International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) V...
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Comparison of performance of coated carbide inserts with uncoated carbide

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Comparison of performance of coated carbide inserts with uncoated carbide

  1. 1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME392COMPARISON OF PERFORMANCE OF COATED CARBIDE INSERTSWITH UNCOATED CARBIDE INSERTS IN TURNING GRAY CASTIRONYuvaraj P. Ballal1, Manjit M. Khade2, Ajit R. Mane31(Department of Mechanical Engineering, ADCET, Ashta,India)2(Department of Mechanical Engineering, ADCET, Ashta,India )3(Department of Mechanical Engineering, ADCET, Ashta,India)ABSTRACTIn this study, machining performance of a series of commercially available coatedtungsten carbide inserts were investigated during turning of gray cast iron brake drum. Theinserts tested had a coating of TiCN and TiAlN respectively. For comparison, uncoatedcemented tungsten carbide insert of K10 grade was also tested under the same cuttingconditions. Taguchi analysis using ANOVA for 3 parameter, 3 level experimentation - fullfactorial (L27 array) were done with output response variables like surface roughness, materialremoval rate, tool wear. Main effects of factors and their interactions were studied.Keywords: ANOVA, Cemented tungsten carbide insert, Coating, Gray cast iron, Machiningperformance, Taguchi analysis.1. INTRODUCTIONThe challenge of modern machining industries is mainly focused on the achievement ofhigh quality, in terms of work piece surface finish, high production rate, less wear on thecutting tools, economy of machining in terms of cost saving and increase the performance ofthe product[1]. Effective machining of work material depends upon the selection ofappropriate cutting tool. A wide range of cutting tool materials is available with variety ofproperties, performance capabilities, and cost. These include high speed steels, cementedcarbides, ceramics, cermets, cubic boron nitride, and diamond. The cutting tool material,cutting parameters and tool geometry directly influence the productivity of machining operation[2].INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERINGAND TECHNOLOGY (IJMET)ISSN 0976 – 6340 (Print)ISSN 0976 – 6359 (Online)Volume 4, Issue 2, March - April (2013), pp. 392-400© IAEME: www.iaeme.com/ijmet.aspJournal Impact Factor (2013): 5.7731 (Calculated by GISI)www.jifactor.comIJMET© I A E M E
  2. 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME3932. EXPERIMENTAL DETAILS2.1. Selection of work and tool materialGray iron is one of the oldest cast ferrous products. In spite of competition from newermaterials and their energetic promotion, gray iron is still used for those applications where itsproperties have proved it to be the most suitable material available. Gray iron castings are readilyavailable in nearly all industrial areas and can be produced in foundries representingcomparatively less investments. Chemical composition of FG260 gray cast iron is shown infollowing table 1. The recently developed tool materials like coated carbides have improved theproductivity levels of difficult-to-machine materials. The coated carbide tool was selected forturning of cast iron. Cemented carbide is chosen as uncoated cutting tool material. The ISO gradeselected is K10. Other details are:Designation : CNMA 120408Nose radius : 0.8 mmTool Holder : PCLNR 2525 M 12.Table 1: Chemical composition of gray cast ironElements Composition %Carbon 2.5 -3.7Silicon 0.10-0.30Manganese 0.5-1.0Sulphur 0.07-0.1Phosphorous 0.1-0.9Iron remainder2.2. Selection of work and tool materialIn Taguchi method-based design of experiments, to select an appropriate orthogonal arrayfor experimentation, the total degrees of freedom (DOF) needs to be computed. The DOF isdefined as the number of comparisons between machining parameters that need to be made todetermine, which level is better and specifically how much better it is. For example, a three-levelmachining parameter has two DOF. The DOF associated with interaction between two machiningparameters are given by the product of the DOF for the two machining parameters. In the presentstudy, interactions between the three machining parameters will be considered. Therefore, thereare 18 DOF owing to three three-level independent parameters, refer table 2 [3].Table 1: Machining parameters and their levelsProcess ParametersParameterDesignationDOFLevelsI II IIICutting speed (mm/min) A 2 350 400 450Feed (mm/rev) B 2 0.2 0.25 0.3Tool type C 2UncoatedK10 carbideinsertTiCN coatedK10 carbideinsertTiAlN coatedK10 carbideinsertInteractions (AB,AC, BC) -[(3-1) X (3-1)] X3=12- - -Total DOF - 18 - - -The machine used for turning is SIMPLE TURN 5075 CNC LATHE (Fanuc Series).
  3. 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME3942.3. Experimental resultsThe experimental results obtained after performing experiments are shown in the table 3[3,4].Table 3: Experimental resultsSt.orderCuttingspeedm/minFeedmm/revTooltypeDepth ofcut (mm)(const.)Surfacefinish(Ra)( µm)Tool wearrate(gms/min)Flankwear(mm)MRR1 350 0.2 UC 2 2.08 0.00125 0.513 242.2142 350 0.2 TiCN 2 3.52 0.00021 0.096 300.7753 350 0.2 TiAlN 2 1.03 0.00006 0.024 372.2354 350 0.25 UC 2 2.86 0.00182 0.972 288.3155 350 0.25 TiCN 2 4.23 0.00017 0.062 340.1536 350 0.25 TiAlN 2 1.82 0.00012 0.034 420.8577 350 0.3 UC 2 3.26 0.00224 0.920 316.1238 350 0.3 TiCN 2 5.38 0.00034 0.098 418.1929 350 0.3 TiAlN 2 2.38 0.00008 0.028 436.32410 400 0.2 UC 2 1.80 0.00240 1.087 304.27811 400 0.2 TiCN 2 3.28 0.00020 0.092 315.44112 400 0.2 TiAlN 2 2.20 0.00003 0.017 406.45113 400 0.25 UC 2 1.38 0.00260 0.966 308.97014 400 0.25 TiCN 2 2.62 0.00024 0.094 413.39715 400 0.25 TiAlN 2 3.93 0.00003 0.014 543.15716 400 0.3 UC 2 3.08 0.00326 1.130 324.67117 400 0.3 TiCN 2 5.48 0.00030 0.126 469.14818 400 0.3 TiAlN 2 2.46 0.00038 0.143 568.42019 450 0.2 UC 2 1.89 0.00302 1.184 343.21020 450 0.2 TiCN 2 2.58 0.00004 0.023 497.43521 450 0.2 TiAlN 2 4.38 0.00008 0.032 582.69022 450 0.25 UC 2 2.42 0.00602 1.820 401.23823 450 0.25 TiCN 2 5.28 0.00006 0.038 714.00024 450 0.25 TiAlN 2 3.35 0.00019 0.064 879.54525 450 0.3 UC 2 3.58 0.00436 1.540 447.05826 450 0.3 TiCN 2 4.83 0.00138 0.532 865.11627 450 0.3 TiAlN 2 4.68 0.00014 0.056 998.1203. STATISTICAL ANALYSIS OF VARIANCEThe statistical analysis of variance for all responses is as follows [1, 2, 3, 4, 5, and 6],3.1. Statistical Analysis of Surface Roughness (Ra)Statistical ANOVA shown in Table 4, indicate that tool type is the most significant factorfor surface roughness which has P-value of 0.002.
  4. 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME395Table 4: ANOVA for Surface finish (Ra)S=0.892127 R-Sq= 61.09 % R-Sq(adj) = 49.42 % SS= sum of squaresThe main effect plot (Fig.1) shows that cutting speed has almost no effect on the surfaceroughness at higher levels. Feed rate has linear relationship with the surface roughness, itincreases as feed rate is increased due to the fact that more forces of the tool on the workpiecedue to higher feed rates tends to lose the surface finish, so for good surface quality, a low feedrate is essential. Uncoated tools exhibit lower surface roughness than coated tools, this is dueto loss of tool edge at continuous machining by uncoated tools.4504003504.03.53.02.50.300.250.20TiAlNTiCNUC4.03.53.02.5cutting speedMeanfeedtool typeData MeansFig 1. Main effect plot for Surface finish (Ra)The interaction plot as shown in Fig 2, indicates that at higher speeds and higher feeds, thesurface roughness increases and this is same for both coated and uncoated tools. Surfaceroughness values decreases as speeds increases from 350 to 450 m/min in comparison to bothcoated and uncoated tools.Source DF SS MS F PCuttingspeed2 3.2278 1.6139 2.03 0.158Feed rate 2 8.5834 4.2917 5.39 0.013Tool type 2 13.1821 6.5911 8.28 0.002Error 20 15.9178 0.7959 - -Total 26 40.9112 - - -
  5. 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME396Fig 2. Interaction plot for surface finish3.2. Statistical Analysis of Tool Flank WearIt is found that the tool wear progresses rapidly during machining of cast iron. StatisticalANOVA shows that the tool type is the most significant factor for the wear and cutting speed isthe next influencing factor(refer table 5).Table 5: ANOVA for tool flank wearS = 0.203854 R-Sq = 89.39% R-Sq(adj) = 86.20%The main effects plots (Fig 3) shows that an increase in cutting speed causes rapid increase in thetool wear.Feed rate shows very linear effect on the wear. As feed is increased, there is moreincrement in the wear since feed rate increases with increase in force on cutting edge of tool.Uncoated tools have higher wear as compared to coated tools, the least wear is observed inTiAlN coating as shown in Fig 3.Source DF SS MS F PCuttingspeed2 0.3680 0.1840 4.43 0.026Feed rate 2 0.1302 0.0651 1.57 0.233Tool type 2 6.5007 3.2503 78.21 0.000Error 20 0.8311 0.0416 - -Total 26 7.8300 - - -
  6. 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME3974504003501.000.750.500.250.000.300.250.20TiAlNTiCNUC1.000.750.500.250.00cutting speedMeanfeedtool typeMain Effects Plot for flank wear (mm)Data MeansFig 3. Main effect plot for tool flank wear (mm)The wear behavior at the lower to higher speeds is almost the same at different feed rates, asseen in Fig 4. At lower feed of 0.2 mm/rev, the wear is least. Uncoated tools exhibiting higherflank wear than coated tools. It is also seen that as speed is increasing, the flank wear is alsoincreasing, this is due to the loss of hot hardness at high cutting speed. All the tools exhibithigher flank wear at higher feeds.Fig 4. Interaction plot for tool flank wear
  7. 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME3983.3. Statistical Analysis of Material Removal RateStatistical ANOVA shown in Table 6, indicate that in case of MRR, all processparameters namely cutting speed, feed and tool type are significant factors.Table 6: ANOVA for MRRS = 90.1397 R-Sq = 83.53% R-Sq(adj) = 78.59Fig 5. Main effect plot for MRR (gm/min)The main effects plots (Fig 5) and interaction plots (Fig 6) shows that MRR increaseswith increase in cutting speed, feed and tool type and most significant at 450 m/min, 0.3mm/rev and TiAlN coated cutting tool.Source DF SS MS F PCuttingspeed2 418421 209211 25.75 0.000Feed rate 2 124567 62283 7.67 0.003Tool type 2 281027 140514 17.29 0.000Error 20 162503 8125 - -Total 26 986518 - - -
  8. 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME399Fig 6. Interaction plot for MRR4. CONCLUSIONThe experiments were conducted as per Taguchi L 27 orthogonal array. After fixingprocess parameters (cutting speed, feed, depth of cut and cutting tool material) observationsfor response variables (SF, Tool wear, MRR) were taken. The following are the conclusionsmade after experimentation and statistical analysis of variance.1. Tool type is the most significant factor for surface roughness. Coated cutting toolsshows higher roughness values than uncoated cutting tools at lower feed rates androughness value increased as feed rate increased.2. The roughness value for TiAlN coated cutting tools increases with increase incutting speed and roughness value for TiCN is high and roughness value foruncoated cutting tools is low for selected cutting speed range.3. Tool wear rate is much higher for uncoated cutting tool than coated cutting toolsfor selected process parameters. For TiAlN coated cutting tool have least toolwear.4. MRR increases with increase in cutting speed , feed and most significant at 450m/min, 0.3 mm/rev and TiAlN coated cutting tool.REFERENCES[1]Thamizhmanii S., Saparudin S. and Hasan S. “Analyses of surface roughness by turningprocess using Taguchi method”, Journal of achievements in material and manufacturingengineering, Pg. 503-506, Vol. 20, Issue 1-2, Jan- Feb, 2007[2]Khandey Umesh, “Optimization of surface roughness, material removal rate and cuttingtool flank wear in turning using extended Taguchi approach”, masters dissertation report,NIT Rourkela, August 2009.
  9. 9. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 2, March - April (2013) © IAEME400[3]Ramji B.R, H.N. Narasimha Murthy and M. Krishna, “Analysis of roughness and flankwear in turning gray cast iron using cryogenically treated cutting tools”, Research Journalof Applied Sciences, Engineering and Technology 2(5), Pg. 414-417, 2010, ISSN: 2040-7467[4]Gopalsamy Bala Murugan, Mondal Biswanath and Ghosh Sukamal, “Taguchi method andANOVA: An approach for process parameters optimization of hard machining whilemachining hardened steel”, Journal of Scientific and Industrial Research, Vol. 8, August2009, pp. 686-695.[5]Dolinšek S. and Kopač J., “Mechanism and types of tool wear particularities in advancedcutting materials”, Journal of Achievements in Materials and Manufacturing Engineering,November 2006, Volume 19 Issue 1.[6]Singh Hari, “Optimizing Tool Life of Carbide Inserts for Turned Parts using Taguchi’sDesign of Experiments Approach”, Proceedings of the International MultiConference ofEngineers and Computer Scientists 2008 Vol II, 19-21 March, 2008.[7]K.Dharma Reddy and Dr.P.Venkataramaiah, “Experimental Investigation on Responsesin Turning of Aluminium with Carbide Tipped Tool at Different Coolant Conditions”International Journal of Mechanical Engineering & Technology (IJMET), Volume 3,Issue 2, 2012, pp. 189 - 199, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.[8]R. R. Deshmukh and V. R. Kagade, “Optimization of Surface Roughness in TurningHigh Carbon High Chromium Steel by using Taguchi Method”, International Journal ofMechanical Engineering & Technology (IJMET), Volume 3, Issue 1, 2012, pp. 321 - 331,ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.[9]Vipin Kumar Sharma, Qasim Murtaza and S.K. Garg, “Response Surface Methodology &Taguchi Techquines to Optimization of C.N.C. Turning Process”, International Journal ofProduction Technology and Management (IJPTM), Volume 1, Issue 1, 2010, pp. 13 - 31,ISSN Print: 0976- 6383, ISSN Online: 0976 – 6391.

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