H. (2007), Konstruktionslehre: Grundlagen erfolgreicher Produktentwicklung; Methoden und Anwendung, 7. Aufl., Springer, Berlin, Heidelberg.Google Scholar
Riedelsheimer, T., Lindow, K. and Stark, R. (2018), Feedback to design with digital lifecycle-twins: literature review and concept presentation.Google Scholar
Ross, D.T. (1977), “Structured Analysis (SA): A Language for Communicating Ideas”, IEEE Transactions on Software Engineering, SE-3 No. 1, pp. 16–34.CrossRefGoogle Scholar
Rothfuss, G. and Ried, C. (Eds.) (2001), Content Management mit XML: Grundlagen und Anwendungen, Xpert.press, Springer Berlin Heidelberg, Berlin, Heidelberg.CrossRefGoogle Scholar
Samarjiwa, M., Lindow, K., Salomon, D. and Stark, R. (2020), Digital Twin Readiness Assessment: Eine Studie zum Digitalen Zwilling in der fertigenden Industrie.Google Scholar
Schleich, B., Anwer, N., Mathieu, L. and Wartzack, S. (2017), “Shaping the digital twin for design and production engineering”, CIRP Annals, Vol. 66 No. 1, pp. 141–144.CrossRefGoogle Scholar
Schuh, G., Anderl, R., Dumitrescu, R., Krüger, A. and Hompel, M. ten (Eds.) (2020), Industrie 4.0 Maturity Index: Die digitale Transformation von Unternehmen gestalten, Update 2020, acatech - Deutsche Akademie der Technikwissenschaften, München and Berlin and Brüssel.Google Scholar
Sebastian Haag, Klaus Schützer and Zancul, Eduardo (2017), “Digital twin technology – An approach for Industrie 4.0 vertical and horizontal lifecycle integration”, it - Information Technology, No. 3, pp. 125–132.Google Scholar
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Guo, Z., Lu, S.C.-Y. and Nee, A.Y.C. (2019), “Digital twin-driven product design framework”, International Journal of Production Research, Vol. 57 No. 12, pp. 3935–3953.CrossRefGoogle Scholar
WiGeP (2020), “WiGeP-Position Paper - Digital Twin”, available at: https://b7s1f6.n3cdn1.secureserver.net/wp-content/uploads/2022/05/Final_WiGeP_Positionspapier_Digital_Twin_englisch.pdf (accessed 23 February 2023).Google Scholar