Surface Roughness Analysis in the Hard Milling of JIS SKD61 Alloy Steel

Hard machining is an efficient solution that can be used to replace the grinding operation in the mold and die manufacturing industry. In this study, an attempt is made to analyze the effect of process parameters on workpiece surface roughness (Ra) in the hard milling of JIS (Japanese Industrial Standard) SKD61 steel, based on a combination of the Taguchi method and response surface methodology (RSM). The cutting parameters are selected based on the structural dynamic analysis of the machine tool. A set of experiments is designed according to the Taguchi technique. The average Ra is measured by a Mitutoyo Surftest SJ-400, and then analysis of variance (ANOVA) is performed to determine the influences of cutting parameters on the given Ra. Quadratic mathematical modeling is introduced for prediction of the Ra during the hard milling process. The predicted values are in reasonable agreement with the observation of experiments. In an effort to obtain the minimizing Ra, a single objective optimization is employed based on the desirability function. The result shows that the percentage error between measured and predicted values of Ra is 3.2%, which is found to be insignificant. Eventually, the milled surface roughness under the optimized machining conditions is 0.122 µm. This finding shows that grinding may be replaced by finish hard milling in the mold and die manufacturing field.

[1]  P. V. Rao,et al.  Selection of optimum tool geometry and cutting conditionsusing a surface roughness prediction model for end milling , 2005 .

[2]  İlhan Asiltürk,et al.  Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method , 2011 .

[3]  S. Jeyakumar,et al.  Prediction of cutting force, tool wear and surface roughness of Al6061/SiC composite for end milling operations using RSM , 2013 .

[4]  G. Derringer,et al.  Simultaneous Optimization of Several Response Variables , 1980 .

[5]  Vishal S. Sharma,et al.  Design optimization of cutting conditions and analysis of their effect on tool wear and surface roughness during hard turning of AISI-H11 steel with a coated—mixed ceramic tool , 2009 .

[6]  Jaime Gilberto Duduch,et al.  Surface integrity of ultra-precision diamond turned Ti (commercially pure) and Ti alloy (Ti-6Al-4V) , 2007 .

[7]  Yusuf Altintas,et al.  Analytical Prediction of Stability Lobes in Milling , 1995 .

[8]  Habibollah Haron,et al.  Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process , 2010, Expert Syst. Appl..

[9]  Raviraj Shetty,et al.  Analysis of surface roughness and hardness in titanium alloy machining with polycrystalline diamond tool under different lubricating modes , 2014 .

[10]  J. Paulo Davim,et al.  Machining of Hard Materials , 2011 .

[11]  J. A. Ortiz,et al.  Analysis of factors affecting the high-speed side milling of hardened die steels , 2005 .

[12]  L. N. López de Lacalle,et al.  Advanced cutting conditions for the milling of aeronautical alloys , 2000 .

[13]  Oğuz Çolak,et al.  Investigation of TiN Coated CBN and CBN Cutting Tool Performance in Hard Milling Application , 2011 .

[14]  Song Zhang,et al.  Taguchi Method Based Process Space for Optimal Surface Topography by Finish Hard Milling , 2009 .

[15]  Sulaiman Hasan,et al.  Analyses of surface roughness by turning process using Taguchi method , 2007 .

[16]  Keith Ridgway,et al.  The effect of tool edge preparation on tool life and workpiece surface integrity , 2004 .

[17]  Jun Zhao,et al.  Surface roughness and chip formation in high-speed face milling AISI H13 steel , 2012 .

[18]  N. Suresh Kumar Reddy,et al.  Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling , 2005 .

[19]  Xinmin Fan,et al.  The influence of cutting force on surface machining quality , 2007 .

[20]  Jon Rigelsford,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2004 .

[21]  Oğuz Çolak,et al.  Milling surface roughness prediction using evolutionary programming methods , 2007 .

[22]  Angelos P. Markopoulos,et al.  Surface roughness prediction for the milling of Ti–6Al–4V ELI alloy with the use of statistical and soft computing techniques , 2016 .

[23]  N. Suresh Kumar Reddy,et al.  A GENETIC ALGORITHMIC APPROACH FOR OPTIMIZATION OF SURFACE ROUGHNESS PREDICTION MODEL IN DRY MILLING , 2005 .

[24]  M. Elbah,et al.  Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology , 2014 .

[25]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[26]  Anselmo Eduardo Diniz,et al.  Toroidal milling of hardened SAE H13 steel , 2004 .

[27]  Ali Riza Motorcu,et al.  The Optimization of Machining Parameters Using the Taguchi Method for Surface Roughness of AISI 8660 Hardened Alloy Steel , 2010 .

[28]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[29]  Mohd Amri Sulaiman,et al.  Prediction Surface Roughness in High-Speed Milling of Inconel 718 under Mql Using Rsm Method , 2013 .

[30]  Habibollah Haron,et al.  Prediction of surface roughness in the end milling machining using Artificial Neural Network , 2010, Expert Syst. Appl..

[31]  K. Palanikumar,et al.  OPTIMAL MACHINING CONDITIONS FOR TURNING OF PARTICULATE METAL MATRIX COMPOSITES USING TAGUCHI AND RESPONSE SURFACE METHODOLOGIES , 2006 .

[32]  C. J. Luis Pérez,et al.  Surface roughness prediction by factorial design of experiments in turning processes , 2003 .

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

[34]  Hasan Kurtaran,et al.  Application of response surface methodology in the optimization of cutting conditions for surface roughness , 2005 .

[35]  Sandeep Kumar,et al.  Appl. Sci , 2013 .

[36]  Song Zhang,et al.  Empirical models and optimal cutting parameters for cutting forces and surface roughness in hard milling of AISI H13 steel , 2010 .

[37]  J. Vivancos,et al.  Optimal machining parameters selection in high speed milling of hardened steels for injection moulds , 2004 .

[38]  M. RahmanM.,et al.  Optimization of Surface Roughness in End Milling on Mould Aluminium Alloys (AA6061-T6) Using Response Surface Method and Radian Basis Function Network , 2008 .

[39]  Ugur Esme.  Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology , 2015 .

[40]  Tarek Mabrouki,et al.  Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization , 2012 .