A desktop learning factory for smart and resilient manufacturing based on digital twin and AI

Learning factories have been increasingly applied in engineering research and education. In this paper, we develop a small-scale, low-cost, fully open-sourced learning factory that leverages AI and digital twins to demonstrate smart and resilient manufacturing. The learning factory consists of an AGV, three robots, two conveyors and their digital twins. Three typical use cases are designed to demonstrate the capabilities of the learning factory, i.e., material sorting through computer vision-based robot control, coordinating AGV, robots and conveyors for assembly, and digital twin-driven predictive maintenance. The results show that the developed learning factory can adequately support the teaching and research activities on digital twins and AI on manufacturing. Its fully open-source architecture and relatively low deployment cost make it an ideal solution for universities and research institutions.