Maderthaner, J., Kugi, A., & Kemmetmüller, W. (2023). Optimal control of the part mass for the injection molding process. Journal of Process Control, 129, Article 103027. https://doi.org/10.1016/j.jprocont.2023.103027
E376-02 - Forschungsbereich Komplexe Dynamische Systeme E376 - Institut für Automatisierungs- und Regelungstechnik
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Journal:
Journal of Process Control
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ISSN:
0959-1524
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Date (published):
Sep-2023
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Publisher:
ELSEVIER SCI LTD
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Peer reviewed:
Yes
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Keywords:
optimal control; Nonlinear Model Predictive Control (NMPC); Injection Molding; quadratic programming; model predictive control
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Abstract:
Injection molding is one of the most important processes to manufacture plastic goods. During the long production times, process variations might lead to a varying product quality. Therefore, in the state of the art, the machine variables of injection molding machines (e. g. the barrel temperature and the screw speed) are controlled to suppress these variations. However, the influence of changes of the raw material on the part quality cannot be systematically suppressed with state-of-the-art controllers. In this work, a novel control concept is proposed where the part mass is controlled instead of the usual machine variables. The control strategy is based on an estimation of the plastics mass in the mold. In order to account for the system nonlinearities, a model predictive control strategy is developed for both the filling and the holding-pressure phase. The feasibility and the benefits of this proposed part-mass control strategy is evaluated by a series of measurements on an electric injection molding machine.
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Research Areas:
Mathematical and Algorithmic Foundations: 70% Modeling and Simulation: 30%