Abstract
Complex systems that link virtualization and simulation platforms with actual data from industrial processes are vital for the next generation of production. Digital twins are such systems that have several advantages, notably in manufacturing where they can boost productivity throughout the whole manufacturing life-cycle. Enterprises will be able to creatively, efficiently, and effectively leverage implicit information derived from the experience of current production processes, thanks to cognitive digital twins. The development of numerous technologies has made the digital twin notion more competent and sophisticated throughout time. This article proposes a heuristic approach for cognitive digital twin technology as the next development in a digital twin that will aid in the realization of the goal of Industry 4.0. In creating cognitive digital twins, this article suggests the use of a heuristic approach as a possible route to allowing cognitive functionalities. Here, heuristic optimization is proposed as a feature selection tool to enhance the cognitive capabilities of a digital twin throughout the product design phase of production. The proposed approach is validated using the use-case of Power Transfer Unit (PTU) production, which resulted in an improvement of 8.83% in classification accuracy to predict the faulty PTU in the assembly line. This leads to an improved throughput of the PTU assembly line and also saves the resources utilized by faulty PTUs.
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Acknowledgment
This work was supported in part by the project DIGICOGS project which is financed by Vinnova (Vinnovas Diarienr: 2019-0532) and the innovation program Process Industrial IT and Automation (PiiA) at Mälardalen University.
The authors would like to thank Michael Osbakk, Mikael Eriksson, Jonathan Widén, Jimmy Vesa, and ‘GKN Drive line’ for all the help and support during this study.
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A Details of Features Taken from the PTU Manufacturing Process
A Details of Features Taken from the PTU Manufacturing Process
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Rehman, A.u., Ahmed, M.U., Begum, S. (2023). Cognitive Digital Twin in Manufacturing: A Heuristic Optimization Approach. In: Maglogiannis, I., Iliadis, L., MacIntyre, J., Dominguez, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2023. IFIP Advances in Information and Communication Technology, vol 676. Springer, Cham. https://doi.org/10.1007/978-3-031-34107-6_35
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