Description

Fiber-reinforced thermoplastics are plastics that are mechanically reinforced by embedding fibers (e.g., glass or carbon fibers). They offer high strength, stiffness, and impact resistance while maintaining low weight.

Due to these properties, they are used in applications such as the automotive industry, aerospace engineering, and medical technology. Fiber-reinforced laminates can be heated and formed into complex geometries through a pressing process. Various forming defects occur during this process, which is why the production process is considered immature. Artifacts, such as wrinkles in the material or deviations in fiber volume content, are generally not visible to the naked eye but create mechanical weaknesses in the material. An approach to artifact detection is to print a pattern on the unformed material and subsequently correlate the deformed pattern with the forming defects in the component.

This master’s thesis will be conducted within the DFG research project FOR5339 ”AI-based Methodology for the Fast Maturation of Immature Manufacturing Processes”.

Tasks

• Literature review on different patterns and optical image processing methods
• Evaluation of different patterns with regard to various constraints and criteria
• Analysis of deformed patterns and detection of artifacts using optical image processing
• Validation of the methodology based on experimental results

Supervision:

Frank Döhner frank.doehner@kit.edu

Start: Upon agreement

Language: German or English