IMPROVING THE SURFACE ROUGHNESS AT LONGITUDINAL TURNING USING THE DIFFERENT OPTIMIZATION METHODS

Determination of optimal machining parameters is a continuous engineering task whose goals are to reduce the production costs and to achieve the desired product quality. Hence, this paper presents and discusses different optimization methods to determine the optimal values of cutting speed, feed and depth of cut with the purpose of improving the surface roughness obtained in the finish longitudinal turning operation. Two experimental plans, one based on the conventional rotatable central composite design and the other based on the orthogonal arrays and signal-to-noise ratio were carried out on the practical case. By using these plans, different optimization methods, namely analytical, classical mathematical, Taguchi and artificial neural networks were performed and the results of optimal cutting parameters obtained with these methods were compared. Finally, the features, the merits and the limitations of the presented optimization methods were discussed.