Prediction of Surface Finish in End Milling Operation Using Adaptive Neuro-Fuzzy System

Surface finish is an important parameter in manufacturing engineering. It is a characteristic that could influence the performance of machined parts and the production costs. This paper proposes a method using adaptive neuro-fuzzy inference system to establish the relation between machining parameters and surface finish in end milling and consequently, can effectively predict surface finish of workpiece using input cutting parameters namely, spindle speed, feed rate and depth of cut. The results obtained with the adaptive neuro-fuzzy inference system are compared with the experimental results. The comparison indicates that the proposed method can produce optimized knowledge base of fuzzy system for predicting surface finish in end milling operation.