Towards Real-time Process Monitoring and Machine Learning for Manufacturing Composite Structures
Simon Stieber, Alwin Hoffmann, Alexander Schiendorfer, Wolfgang Reif, Matthias Beyrle, J.S. Faber Faber, Michaela Richter, Markus G. R. Sause
Abstract
Components made from carbon fiber reinforced plastics (CFRP) offer attractive stability properties for the automotive or aerospace industry despite their light weight. To automate CFRP production, resin transfer molding (RTM) based on thermoset plastics is commonly applied. However, this manufacturing process has its shortcomings in quality and costs. The project CosiMo aims for a highly automated and cost-attractive manufacturing process using cheaper thermoplastic materials. In a thermoplastic RTM (T-RTM) process, the polymerization of ε-caprolactam to polyamide 6 is investigated using an intelligent mold tooling. Multiple sensor types integrated into the mold allow for tracking of process-relevant variables, such as material flow and polymerization state. In addition to monitoring the T-RTM process, a digital twin visualizes progress and makes predictions about issues and countermeasures based on machine learning.