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 application 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 application 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, this is the first example of an AI application dealing with production cycle design in bolt manufacturing

Enhancing Manufacturing with AI-powered Process Design

Genalti G.;Corbo G.;Bianchi T.;Magri L.;Boracchi G.;Miragliotta G.;Gatti N.
2024-01-01

Abstract

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 application 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 application 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, this is the first example of an AI application dealing with production cycle design in bolt manufacturing
2024
International Joint Conference on Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1279177
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