A novel method for carbon fiber reinforced thermoplastics production combining single point incremental forming and 3D printing
Zsolt Kállai, Doran Nettig, Johann Kipping, Jan-Erik Rath, Thorsten Schüppstuhl
- 发表年份
- 2025
- 引用次数
- 1
摘要
Dieless processes such as additive manufacturing or incremental sheet forming are becoming increasingly popular in manufacturing carbon fiberreinforced components. They are a promising option for producing individual parts or small lot sizes without the need for expensive molds and can thus revolutionize the creation of patient-tailored prosthetics or high-end sports equipment. In this paper, the combination of robotic singlepoint incremental forming of carbon fiber-reinforced organo sheets with carbon fiber-reinforced 3D printing is presented. Combining those dieless processes in a novel process chain, complex parts with different geometric features could be produced without the need for adhesives or fasteners. The developed method begins with designing the desired component in CAD and its division into sections to be formed incrementally and sections to be 3D printed. For incremental forming, an organo sheet is cut to the necessary shape, sandwiched between a layup of dummy metal sheets, fixed on a clamping frame, and heated to the required forming temperature. Path planning for the robot is carried out based on a selected forming strategy, and the sheet is formed. Afterward, the part is transferred and fixed onto a robotic experimental 3D printing setup. The part\x92s surface is 3D-scanned to provide the basis for the path planning algorithm. The slicer software generates non-planar layers based on the actual shape of the formed sheet and the desired geometry of the printed part section. After slicing, the code for the robot is generated and the print job is executed. Within this paper, the conceptualized process chain is presented and basic functionality is proven by manufacturing a demonstration part. The first results are promising to enable efficient manufacturing of complex components that combine different geometric features in small batch sizes. Future research will be conducted to analyze and optimize the process chain and its capabilities, especially regarding the resulting part quality.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991