Work

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

Year: 2025

Type: conference-paper

Abstract: 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.

Source: International Conference on Control, Decision and Information Technologies (CoDIT)

DOI: 10.1109/codit66093.2025.11321707

Authors: Wenxuan Hu, Zhuoxuan Cao, Achraf El Messaoudi, Peilin Li, Zhiguo Zeng

Institutions: Sorbonne Université, Université Paris-Saclay, CentraleSupélec, Laboratoire Génie Industriel

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Quality education

Open Access status: green

Funder: Agence Nationale de la Recherche