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7351 |
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Wednesday, May 04, 2022, Hall G1 11:30 AM Modeling & Simulation I |
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Spraying parameters selection based on predicted equipment status: A study on measured voltage |
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Majid Nabavi / Oerlikon Metco AG, Switzerland Xavier Guidetti* / ETH Zürich University, Switzerland Ehsan Fallahi/ Oerlikon Metco, Switzerland John Lygeros/ ETH Zürich University, Switzerland Alisa Rupenyan/ ETH Zürich University, Switzerland |
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Previous work conducted on atmospheric plasma spraying has shown the importance of including the measured gun voltage in the modeling procedure to improve the outputs prediction quality. Given a set of controllable input parameters, the produced coating specifications are influenced by the gun voltage measured during the spraying process. As the gun voltage can only be measured once the coating process has started, making predictions about the expected voltage is necessary to better select the process inputs that produce a coating with desired specifications. We suggest that the gun voltage is related to the status of the manufacturing equipment. Exploiting voltage information, we propose a modeling and configuration procedure that uses Gaussian process regression and Kalman filtering to reduce the impact of session-to-session equipment changes as well as in-session equipment wearing. We then demonstrate this approach in simulation and experiments, using an industrial atmospheric plasma spraying set-up to produce TBC coatings with F4 gun. |