IMPROVING THE SURFACE ROUGHNESS AT LONGITUDINAL TURNING USING THE DIFFERENT OPTIMIZATION METHODS
暂无分享,去创建一个
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.
[1] E. Kuljanic,et al. Capp Software for Tool Selection, Optimization and Tool Life Data Base Adaptation in Turning , 1999 .
[2] M. Brezocnik,et al. Integrated Genetic Programming and Genetic Algorithm Approach to Predict Surface Roughness , 2003 .
[3] Sonja Jozić,et al. DESIGN OF EXPERIMENT'S APPLICATION IN THE OPTIMIZATION OF MILLING PROCESS , 2010 .
[4] George-Christopher Vosniakos,et al. Predicting surface roughness in machining: a review , 2003 .