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This study presents the development of a soft sensor-based digital twin (DT) aimed at reducing startup times in the manufacturing of PVC tubes while enabling real-time monitoring of product quality. The DT utilizes machine learning algorithms trained on data from an experimental campaign to optimize the extrusion process and achieve customer specifications efficiently. The findings demonstrate that the DT significantly enhances process efficiency by minimizing material waste and labor costs during the compl

Author

Pallavi Bhatnagar

Language

EN