Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems

Abstract

Metal Additive Manufacturing (AM) has been attracting a continuously increasing attention due to its great advantages compared to traditional subtractive manufacturing in terms of higher design flexibility, shorter development time, lower tooling cost, and fewer production wastes. However, the lack of process robustness, stability and repeatability caused by the unsolved complex relationships between material properties, product design, process parameters, process signatures, post AM processes and product quality has significantly impeded its broad acceptance in the industry. To facilitate efficient implementation of advanced data analytics in metal AM, which would support the development of intelligent process monitoring, control and optimisation, this paper proposes a novel Digital Twin (DT)-enabled collaborative data management framework for metal AM systems, where a Cloud DT communicates with distributed Edge DTs in different product lifecycle stages. A metal AM product data model that contains a comprehensive list of specific product lifecycle data is developed to support the collaborative data management. The feasibility and advantages of the proposed framework are validated through the practical implementation in a distributed metal AM system developed in the project MANUELA. A representative application scenario of cloud-based and deep learning-enabled metal AM layer defect analysis is also presented. The proposed DT-enabled collaborative data management has shown great potential in enhancing fundamental understanding of metal AM processes, developing simulation and prediction models, reducing development times and costs, and improving product quality and production efficiency.

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“…DebRoy et al and Knapp et al [49,50] provided a perspective of building blocks of the additive manufacturing process modeling and simulation at multiple scales. Liu et al [51] proposed a collaborative data management framework for metal additive manufacturing systems. Cai et al [52] used the augmented reality technique to communicate the layout information between a reconfigurable additive manufacturing system made of robotic arms and its corresponding digital Transactions of the ASME twin for toolpath planning and simulation.…”