TOOL WEAR AND SURFACE ROUGHNESS PREDICTION USING ANN IN CNC MILLING OPERATIONS

Abstract

The paper presents the state of art of review on tool wear and surface roughness prediction using artificial neural networks in CNC milling operations. In manufacturing industries milling is widely used metal removal processes. Milling is the basic machining process to produce flat surface by progressive chip removal. The surface roughness parameter ids most important factor to analyze the performance of machining properties like creep life, corrosion resistance and also fatigue behavior. However, proper selection of cutting conditions and parameters for achieving a desired surface finish is very difficult task, because the mechanism behind the occurrence of surface roughness is very dynamic, complicated and process dependent. An experiment was conducted using computer numerical controlled milling machine to train the data and to check the performance of the network. The basic factors like speed, depth of cut and feed were taken in an experiment.