Selection of a suitable multiresponse optimization technique for turning operation

The present work deals with the comparison of four multi response optimization methods, viz. multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio, Grey relational analysis (GRA), and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian) methods taking a case study in turning mild steel specimen using HSS cutting tool. The various factors like cutting speed, feed rate, depth of cut and coolant flow rate are considered as the input process variables, while the material removal rate (MRR), surface roughness (SR) and specific energy consumption (SEC) are considered as various performance characteristics. One set of experimental data is analyzed using the standardized procedures. The optimization performances of these four methods are compared. The results show that MRSN ratio method proves to be the best optimization method. It is found that the feed rate has a highest impact on the overall performance as compared to other process parameters.

[1]  M. A. El Baradie,et al.  Cutting fluids: Part I. Characterisation , 1996 .

[2]  Mustafa Günay,et al.  Application of Taguchi method for determining optimum surface roughness in turning of high-alloy white cast iron , 2013 .

[3]  P. Shahabudeen,et al.  Simultaneous optimization of multi-response problems in the Taguchi method using genetic algorithm , 2006 .

[4]  Ulaş Çaydaş,et al.  Optimization of turning parameters for surface roughness and tool life based on the Taguchi method , 2008 .

[5]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[6]  Ramón Quiza Sardiñas,et al.  Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes , 2006, Eng. Appl. Artif. Intell..

[7]  Y. S. Tarng,et al.  Optimization of turning operations with multiple performance characteristics , 1999 .

[8]  R. N. Kackar Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[9]  S. V. Wong,et al.  Surface Roughness Identification Using the Grey Relational Analysis with Multiple Performance Characteristics in Turning Operations , 2012 .

[10]  Lee-Ing Tong,et al.  Optimization of multi-response processes using the VIKOR method , 2007 .

[11]  Steven R Schmid Kalpakjian,et al.  Manufacturing Engineering and Technology , 1991 .

[12]  Hung-Chang Liao,et al.  Multi-response optimization using weighted principal component , 2006 .

[13]  Muh-Cherng Wu,et al.  An enhanced Taguchi method for optimizing SMT processes , 1992 .

[14]  P. Srihari,et al.  International Conference On DESIGN AND MANUFACTURING, IConDM 2013 Influence of cutting parameters on cutting force and surface finish in turning operation , 2013 .

[15]  Ming-Chang Jeng,et al.  Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis , 2009 .

[16]  Shankar Chakraborty,et al.  Optimisation of multiple responses for WEDM processes using weighted principal components , 2009 .

[17]  Ali Riza Motorcu,et al.  Surface roughness model in machining hardened steel with cubic boron nitride cutting tool , 2008 .