Experimental Investigations to Study Tool Wear During Turning of Alumina Reinforced Aluminium Composite

CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector Available online at www.sciencedirect.com Procedia Engineering 51 (2013) 818 – 827 Non-Circuit Branches of the 3rd Nirma University International Conference on Engineering (NUiCONE 2012) Experimental Investigations To Study Tool Wear During Turning Of Alumina Reinforced Aluminium Composite Puneet Bansala Lokesh Upadhyayb a M.Tech Scholar,SVNIT Surat,India Sachdeva Institute of Technology,Mathura,India b Abstract Metal matrix compositions (MMC) have become a leading materials and particles reinforced aluminum MMCs have received considerable attention due to their excellent mechanical properties like high hardness, high tensile strength etc. These materials difficult to machine because of high hardness and abrasive nature of reinforcing elements like alumina particles. In this study, homogenized (2%, 4%, and 6%) by weight of alumina aluminum metal matrix composite materials were fabricated and selected as workpiece for experimental investigations of tool wear, surface roughness and metal removal rate. The titanium nitride coated tungsten carbide tool and uncoated tungsten carbide tools were used at different cutting speeds (265,400,535 rpm), feed rate (0.29, 0.32, 0.35 mm/rev.), and depth of cut (1.0, 1.5, 2.0 mm). The microstructures and mechanical properties of produced composite specimens have been investigated. It has been observed that increase of reinforcement element produced better mechanical properties such as hardness and tensile strength. The turning experiments were planned by taguchi method. The obtained experimental data has been analyzed using signal to noise ratio and ANOVA. The main effects have been discussed and percentage contribution of various process parameters speed, feed, depth of cut and concentration effecting tool wear, surface roughness and metal removal rate have been determined. . 2012The Published ElsevierbyLtd. Selection and/or under responsibility of the Institute of Technology Nirma © 2013 Authors.by Published Elsevier Ltd. Open accesspeer-review under CC BY-NC-ND license. Selection andAhmedabad. peer-review under responsibility of Institute of Technology, Nirma University, Ahmedabad. University, Keywords: Matel Matrix Composite (MMC), Hardness, Toughness, Tool Wear, Nomenclature MRR Material Removal Rate P1 Cutting Speed (v) in rpm P2 Feed Rate (f) in mm/rev P3 Depth of Cut (d) in mm P4 concentration of Alumina by weight in percentage % Greek symbols Signal to noise (S/N) ratio Percentage contribution of each parameter. Subscripts p Number of significant parameters e Sum of squared error 1. Introduction applications. Composite material is a materials system composed of two or more dissimilar constituents, differing in forms, 1877-7058 © 2013 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and peer-review under responsibility of Institute of Technology, Nirma University, Ahmedabad. doi:10.1016/j.proeng.2013.01.117 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 819 insoluble in each other, physically distinct and chemically inhomogeneous. Each of the various components retains its identity in the composite and maintains its characteristic structure and properties. These are recognizable interfaces between the materials. The resulting product possesses properties much differed from the properties of constituents materials, also referred as composites. Metal matrix composite (MMC) are widely used composite materials in aerospace, automotive, electronics and medical industries. They have outstanding mechanical properties like high strength, low weight, low ductility, high wear resistance, high thermal conductivity and low thermal expansion. These desired properties are mainly manipulated by matrix, the reinforcement element and the interface. Aluminium-based Al2O3 particle reinforced MMC material have become useful engineering materials due to their properties such as low weight, heat-resistant, wear-resistant and low cost. These are found in various engineering applications such as cylinder block liners, vehicle drive shafts, automotive pistons, bicycle frames etc. These materials are known as the difficult-to-machine materials, because of the hardness and abrasive nature of reinforcement element like alumina (Al2O3) particle. In metal cutting three basic causes have been suggested for tool wear; adhesion, abrasion and diffusion. The progressive wear of cutting tool takes place in two distinct ways. Usually, wear first occurs on the clearance or flank face of the tool in the form of a wear land due to rubbing against the newly machined surface. As a result of chip flowing over the rake face, wear also occurs on the rake surface. This is usually characterized by the formation of a crater. Kilickap et al. [1-2] developed a relationship between tool wear and surface roughness to cutting parameters for machining of homogenized SiC-p reinforced aluminium metal matrix composite. The study emphasize on investigated the tool wear rate of different coated and uncoated tool and surface roughness in different cutting parameters. It was observed that increase in reinforcement element addition produced better mechanical properties such as impact toughness but tensile strength shoes different trends. Lane [3] attributed the increase in the wear of PCD tool by abrasion to increases in kinetic energy gained by abrading SiC particles. They studied the performance of different CVD tools with thin and thick films. According to their observations, CVD tools with thin films failed catastrophically during the end milling of the 20%SiC/Al composite. Tomac and Tonnesson [4] developed a tool life relationship for carbide tool during the machining of SiC/Al composite at speeds lower than 100 m/min. They attribute the increases in the tool life at higher feed rates to the thermal softening of the composites. They suggested that coatings with less hardness than that of Al 2O3 and SiC offered little to no advantage during the machining of SiC/Al composites. The performance of CVD inserts to that of TiN, Ti(C,N) and Al2O3 coated tools by CVD method offered better overall performance than that of the other tool.Brun et al. [5] observed that the wear rate of ceramics tools was harder than silicon carbide and it was inversely proportional to their hardness. Tool wear was found to be invasively proportional to the feed rate. Winert [6] attributes the wear of the carbide tool to abrading Al2O3 indicated particles that forms on the surface and rub the tool in the direction of the chips flow. that the PCD tripped tools, while they lasted, were superior to the carbide tools and they in turn, were much better than the coated and uncoated HSS drills due to hardness of tool. Yanming and zehna [8], investigated the tool wear and its mechanism for cutting SiC particles reinforced Al matrix component. Hung [9] validity several tool wear model and stated that roughing with uncoated WC insert and then finishing with PCD tool was the most economical in way machining SiC reinforced composites. El-Gallab and Sklad [10] focused the effect of various cutting parameter on surface quality and extend of the sub-surface damage due to machining using PCD tools. our main objective of the present work to develop a composite material (Al2O3-p reinforced aluminium composite) and to study the effect of turning parameters like speed, feed, depth of cut and concentration of alumina on tool wear, surface roughness, and material removal rate. The above objective has been achieved by following steps: To prepare the Al2O3-p reinforced Al composite by sand casting To characterize the composite material and find the hardness and tensile strength. To identify ranges of process parameters for the turning of above materials. To perform the turning experiments and find out tool wear, surface roughness, material removal rate 2. DETAILS OF THE EXPERIMENTS 820 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 2.1 Selection of the workpiece material The manufacturing of the composite material we select two materials. The Al 2024 alloy is us Al2O3 is used as reinforcement material for manufacturing. The range of particle size of alumina is 16-30 μm and average particle size is 25μm. 2.2 Manufacturing of Al-Al2O3 composite The Al2O3 reinforced Al composite was produced by sand casting in foundry shop shown in fig (1).The dimensions of final product were 45mm in diameter and 300mm length. In order to obtain matrix material at the beginning phase of the production, 99.9% pure aluminium was melted in the crucible at 700°C on muffle furnace. Then the alumina was added in the crucible and steered continuously. In order to increase wetting capability of reinforcement, 2% of Mg was added. In our experiment three types of alumina particles reinforced metal matrix composites were casted. In the first type 10% by weight alumina and remaining aluminium and could able to mix 2% by weight alumina in the final cast product.In type second 20% by weight alumina and remaining aluminium and could able to mix 4% by weight alumina in the final cast product. In third type 30% by weight alumina and remaining aluminium and could able to mix 6% by weight alumina in the final cast product.The total 27 pieces were casted out of which 9 contained 2% alumina, another 9 contained 4% alumina and the remaining were of 6% alumina by weight and one piece of 100% aluminium by weight (Fig.2). Fig 1: A diagram shows crucible used for casting Fig 2: Workpiece of composite 2.3 Characterization of workpiece material Hardness, tensile strength, scanning electron microscope images and EDAX have been characterized of work piece material. Hardness of composite is tested on the Rockwell hardness testing machine .The model of machine is Fine Engineering industri ball penetration, of pressure on our three specimens of 2%, 4% & 6% by weight in alumina particles reinforced aluminium metal matrix composite. Tensile strength of composite specimen is measured by universal testing machine. The maximum capacity of our UTM is 40,000 kgf. When the composite specimens obtained from casting, their microstructure of 2%, 4%, and 6% will examined with the scanning electron microscope (SEM). The scanning electron microscope (SEM) is a type of Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 821 electron microscope that images the sample surface by scanning it with a high-energy beam of electrons in a raster scan pattern. Energy dispersive X- ray spectroscopy (EDAX) give the dispersive energy of materials in terms of percentage in the workpiece material. 2.4 SEM of composite specimens The SEM images of work piece material of 2%, 4%, and 6% reinforcement of alumina shown in fig (3) Fig (a) Fig (b) Fig (c) Fig 3: (a,b,c) SEM images of composite specimens, 2%, 4%, and 6% Cons. of alumina 2.5 Energy dispersive X- ray spectroscopy (EDAX) The EDAX analysis stands for energy dispersive X ray spectroscopy. It is a technique used for identifying the elemental composition of the specimen. The EDAX of workpeice material of 6% reinforcement of alumina shown in fig. (4). Element Wt.(%) Error Aluminium 92.49 4.4 Oxygen 8.95 1.8 50 cps/eV 40 30 O Al 20 10 0 1 2 3 4 5 6 keV Fig 4: A diagram shows the EDAX of workpiece 2.6 Selection of cutting tool Two types of tools for turning of composite material have been used first is coated and second is uncoated. The coated tool designation is DNMG 150608. It is the titanium nitride (TiN) coated carbide tool of golden (yellow) colour. The uncoated tool designation is DNMG 150608 THM. It is uncoated carbide tool of grey colour. The designation of tool holder which is used for hold the tool is MDJNR-2020-K15, MDJNR-2525-M15. 822 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 2.7 Design of experiments 2.7.1 Taguchi method Taguchi proposed an experimental plan in terms of orthogonal array that gives different combinations of parameters and their levels for each experiment. According to this technique, entire parameter space is studied with minimum number of experiments. This approach is based on the use of Orthogonal arrays to conduct small, highly fractional factorial experiments up to larger, full factorial experiment. In this research there are four controllable variables or process parameters namely, cutting speed, feed, depth of cut and % of concentration. Three levels were specified for each of the factors. The orthogonal array chosen was L9, which has 9 rows corresponding to the number of parameter combinations. Three trials were performed for each combination resulting in a total of 27 trials which allows analysis of the variance of the results. LEVEL P1 P2 P3 P4 1 265 0.29 1.0 2 2 400 0.32 1.5 4 3 535 0.35 2.0 6 Table 1: Details of process parameter Experiment 1 2 3 4 5 6 7 8 9 P1 1 1 1 2 2 2 3 3 3 P2 1 2 3 1 2 3 1 2 3 P3 1 2 3 2 3 1 3 1 2 P4 1 2 3 3 1 2 2 3 1 Experiment 1 2 3 4 5 6 7 8 9 Table 2: L 9 orthogonal array Speed Feed DOC Cons. 265 265 265 400 400 400 535 535 535 0.29 0.32 0.35 0.29 0.32 0.35 0.29 0.32 0.35 1.0 1.5 2.0 1.5 2.0 1.0 2.0 1.0 1.5 2 4 6 6 2 4 4 6 2 Table 3: L9 array of process parameter 2.8 Selected response variable The following response variables were selected for the present work: Tool wear rate (TWR) Surface roughness (Ra) Material removal rate (MRR) 2.9 Turning experiment The turning experiments were conducted under wet conditions on centre lathe model Waltham mass, U.S.A having height 1371.60mm, bed length 1066.80mm, bed width 177.80mm, bed to centre distance 127mm and motor 1hp. The 45mm diameter and 300mm length workpeice were subjected to tuning on the lathe. After the turning operation has been performed the tool wear, surface roughness, material removal rate was measured with the help of following equipments. 823 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 2.9.1 Tool wear Tool wear measurements were carried out by using zm_LV150A_360 microscope to determine the degree of flank wear on worn cutting tool after each test. The machining test will carried out for 60 second. During examination of tool wear, flank wear amount on free surface was taken as reference. The least count of this apparatus is 1 micron. 2.9.2 Surface roughness The surface roughness was measured by Mitutoyo company surtronic 3+ measuring equipment shown in fig (3.9). The cut of length is 0.8 mm and least count of Ra value is 1 micron. 2.9.3 Material removal rate It is calculated by change in workpiece volume to the time taken during turning. MRR Initial Volume Final Volume Time taken during turning 3. RESULTS AND DISCUSSION Hardness and Tensile strength of the workpieces are tested shows in fig 5,6 3.1 Hardness 3.2 Tensile Strength Fig 5: Hardness V/s reinforcement ratio curve Fig 6: Tensile strength Vs reinforcement ratio curve Experiments data is analyzed by using signal to noise ratio (S/N ratio) and Analysis of Variance (ANOVA). Based on the results of the S/N ratio and ANOVA, optimal parameter settings for better accuracy are obtained and verified experimentally. Regression models are developed to get the compensation factor for any set of process parameters.In Taguchi method, S/N ratio is measure of quality characteristics and deviation from the desired value. The term signal represents the desirable value (mean) and the noise represents the undesirable value (Standard Deviation from Mean) for the output characteristic [15]. The S/N ratio ( ) is defined as -10 log (M .S.D. ) (1) where, M .S .D. is the mean-square deviation for the output characteristic.Smaller the better type of S/N ratio is used in analysis for better accuracy. For smaller the better case, the S/N ratio is obtained by [15] 824 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 M .S .D. 1 n n i 1 Y 2 i (2) where, n is the total number of the experiments in the orthogonal array and Yi is the mean percentage hardness for the ith experiment. S/N ratios for each of the experiment is calculated and presented in table 4.1. The effect of a factor level is defined as the deviation it causes from the overall mean. The overall mean S/N ratio ( m ) of the experiments is calculated by [15] m Where, i is the mean S/N ratio of the 1 n n i 1 i (3) i th experiment? All three levels of every factor are equally represented in the nine experiments. Thus m is a balanced overall mean for the entire experiment. Since the experimental design is orthogonal, it is possible to separate out the effect of each factor at each level. Mean response is the average of quality characteristic for each parameter at different level. S/N ratio and tool wear, surface roughness and material removal rate for each parameter at each level can be calculated from mean S/N ratio and tool wear, surface roughness and mrr of each of the experiment. The TW, SR and MRR for each of the parameter at each level are calculated. These are also called as main effects. 3.1 Coated tool 3.1.1 Tool wear Fig 7: Effect of process parameter on tool wear Fig 8: Effect of Signal to noise ratio on tool wear 3.1.2 Surface roughness Figure 4.3: Effect of process parameter on Surface roughness Fig 9: Effect of Signal to noise ratio on Surface roughness Fig 10:Effect of Signal to noise ratio on Surface roughness Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 3.1.3 MRR Fig 11: Effect of process parameter on MRR Fig 12 : Effect of Signal to noise ratio on MRR 3.2 Uncoated tool 3.2.1 Tool wear Fig 13: Effect of process parameter on tool wear Fig 14: Effect of Signal to noise ratio on tool wear 3.2.2 Surface Roughness Fig 15: Effect of Signal to noise ratio on Surface roughness Fig 16: Effect of Signal to noise ratio on Surface roughness 3.2.3 MRR Fig 17 : Effect of process parameter on MRR Fig 18 : Effect of Signal to noise ratio on MRR 3.3 Analysis of variance (ANOVA) Purpose of ANOVA is to investigate the parameters, whose combination to total variation is significant. 825 826 Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 3.3.1 Coated tool 3.3.1.1 Tool wear 3.3.1.2 Surface Roughness b) a) Fig 19: % contribution of parameters on coated tool on a) Tool Wear 3.3.1.3 MRR c) b) Surface Roughness c) MRR 3.3.2 Uncoated Tool 3.3.2.1 Tool wear 3.3.2.2 Surface Roughness b) a) Fig 20: % contribution of parameters on coated tool on a) Tool Wear 3.3.2.3 MRR c) b) Surface Roughness c) MRR 4. Conclusions In this study the machinability and mechanical properties of the alumina reinforced aluminium composite material has examined. The effect of cutting parameter on the tool wear rate, surface roughness and material removal rate were measured. The following conclusions have been drawn. It has been observed that the life of coated tool is more than the uncoated tool. The tool wear rate increases as the reinforcement ratio increases in the composite material. The cutting speed is main parameter which affects the tool wear, surface roughness and material removal rate. Machinability of this composite material is very different from traditional materials because of abrasive reinforcement element. Due to this abrasive nature of alumina causes more wear on cutting tools. Feed rate is not as effective as cutting speed on tool wear, but as feed rate increases, the wear of cutting tool also increases. It has been observed that increase in reinforcement ratio effects surface roughness inversely. Puneet Bansal and Lokesh Upadhyay / Procedia Engineering 51 (2013) 818 – 827 827 Surface finish increased as the cutting speed increases. The higher the reinforcement ratio less is the material removal rate. With increase in reinforcement ratio, the hardness and tensile strength of composite material found to be increased. Taguchi method has been adopted for the design of experiments and the results have been analyzed by minimizing S/N ratio and ANOVA 4. References 1. Kilickap, E.,Cakir, O., Aksoy,M., Inan, A.,2005. Study of tool wear and surface roughness in machining of homogenized SiC-p reinforced aluminium metal matrix composites.J.Mater. Process. Technol. 164-165,862-867. 2. Kilickap, Orhan Cakir 2008.Investigate the mechanical and machinability properties of SiC-p reinforced AlMMC. Journal of materials processing technology 198 (2008) 220-225. 3. C.T. Lane, Drilling and tapping of SiCp reinforced Al, in: Proceedings of theMachining of Composite Materials Conference, ASM International, Pittsburgh, PA, October 1993. 4. N. Tomac, K. Tonnesson, Machining of particulate Al matrix composites, Ann. 5. M.K. Brun, M. Lee, F. Gorsler, Wear characteristics of various hard materials CIRP 41 ( ) (1992) 55 58. for machining SiCp reinforced aluminium alloy, Wear 104 (1985) 21 29. 6. K. Winert, A consideration of tool wears mechanism when machining metal matrix composites, Ann. CIRP 42 (1) (1993) 95 98. te, Process. Adv. Mater. 2 (1992) 7. 37 46. 8. Q. Yanming, Z. Zehna, Tool wear and its mechanism for cutting SiC p reinforced Al matrix composites, J. Mater. Process. Technol. 100(2000) 194 199. 9. N.P. Hung, F.Y.C. Boey, K.A. Khor, C.A. Oh, H.F. Lee, Machinability of cast and powder formed aluminium alloys reinforced with SiC particles, J. Mater. Process. Technol. 48 (1 4) (1995) 291 297. 10. M. El-Gallab, M. Sklad, Machining of Al/SiCp metal matrix composites. Part II. Workpiece integrity, J. Mater. Process. Technol. 83 (1998) 277 283. 11. Akdogan, A.,Ozben, T.,2001 Investigation of the mechanical properties of produced squeez casting method with SiC-p reinforced metal matrix composite materials. In: Proceeding of the 2 nd Mechanical Engineering and Manufacturing Technologies symposium, Turkey, pp. 358-367 12. N. Raghunath, P.M. Pandey , Improving Accuracy through shrinkage modeling by using Taguchi method in SLS, International Journal of Machine Tools and Manufacture, 2007, 47, pp 985-995 13. W.H. Yang, Y.S. Tarng, Design optimization of cutting parameters for turning operations based on the Taguchi method, Journal of Materials Processing Technology 84 (1998) 122 129. a McGraw Hill, Edition, 2005. 14. 15. B.L.Juneja, G.S. Sekhon and Nitin Seth: Fandamental of metal cutting and machine tools, New age publication Edition, II. 16. Milton.C.Shaw: Metal cutting principles. 17. E. Paul Degarmo and J. T. Black, Materials and processes in manufacturing.