A Digital Twin for estimating Process Quality during Automated Fiber Placement of Thermoplastic Composites
The digital twin (DT) is a methodology accelerating process knowledge for the automated fiber placement (AFP) of unidirectional thermoplastic tape with in-situ consolidation. It implies a continuous assessment and evaluation of data allowing a faster process optimization and reducing ramp-up times. This study visualizes measured data within an automated digital shadow and combines it with analytical models for the AFP of thermoplastic composite blanks with in-situ consolidation. A DT combining analytical and experimental data is created visualizing quality indicators of a thermoplastic composite blank during manufacturing. In this study, a model predicting the degree of bonding is selected calculated based on the measured temperature data. The results show how a DT enables an easy and systematic method to analyse and optimize the AFP processing. It is a promising tool for automatizing process analysis and part quality estimation during the manufacturing of composite parts.