In Situ Calibration Algorithm to Optimize Energy Consumption in an Automotive Stamping Factory Process

PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (ICINCO)(2022)

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Abstract
The world's large factories in all sectors consume a great deal of resources, either raw materials or energy, to develop their products. Saving resources can have a positive impact on the sustainable development of the planet. Automotive manufacturers are a clear example of how to save by investing resources in improving technologies and optimizing processes. This article focuses on one of the most common processes in the automotive sector: the stamping process. For the optimization of this process, previous simulations are usually carried out in order to define the optimal parameters and which should only be applied for a correct operation. The real circumstances of the plant show there is a large discrepancy between the parameters obtained by simulation and the real process because of the difference in material properties, lubrication, press operation, etc. The solution is that the operators must adjust the parameters a posteriori and the only criterion to follow is obtaining the right quality of the part. In many cases, the parameters are well above the ideal. This article presents some algorithms used in order to perform an in situ calibration of the stamping presses to find the press parameters that, guaranteeing the quality of the part, allow to adjust the energy consumption to the minimum. At the end of this article the experimental results from this in-situ calibration process and the energy savings are shown.
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Key words
Predictive Maintenance, Machine Health Monitoring, Energy Consumption, IIoT, Sustanibale Development, In Situ Calibration
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