CREATION OF DIGITAL TWINS - KEY CHARACTERISTICS OF PHYSICAL TO VIRTUAL TWINNING IN MECHATRONIC PRODUCT DEVELOPMENT

Abstract Due to the falling costs of computational resources and the increasing potential of data acquisition, interest in digital twins, a virtual copy of the physical original, and their industrial application is increasing. Nevertheless, there is limited published work on how to support the process of physical to virtual twinning and what its key aspects are. The aim of this study is to present insights with regards to physical to virtual twinning gained from modelling projects in mechatronic product development. We conducted a survey and in-depth interviews with members of modelling projects. In the surveys and interviews we identified how physical products and virtual models were linked, which virtual models were used and which general challenges and key aspects are considered important by the project members. Our findings show that the key characteristics that pose challenges to modelling regarding physical to virtual twinning are model granularity, model validation, and model integration and interconnectivity.

[1]  Patric Grauberger,et al.  QUALITATIVE MODELLING IN EMBODIMENT DESIGN - INVESTIGATING THE CONTACT AND CHANNEL APPROACH THROUGH ANALYSIS OF PROJECTS , 2020 .

[2]  Sandro Wartzack,et al.  Geometrical Variations Management 4.0: towards next Generation Geometry Assurance , 2018 .

[3]  Edward H. Glaessgen,et al.  The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles , 2012 .

[4]  Roland Rosen,et al.  About The Importance of Autonomy and Digital Twins for the Future of Manufacturing , 2015 .

[5]  Ben Hicks,et al.  A FRAMING OF DESIGN AS PATHWAYS BETWEEN PHYSICAL, VIRTUAL AND COGNITIVE MODELS , 2020, Proceedings of the Design Society: DESIGN Conference.

[6]  Patric Grauberger,et al.  Product models in embodiment design: an investigation of challenges and opportunities , 2019, SN Applied Sciences.

[7]  Stefan Boschert,et al.  Digital Twin—The Simulation Aspect , 2016 .

[8]  Benjamin Haefner,et al.  Function-oriented measurements and uncertainty evaluation of micro-gears for lifetime prognosis , 2017 .

[9]  Jakob F. Maier,et al.  Model granularity in engineering design – concepts and framework , 2017, Design Science.

[10]  Sandro Wartzack,et al.  Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products , 2019, Procedia CIRP.

[11]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[12]  Sven Matthiesen,et al.  From Reality to Simulation – Using the C&C2-Approach to Support the Modelling of a Dynamic System , 2018 .

[13]  Michael W. Grieves,et al.  Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems , 2017 .

[14]  Sandro Wartzack,et al.  Shaping the digital twin for design and production engineering , 2017 .

[15]  S. Wartzack,et al.  WiGeP-Positionspapier: „Digitaler Zwilling“ , 2020 .

[16]  Rikard Söderberg,et al.  Toward a Digital Twin for real-time geometry assurance in individualized production , 2017 .

[17]  Jason Yon,et al.  Characterising the Digital Twin: A systematic literature review , 2020, CIRP Journal of Manufacturing Science and Technology.

[18]  Rikard Söderberg,et al.  An information and simulation framework for increased quality in welded components , 2018 .