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Laser profile scanners look into the future of composite manufacturing

31 January 2024

A research project undertaken by the Bristol Composites Institute (BCI) at the University of Bristol used laser profile sensors from Micro-Epsilon to detect defects formed during the composite manufacturing process. 


By linking live laser sensor data with a convolutional neural network (CNN), the team at BCI can conduct real-time automated inspection of manufactured parts. This novel inspection technique provides great potential to improve efficiency and reduce waste in composite manufacturing.

The team at BCI achieved this goal by embedding Micro-Epsilon’s sensors into a lab-scale automated fibre placement (AFP) system, which is a composite manufacturing method commonly used in the aerospace industry. The AFP method uses robotic arms to deposit layers of carbon fibre-reinforced composites (CFRP) onto bespoke moulds. This process can create complex shapes at high speed. 

However, manufacturing-induced defects are inevitable during AFP. 


Read the full article in DPA's February issue



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