In-Process Surface Roughness Recognition (ISRR) System in End-Milling Operations

This paper describes a new approach for surface roughness recognition (ISRR) systems to predict surface roughness (Ra) in-process using an accelerometer to measure vibration signals and cutting conditions while end-milling is taking place. The analysis of the data and the model building is carried out using a neural fuzzy system. Experimental results show that the parameters of spindle speed, feedrate, depth of cut, and vibration variables can predict the surface roughness (Ra) effectively. Surface roughness can also be predicted with a 96% accuracy rate by ISRR using the neural fuzzy system.