A Study of Effects of Machining Parameters on Tool Life

This work involves the investigation carried out to study the effects of machining parameters on tool life under dry machining environment. Three cutting tool materials (HSS blank tool - M2 C66, tungsten carbide insert tool grade P-10, DMNG carbide insert tool 150412-SA) and work materials (medium carbon steel 0.4 wt% C, mild steel 0.29 wt% C, brass C330) were examined. The experiments were conducted under three different spindle speeds (900, 1120, 1400rev/min); feed rates (0.1, 0.2, 0.3mm/rev) and depths of cut (0.5, 1.0, 1.5mm). The settings of machining parameters were determined by using the Taguchi experimental design method. The level of importance of the machining parameters on tool life was determined by using analysis of variance (ANOVA). The optimum machining parameters combination was obtained by using the analysis of signal-to-noise (S/N) ratio. The relationship between cutting parameters and tool life was obtained. From the results, the spindle speed had the most significant effects on tool life followed by feed rate and the depth of cut. The life of the HSS when cutting the three work pieces (medium carbon steel, mild steel and brass) was 161s, 321s and 386s respectively. The life of tungsten carbide when cutting the three work materials was 480s, 726s and 1028s respectively. The life of DMNG carbide were 782s using medium carbon steel, 864s using mild steel, and 1183s using brass. The shortest life of the three cutting tool materials (HSS, tungsten carbide and DMNG carbide) on the three work material (medium carbon steel, mild steel and brass) occurred at cutting speed (1400 rev/min), feed rate (0.3 mm/rev) and depth of cut (1.5 mm), where the life of the HSS were (15s using medium carbon steel, 58s using mild steel, 94s using brass). The life of tungsten carbide were (135s using medium carbon steel, 180s using mild steel, 274s using brass) and the life of DMNG carbide were (219s using medium carbon steel, 215s using mild steel, 311s using brass). The increment of spindle speed, feed rate and depth of cut value mostly will affect the tool life.

[1]  Erhan Budak,et al.  An experimental investigation of chatter effects on tool life , 2009 .

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

[3]  David K. Aspinwall,et al.  Rapid machining of hardened AISI H13 and D2 moulds, dies and press tools , 2003 .

[4]  S. S. Mahapatra.  Parametric Analysis and Optimization of Cutting Parameters for Turning Operations based on Taguchi Method , 2006 .

[5]  David K. Aspinwall,et al.  High speed end milling of hardened AISI D2 tool steel (∼58 HRC) , 2002 .

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

[7]  S. Balakrishnan,et al.  Predicting tool flank wear using spindle speed change , 1995 .

[8]  Fryderyk E. Gorczyca.  Application of metal cutting theory , 1987 .

[9]  Khaled Abou-El-Hossein,et al.  Prediction of tool life by statistic method in end-milling operation , 2008 .

[10]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[11]  Sudhansu Ranjan Das,et al.  OPTIMIZATION OF CUTTING PARAMETERS ON TOOL WEAR AND WORKPIECE SURFACE TEMPERATURE IN TURNING OF AISI D2 STEEL , 2012 .

[12]  Alakesh Manna,et al.  Optimization of machining conditions for effective turning of E0300 alloy steel , 2008 .

[13]  Tsann Lin.  Experimental design and performance analysis of TiN-coated carbide tool in face milling stainless steel , 2002 .

[14]  Rosli Abu Bakar,et al.  Effect of Dry Cutting on Force and Tool Life When Machining Aerospace Material , 2010 .

[15]  Joachim Bluhm,et al.  A Study of the Effects of Machining Parameters on the Surface Roughness in the End-Milling Process , 2007 .

[16]  M. A. El Baradie,et al.  Prediction of tool life in end milling by response surface methodology , 1997 .

[17]  P. S. Sivasakthivel,et al.  PREDICTION OF TOOL WEAR FROM MACHINING PARAMETERS BY RESPONSE SURFACE METHODOLOGY IN END MILLING , 2010 .

[18]  Masahiro Anzai,et al.  High Speed Milling of Cast Iron , 1995 .

[19]  S. J. Ojolo,et al.  Experimental determination of the effect of some straight biological oils on cutting force during cylindrical turning , 2008 .

[20]  Paul Mativenga,et al.  Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining , 2006 .

[21]  J. Dong,et al.  Effect of Cutting Parameters on Diamond Tool Life during Cutting Stainless Steel , 2009 .

[22]  Tuğrul Özel,et al.  Multi-objective optimization for turning processes using neural network modeling and dynamic-neighborhood particle swarm optimization , 2007 .

[23]  Y. S. Liao,et al.  Wear behavior in turning high hardness alloy steel by CBN tool , 2008 .

[24]  R. Nayak,et al.  Optimization of Cutting Parameters on Tool Wear, Workpiece Surface Temperature and Material Removal Rate During Turning of AISI D2 Steel , 2012 .

[25]  T. Özel,et al.  Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel , 2005 .

[26]  Muammer Nalbant,et al.  Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning , 2007 .

[27]  Uvanandan Valavan.  Tool life prediction based on cutting forces and surface temperature in edge trimming of multidirectional CFRP composites , 2007 .

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