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UMINF 19.09

An AI-enabled assembly support system for industrial production

In this report, we present a prototype assembly support system for hydraulic components, tailored to a mechanical industry production plant. The case study for the project is Komatsu Forest, a leading provider of forestry machines. The system uses multimodal data analysis to understand the assembly process and detect errors. In particular, it uses a TensorFlow network to identify hydraulic components, a projective computer vision model to map a CAD drawing against the partial assembly, and natural language processing techniques to recognise patterns in the non-conformance reports.

Keywords

Assembly support, Machine learning, Multimodal analysis

Authors

Mona Forsman , Benjamin Björklund , Henrik Bjorklund and Johanna Bjorklund

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Entry responsible: Johanna Bjorklund

Page Responsible: Frank Drewes
2021-11-28