Enhancing Manufacturing with AI-powered Process Design

Enhancing Manufacturing with AI-powered Process Design

Gianmarco Genalti, Gabriele Corbo, Tommaso Bianchi, Marco Missaglia, Luca Negri, Andrea Sala, Luca Magri, Giacomo Boracchi, Giovanni Miragliotta, Nicola Gatti

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Demo Track. Pages 8665-8668. https://doi.org/10.24963/ijcai.2024/1004

Manufacturing companies are experiencing a transformative journey, moving from labor-intensive processes to integrating cutting-edge technologies such as digitalization and AI. In this demo paper, we present a novel AI tool to enhance manufacturing processes. Remarkably, our work has been developed in collaboration with Agrati S.p.A., a worldwide leading company in the bolts manufacturing sector. In particular, we propose an AI-powered tool to address the problem of automatically generating the production cycle of a bolt. Currently, this decision-making task is performed by process engineers who spend several days to study, draw, and test multiple alternatives before finding the desired production cycle. We cast this task as a model-based planning problem, mapping bolt technical drawings and metal deformations to, potentially continuous, states and actions, respectively. Furthermore, we resort to computer vision tools and visual transformers to design efficient heuristics that make the search affordable in concrete applications. Agrati S.p.A.'s process engineers extensively validated our tool, and they are currently using it to support their work. To the best of our knowledge, ours is the first AI tool dealing with production cycle design in bolt manufacturing.
Keywords:
Planning and Scheduling: PS: Applications
Search: S: Heuristic search