About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Presentation Title |
Effects of Complex Die Cast Manufacturing Systems and the Critical Error Threshold on Applications of Machine Learning in Production |
Author(s) |
David J. Blondheim |
On-Site Speaker (Planned) |
David J. Blondheim |
Abstract Scope |
Research in machine learning (ML) for manufacturing processes is often applied to highly specific applications, typically with a focus on part quality predictions. This research is then completed in limited production settings or academic facilities. There is difficulty scaling these findings within manufacturing plants. Production manufacturing environments should be understood as highly complex systems when applying machine learning. System complexity, combined with the high-quality performance of most manufacturing systems currently achieve, means ML must exceed a Critical Error Threshold (CET) in accuracy to provide value of implementing ML in a manufacturing organization. This work will review system complexity and the CET to explain the difficulty in successful ML applications for quality predictions in die casting. Guidance on other ML applications in die casting will also be provided. |
Proceedings Inclusion? |
Undecided |