What is it about?
This paper presents a very detailed neural network modelling approach to predict multiple profile points in cold spray additive manufacturing at both normal and off-normal spray angles. The detailed methodology explanation will contribute to solving similar prediction problems in additive manufacturing as well as other manufacturing community. This is the first computational intelligence approach in the prediction of cold spray profiles. Also unique is in that the application of such an approach in the entire profile prediction instead of key geometric features only. The approach presented in this publication can be extended to other areas such as Wire and Arc Additive Manufacturing and Laser Cladding.
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Photo by Ines Álvarez Fdez on Unsplash
Why is it important?
Important for any related works requiring the accurate prediction of a single-track profile (e.g. welding). In additive manufacturing, the prediction of such single-track profiles may be necessary when predicting the overlapping and overlayer shape predictions.
Perspectives
This is the first step of a series of our works to combine the artificial intelligence into additive manufacturing
Mr Daiki Ikeuchi
University of Cambridge
Read the Original
This page is a summary of: Neural Network Modelling of Track Profile in Cold Spray Additive Manufacturing, Materials, September 2019, MDPI AG,
DOI: 10.3390/ma12172827.
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