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 |
Profit-Driven Methodology for Servo Press Motion Selection Under Material Variability |
Author(s) |
Luke Mohr, Nozomu Okuda, Alex Kitt, Hyunok Kim |
On-Site Speaker (Planned) |
Luke Mohr |
Abstract Scope |
Servo presses enable new types of forming motion profiles that can be used to stamp difficult materials such as high strength steels. EWI's newly-developed Smart Forming Algorithm is an application of Bayesian statistics to intelligently select which motion profile maximizes the expected utility given the properties of the incoming material. Bayesian logistic regression is used in conjunction with expected utility to estimate manufacturing returns, which can be used to make informed process decisions. This presentation will describe the statistical methodology used to build the algorithm, how an operator can interpret results from the algorithm to influence process decisions, and a use case which demonstrates that this approach can increase expected returns by more than 20%. |
Proceedings Inclusion? |
Undecided |