Abstract
The subject discussed in this article concerns the determination of optimal sensor (pressure & temperature) configurations for polymer injection moulds. A sensor configuration is considered optimal when it is able to predict the product quality (dimension, warpage, etc.) with a good accuracy (from experimental data provided by these sensors). Initially, plastic engineers integrated sensors in moulds to acquire knowledge about their processes and to have better understanding of physical phenomenon. This article presents a numerical methodology to identify optimal combinations of sensors. The methodology is firstly based on polymer injection molding simulation to collect virtual sensor data. In a second step, virtual sensor data are analyzed by modern data-driven modeling techniques to identify optimal sensor configurations.
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