Optimization of drilling parameters using Taguchi technique and response surface methodology (RSM) in drilling of AISI 304 steel with cryogenically treated HSS drills

In this study, the effects of cryogenic treatment and drilling parameters on surface and hole quality were investigated in the drilling of AISI 304 stainless steel under dry drilling conditions. The control factors to provide better surface roughness (Ra) and roundness error (Re) were determined using the Taguchi method. RSM was also used to determine interactions among the control factors. In addition, analysis of variance was employed to determine the most significant control factors on the surface roughness and roundness error. Three drill categories (conventional heat treatment—CHT, cryogenic treatment—CT, cryo-tempering—CTT), cutting speeds, and feed rates were considered as control factors, and an $$\text{ L }_{27}$$L27 full factorial design with a mixed orthogonal array was selected for experimental trials. As a result, it was found that the feed rate and cutting speed were the most significant factors on the surface roughness and roundness error with percentage contributions of 83.07 and 64.365 % respectively. The predictive quadratic models were derived by the RSM to obtain the optimal surface roughness and roundness error as a function of drilling parameters and heat treatments applied to the drills.

[1]  Jyh-Cheng Yu,et al.  Optimization of extrusion blow molding processes using soft computing and Taguchi’s method , 2004, J. Intell. Manuf..

[2]  Y. S. Tarng,et al.  Design optimization of cutting parameters for turning operations based on the Taguchi method , 1998 .

[3]  Fan-Tien Cheng,et al.  Development of holonic manufacturing execution systems , 2004, J. Intell. Manuf..

[4]  Mark A.M. Bourke,et al.  Microstructure of cryogenic treated M2 tool steel , 2003 .

[5]  Uday S. Dixit,et al.  Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process , 2003 .

[6]  Ko-Ta Chiang,et al.  Modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic , 2008 .

[7]  B. Bhattacharyya,et al.  Investigation for controlled ellectrochemical machining through response surface methodology-based approach , 1999 .

[8]  Cevdet Göloglu,et al.  Zigzag machining surface roughness modelling using evolutionary approach , 2009, J. Intell. Manuf..

[9]  Anselmo Eduardo Diniz,et al.  Vibration analysis of cutting force in titanium alloy milling , 2010 .

[10]  Cristian Caizar,et al.  Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3 , 2011 .

[11]  R. Suresh,et al.  Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool , 2012 .

[12]  D. J. Stephenson,et al.  Application of response surface methodology for the optimisation of micro friction surfacing process , 2010 .

[13]  A. Rajadurai,et al.  Microstructural study of cryogenically treated En 31 bearing steel , 2009 .

[14]  Adem Çiçek,et al.  Machinability of AISI 316 Austenitic Stainless Steel With Cryogenically Treated M35 High-Speed Steel Twist Drills , 2012 .

[15]  Yusuf Kaynak,et al.  Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes , 2009 .

[16]  Deniz Baş,et al.  Modeling and optimization I: Usability of response surface methodology , 2007 .

[17]  Adem Çiçek,et al.  Taguchi method based optimisation of drilling parameters in drilling of AISI 316 steel with PVD monolayer and multilayer coated HSS drills , 2012 .

[18]  İlhan Asiltürk,et al.  Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis , 2012 .

[19]  D. I. Lalwani,et al.  Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel , 2008 .

[20]  Lukáš Pilný,et al.  HOLE QUALITY AND BURR REDUCTION IN DRILLING ALUMINIUM SHEETS , 2012 .

[21]  Yi-Wei Lin,et al.  Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers , 2012, J. Intell. Manuf..

[22]  Mohammad Nazrul Islam,et al.  Effect of Canned Cycles on Drilled Hole Quality , 2009 .

[23]  Hong Hocheng,et al.  Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network , 2008 .

[24]  Phillip J. Ross,et al.  Taguchi Techniques For Quality Engineering: Loss Function, Orthogonal Experiments, Parameter And Tolerance Design , 1988 .

[25]  Jagdev Singh,et al.  Wear behaviour of cryogenically treated tungsten carbide inserts under dry and wet turning conditions , 2009 .

[26]  J. Grum,et al.  The use of factorial design and response surface methodology for fast determination of optimal heat treatment conditions of different Ni–Co–Mo surfaced layers , 2004 .

[27]  J. Horng,et al.  Investigating the machinability evaluation of Hadfield steel in the hard turning with Al2O3/TiC mixed ceramic tool based on the response surface methodology , 2008 .

[28]  Viktor P. Astakhov,et al.  Effects of the cutting feed, depth of cut, and workpiece (bore) diameter on the tool wear rate , 2007 .

[29]  Hung-Chang Liao,et al.  Using N-D method to solve multi-response problem in Taguchi , 2005, J. Intell. Manuf..

[30]  S. Renganarayanan,et al.  Cryogenic treatment to augment wear resistance of tool and die steels , 2001 .

[31]  Biswanath Doloi,et al.  Optimization of flank wear using Zirconia Toughened Alumina (ZTA) cutting tool: Taguchi method and Regression analysis , 2011 .

[32]  Kadir Yavuz,et al.  An experimental investigation into the machinability of GGG-70 grade spheroidal graphite cast iron , 2009 .

[33]  Lucian Savu,et al.  CONSIDERATIONS REGARDING EVALUATION OF THE ACCURACY ASSESSMENT OF THE ROUNDNESS , 2012 .

[34]  Tatjana V. Sibalija,et al.  An integrated approach to optimise parameter design of multi-response processes based on Taguchi method and artificial intelligence , 2012, J. Intell. Manuf..

[35]  Inderdeep Singh,et al.  Determination of Machining-Induced Damage Characteristics of Fiber Reinforced Plastic Composite Laminates , 2004 .

[36]  Adem Çiçek,et al.  Performance of cryogenically treated M35 HSS drills in drilling of austenitic stainless steels , 2012 .

[37]  V. N. Gaitonde,et al.  Machinability investigations on hardened AISI 4340 steel using coated carbide insert , 2012 .

[38]  T. V. SreeramaReddy,et al.  Machinability of C45 steel with deep cryogenic treated tungsten carbide cutting tool inserts , 2009 .