Development of Data-Driven Digital Twin for Real-Time Monitoring of FDM 3D Printer

Abstract

Fused deposition modelling (FDM) and digital twinning are considered important areas to the future of manufacturing. However, both technologies still face major challenges to their adoption. Errors in printed products are still common in FDM, while cost and gaps in knowledge and technology have made digital twins inaccessible for many. This paper presents the design and use of a data-driven digital twin of an FDM 3D (three dimensional) printer that was used to monitor the motions of a 3D printer in real-time. Sensors attached to the physical 3D printer were used to gather motion data for the virtual 3D printer modelled in Siemens NX. Communication to the virtual printer was handled by a Modbus server and an OPC-DA (Open Platform Communications—Data Access) server. Tests were performed to evaluate the virtual 3D printer’s ability to monitor the real 3D printer’s movements in real-time, the relationship between the printer’s motions and the generated vibration signals, and the digital twin’s ability to repeat the motions from past printing sessions using logged data (history tracking). The results showed that a virtual 3D printer can be used to monitor the motions of an FDM 3D printer in real-time with a maximum average time lag of 0.351 seconds. The vibration patterns generally reflected the state of the physical system. Lastly, the history tracking feature was able to repeat the motions from previous printing sessions using the logged data but introduced some extra lag.