Investigation of cutting condition monitoring by visual measurement of surface texture parameters

Abstract

This paper reports on the development of a cutting condition monitoring system for an end milling process using a machine vision technique. This system measures the surface texture of a finished part to detect the existence of unusual cutting conditions. Meanwhile, mathematical or empirical models can be applied to estimate the amount of adjustment. This approach replaces human intelligence so that an untended milling process becomes possible. Experimental results reveal that the algorithms developed can be successfully applied to detect the existence of errors and calculate the amount of adjustment.