Development of a methodology for the detection of forming defects in continuous fiber-reinforced thermoplastics using optical image processing

Due to the combination of advantages such as high lightweight construction potential, recyclability, weldability and, in particular, short cycle times in component production, continuous fiber-reinforced thermoplastics are increasingly being used in aviation. The stamp forming process can be used to manufacture the components. However, the aviation industry in particular places the highest demands on component quality and forming defects, which can be partially tolerated in other industries, must be avoided through optimized process control. However, some forming defects can only be identified with great effort and in expensive test procedures. For rapid process optimization, however, a way is needed to detect and quantify forming defects quickly, cost-effectively and reliably.

A promising possibility to detect forming defects in a quantifiable way, and thus usable for process optimization, is to apply surface patterns to the starting material and to analyze the resulting pattern after forming using optical image processing methods. For this purpose, different patterns that allow clear tracking of the forming process are to be selected and compared with each other. Suitable patterns can, for example, be applied to the starting material using a UV printer before the samples are formed in an industrial-scale pressing process in a 3600 t press. The resulting surface patterns must be recorded optically and methods must be developed with which these images can be analyzed and correlated with forming defects.
The task will be carried out in close cooperation with the supervising research assistant. You will be supported by our technical staff at all times during the practical activities.
The master's thesis is carried out as part of the DFG research project FOR5339 "AI-based Methodology for the Fast Maturation of Immature Manufacturing Processes".