Smart manufacturing, tailored by the 4th industrial revolution and forces like innovation, competition, and changing demands, lies behind the concurrent evolution (also known as co-evolution) of products, processes and production systems. Manufacturing companies need to adapt to ever-changing environments by simultaneously reforming and regenerating their product, process, and system models as well as goals and strategies to stay competitive. However, the ever-increasing complexity and ever-shortening lifecycles of product, process and system domains challenge manufacturing organization’s conventional approaches to analysing and formalizing models and processes as well as management, maintenance and simulation of product and system life cycles. The digital twin-based virtual factory (VF) concept, as an integrated simulation model of a factory including its subsystems, is promising for supporting manufacturing organizations in adapting to dynamic and complex environments. In this paper, we present the demonstration and evaluation of previously introduced digital twin-based VF concept to support modelling, simulation and evaluation of complex manufacturing systems while employing multi-user collaborative virtual reality (VR) learning/training scenarios. The concept is demonstrated and evaluated using two different wind turbine manufacturing cases, including a wind blade manufacturing plant and a nacelle assembly line. Thirteen industry experts who have diverse backgrounds and expertise were interviewed after their participation in a demonstration. We present the experts’ discussions and arguments to evaluate the DT-based VF concept based on four dimensions, namely, dynamic, open, cognitive, and holistic systems. The semi-structured conversational interview results show that the DT-based VF stands out by having the potential to support concurrent engineering by virtual collaboration. Moreover, DT-based VF is promising for decreasing physical builds and saving time by virtual prototyping (VP).
|Tidsskrift||International Journal of Advanced Manufacturing Technology|
|Status||Udgivet - mar. 2021|
Bibliografisk noteFunding Information:
The research presented in this article was funded by the Manufacturing Academy of Denmark (MADE) and Vestas Wind Systems A/S, including equipment support (Grant: 6151-00006B). This work was also partially supported by the “Virtual EnvironmentS for optimisation and trAining in induStry 4.0 (VESTAS 4.0)” project financed by the North Portugal Regional Operational Programme (NORTE 2020–01/SI/2018) (Grant: POCI-01-0247-FEDER-038524). The authors of this article also would like to thank FlexSim for supporting our research by providing the licence free of charge.
© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature.