An integrated framework for a multi-material surface roughness prediction model in CNC turning using theoretical and machine learning methods

Indirect monitoring and prediction of surface roughness for computer numerical control (CNC) machining enables manufacturers to ensure quality outcomes are achieved, increase process productivity, and decrease the risk of scrapped components. Several approaches have been examined for surface roughness prediction in CNC turning; however, few studies have explored the development of models for multiple materials. These studies typically use a …