Microservice-based digital twin system towards smart manufacturing

Abstract

Digital Twin (DT) is a promising technology that offers versatile services to enhance manufacturing intelligence. However, the agility, reliability and analysis capabilities of existing DT services are severely challenged when applied and deployed at large-scale production lines. To address the aforementioned issues, a microservice-based DT system with redundant architecture is proposed. First, a scalable microservice-based DT system compatible with standard and tailored plug-and-play DT services is constructed for DT protocol adaptation, stream processing, information and model management. Concurrently, a generic information model is proposed to represent the entire production lifecycle from design, operation, and maintenance in a structured manner. Second, an industrial multi-task DT model is introduced, leveraging the aforementioned architecture, to effectively achieve parallel monitoring of surface roughness and tool wear. Finally, industrial manufacturing cases are introduced to verify the feasibility and effectiveness of the proposed system. The results show that heterogeneous DT data are transferred and managed reliably, with a mean absolute percentage error of 1.28% for surface roughness prediction, and 85.71% accuracy in tool wear diagnosis.