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automated fiber placement is widely recognized as one of the most advanced manufacturing processes for structural composite components current afp process control has focused on producing defect-free parts by using fiber trajectory design course monitoring and optimization of the process parameters these are usually determined on a trial and error basis leading to prolonged machine down times given that the deviations between as design and as manufactured parts are inevitable we have proposed on-the-fly tuning of the key afp parameters using real-time data to solve this issue to demonstrate this idea we have designed and constructed a novel prototype afp test bench which houses multiple sensors to measure material properties and processing conditions in real time this data will then be used to update live processing conditions such as speed pressure and temperature to improve the final deposition accuracy this work explores intelligent automated fiber placement system that modifies pro
