Building a cloud-based digital twin for remote monitoring and control of a robotic assembly system

The potential of digital twin (DT) technology to revolutionize industry by enabling virtual simulations of physical systems in real-time has garnered significant attention in recent years. DTs have been widely applied in the manufacturing field to solve various problems, such as shopfloor resource optimization, layout design, commissioning, monitoring, and supervisory control. Cloud-based DT (CBDT) is an emerging concept and shows promise in achieving enhanced remote accessibility, data processing and analysis capabilities, and scalability. However, current CBDT research is still very limited and mainly focuses on theoretical framework that leverages cloud computing advantages in data processing aspects. Yet, practical implementation with technical details for creating a CBDT of a complex manufacturing system is rarely reported, and the interactions between cloud infrastructure and DT modeling and visualization are scarcely investigated. To fill the gaps, this paper first proposes a general CBDT framework for supporting smart manufacturing services. This framework features the integration of modularized cloud intelligence, DT modeling, and DT visualization to achieve enhanced remote accessibility. Moreover, a prototyping system that entails the CBDT-enabled remote monitoring and control services is implemented for a legacy robotic assembly system to partially showcase the process of the proposed framework. The usefulness and remote accessibility of the developed CBDT-based prototype system is further demonstrated with web-based functionalities such as assembly job status update, real-time 3-dimensional DT visualization and simulation of assembly tasks, and remote feedback control over the physical system. Lastly, the prototype system is built upon open-source toolkits (e.g., WebGL) and low-cost commercial software platforms (e.g., Unity and Google Cloud Platform), which could potentially open new opportunities for aiding small-to-medium companies for digital transformation. Future works and limitations are also discussed in the end.