FPGA-Based Digital Twin Implementation for Mechatronic System Monitoring

Digital Twin is a driving technology for Industry 4.0 that enables novel capabilities like smart process control, fault detection, or remaining useful life estimation. Since a Digital Twin is an up-to-date representation of an actual physical process, building this model requires exchanging many datasets from the physical assets. Usually, it is performed on external servers within a cloud-computig architecture that communicates physical assets with the digital twin model. However, the cloud exchange introduces transmission delays and security and data privacy issues that hamper digital asset updates and create safety concerns. Hence, we propose an FPGA-based digital twin implementation where the datasets are taken directly from the physical asset running parallel to the digital asset. This setup eliminates the need for big data and cloud upload, ensuring data privacy and faster, efficient digital twin implementation and update. A case study is implemented to demonstrate embedded Digital Twin capabilities for monitoring mechatronic systems under fault events.