Abstract
Surface quality improvement by a laser polishing (LP) process is a new innovative technology enabling value-adding functionalities, such as improving visual appearance, wettability, friction, and others through the control and reconfiguration of the surface topography. However, the resultant surface is dependent upon many process parameters which makes selecting optimal process parameters to achieve desired surface topography difficult and unrepeatable. It was proposed and demonstrated that recurrent neural network (RNN) can reliably model the LP of H13 tool steel and predict the laser polished surface topography parameters such as areal waviness and roughness with a probability of 99% and 79%, respectively. © 2021 Her Majesty the Queen in Right of Canada, as represented by the National Research Council of Canada; equal contribution of all co-authors
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
