A digital twin framework for prediction, monitoring, and diagnosis in copper tube extrusion
Year: 2024
Type: conference-paper
Abstract: . The strict quality requirements, the increased production rates, variability, and volume constitute challenges in the quality of extruded profiles. State-of-practice methods cannot track down or mitigate all the product features and defects, thus increasing scrap generation and reducing production flexibility. Nevertheless, State-of-the-art approaches are few and dedicated to the product rather than the actual process with the last being researched in terms of process modeling. This study assesses the adoption level of I4.0 technologies in extrusion applications and it applies well-established practices across manufacturing to outline a Digital Twin framework for Prediction, Monitoring, and Diagnosis in the case of copper tube extrusion.
Source: Materials research proceedings
Author: Kyriakos SABATAKAKIS
Institution: University of Patras
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4404993535