Tool Wear Model And Wear Mechanisms When Machining TiAlN . - MYTRIBOS
Jurnal Tribologi 24 (2020) 15-26 Tool wear model and wear mechanisms when machining TiAlN ball end mill with high thermal conductivity steel (HTCS 150) Mohd Fairuz Mohd Rashid 1, Mohd Hairizal Osman 2*, Mohd Hadzley Abu Bakar 3, Anis Afuza Azhar 3, Wan Azahar Wan Yusoff 3, Kunlapat Thongkaew 4 1 Jabatan Keselamatan dan Kesihatan Pekerjaan Melaka, Aras 3 dan 4, Menara Persekutuan, Jalan Persekutuan, Hang Tuah Jaya, 75450 Ayer Keroh, Melaka, MALAYSIA. 2 Fakulti Teknologi Kejuruteraan Mekanikal dan Pembuatan, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MALAYSIA. 3 Centre of Smart System and Innovative Design (CoSSID), Fakulti Kejuruteraan Pembuatan, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MALAYSIA. 4 Department of Industrial Engineering, Faculty of Engineering, Prince of Songkla University, 15 Karnjanavanich Rd., Hat Yai, Songkhla, 90110 THAILAND. *Corresponding author: hairizal@utem.edu.my KEYWORDS ABSTRACT Tool wear model HTCS-150 Milling Ball end mill Wear mechanisms The intent of this research is to develop the regression model and optimization focused on the relationship between the cutting parameters and wear performance when machining HTCS-150 by using Response Surface Methodology experimental design. Microscopy analysis was employed to identify surface characteristics. Experimental processes were carried out using Computer Numerical Control milling machine with ranges of cutting speeds of 484-553 m/min, feed rates of 0.31-0.36 mm/tooth, axial depth of cut of 0.1-0.5 mm and constant radial depth of cut of 0.01 mm. The results show that the model that developed adequately represent the process with modeling validation runs within the 90% prediction interval. The combination of cutting parameter for lowest tool wear recorded as 553 m/min cutting speed, 0.36 mm/tooth feed rate and 0.1 mm axial depth of cut. The wear on the cutting tool started at the centre of the flank face before generated to the near uppercontact zone. Dominant wear mechanisms appeared to be coating delamination, abrasion wear, chipping and adhesion wear. Received 27 September 2019; received in revised form 18 November 2019; accepted 22 January 2020. To cite this article: Rashid et al. (2020). Tool wear model and wear mechanism when machining TiAlN ball end mill with high thermal conductivity steel (HTCS 150). Jurnal Tribologi 24, pp.15-26.
Jurnal Tribologi 24 (2020) 15-26 1.0 INTRODUCTION High Thermal Conductivity Steel 150 (HTCS-150) can be considered a new class of steel that used as a die in a hot stamping process. Hot Stamping is a process where a sheet metal is heated up before stamped and quenched in the die enclosure, similar like metal stamping process. As the part heated, microstructure of the part changed from ferrite to austenite and further changed into martensite as the part cooled down inside the die enclosure (Ghiotti et al. 2016). Here, the strength of the part can be increased up to 3 folds, resulting better structural integrity when this sheet metal applied in structural components. As the cooling and heating involved in hot stamping, the die that used must possess higher thermal conductivity. The introduction of HTCS150 steel as a die for hot stamping process enables quenching process to be operated effectively as HTCS-150 not only exhibiting high thermal diffusivity but also high in hardness, wear resistance and hardenability. This material has also good resistance to thermal fatigue and thermal shock (Rovalma, 2012). HTCS-150 can be machined using rigid tooling by either rough or finish machining to form various shapes and patterns. In general, machining HTCS 150 alloy can be carried out at higher cutting speeds and heavy feed rates, especially in rough condition. Typically, between 30 to 40% of the workpiece weight is machined away to become a component. Rough machining is generally carried out when the steel is in soft condition, annealed state around 30 HRC before heat treatment. The die is then machined with ultra-precision cutting tool to remove the distortions and ensure that the steel surfaces have good finish and texture. To control the surface finish of HTCS-150, the wear performance of cutting tool plays important role. Wear characterization of cutting tool depended on many factors. The cutting parameters and contact conditions considered the most dominant one (Zainol and Yazid, 2018). Cutting parameters control the shearing action in the cutting zone which in the end controls the contact time and temperature generation in the cutting zone. Contact conditions depended on the shape of cutting tool that used in machining. In 5-axis die machining, carbide ball end mill frequently used as this cutting tool capable to shear the surface in flat and curvature shape. Since the contact area of ball end mill depended on the depth of cut and nose radius, different process parameters resulting different thickness of the chip to be removed. If the depth of cut is low enough, there will be no chip formation as the ball mill will shear the material in chipping zone with uncut chip formation (Klocke et al., 2011). Complex interaction between cutting parameters and contact conditions providing different wear mechanisms at the edge of cutting tool, which is need to be systematically examined. Previous literature review presented limited study that refers particularly to the wear mechanisms of ball end mill to machine die based materials. Koshy et al., (2002) studied the high speed machining of AISI D2 and AISI H13 tool steels by applying various ball end mill made from carbide, cermet and PCBN. The authors found that the tool life when machining AISI D2 is lower than machining AISI H3. An analysis of flank wear generally indicated that chipping, adhesion, attrition and fracture dominated the wear mechanisms for the tested tools. Dolinšek and Kopač, (2006) studied the mechanism of TiAlN and multi-layer TiAlN TiN cemented carbides ball end mill in machining 35CrMoV5 steel. The authors suggested that that wear patterns for ball mill similar like drill tool where wear developed at the centre before propagated to the flank area. Feed rate were the most influence parameters as compared to the cutting speed. The increasing of feed rate shifted the development of wear from flank area into the crater region. 16
Jurnal Tribologi 24 (2020) 15-26 Gopalsamy et al., (2009) studied the optimization parameters when milling H13 hardened steel using 10 mm TiN coated carbide ball end mill. Taguchi method and analysis of variance (ANOVA) were employed to analyse the effect of machining parameters on the tool life and surface finish. The researchers found that the optimum parameter for finish machining iswere 204 m/min cutting speed, 0.2 mm/tooth feed rate, 0.2 mm width of cut and 0.2 mm axial depth of cut. The cutting speed recorded as the most influence cutting parameter for tool life and surface roughness. SEM analyses showeds that the tool wear dominated by chipping and adhesion at the edge of cutting tool due to fluctuated stress imposed on the cutting edge. Klocke et al. (2011) investigated the performance of ball end mill during machining two type of steels with different thermal conductivity, coded as HS6-5-3PM and HS4-2-4PM. The tool performance was evaluated in term tool wear, cutting length and cutting force. TiAlN coated four flute ball end mill with 6 mm diameter of was employed to cut these steels. The researchers suggested that machining with material that has lower thermal conductivity would create localized thermal impact during the shearing process, which influence softening of the chip. On the other hand, machining with material that has higher thermal conductivity would benefit shearing process by providing easy penetration of heat into workpiece instead through the chip. In this study, the wear mechanisms when machining TiAlN coated carbide ball end mill with HTCS-150 were presented. The cutting conditions selected were based with those used in the industry. The study also involved with model development and the optimization of cutting parameter, which is updated version from Hadzley et al., (2016). Further observations on tool wear throughout the machining trials were presented to analyse the interaction between cutting tool and HTCS-150 at high temperature. 2.0 EXPERIMENTAL PROCEDURE High Thermal Conductivity Steel -150 (HTCS-150), supplied from industry being the main material to be investigated in this study. The material was prepared within the size of 60 mm x 60 mm x 10 mm block as shown in Figure 1(a). The properties of this material can be found in Rovalma, (2012). The cutting tool was 2 flutes PVD TiAlN coated carbide end mill with a nominal diameter of 20 mm, coded as SRFT20 as shown in Figure 1(b). Figure 1: Experimental setup (a) Material block (b) SRFT20 ball end mill. 17
Jurnal Tribologi 24 (2020) 15-26 For machining trials, Response Surface Methodology (RSM), with box-Behken experimental design were employed with total of 17 experimental run. The milling process was carried out under dry cutting condition using a MAZAK Variaxis 5-axis CNC milling machine as shown in Figure 2(a). The controlled machining parameter is shown in Table 1. The detail of parameter set according to RSM experimental design is shown in Table 2. After machining, tool wear was measured using tool maker microscope as shown in Figure 2(b). The measuring area focused from edge of cutting tool to the average wear area, as designated according to ISO 3685. In all tests, measurements were performed after completing 1000 passes for each running, which is equal 60 meter long. Further assessment to develop tool wear model and analyse the significant parameters that is affected tool wear have been executed by using to analysis of variance (ANOVA). 3D plot was deployed to find optimum cutting parameters based on the minimum tool wear. The model developed was validated using parameters within the range of machining trials and compared with the calculated values. Figure 2: (a) MAZAK Variaxis 5-axis CNC milling machine (b) Tool wear measurement method using tool maker microscope Table 1: Controlled machining parameters for study. Process Parameter Range Unit Cutting Speed 484-553 m/min Feed Rate 0.31-0.36 mm/tooth Depth of Cut 0.1-0.5 mm 18
Jurnal Tribologi 24 (2020) 15-26 Table 2: Experimental design according to RSM approach. Trial Cutting Speed, Feed Rate, Depth of cut, ap No Vc (m/min) Fz (mm/tooth) (mm) 1 484.00 0.31 0.30 2 553.00 0.31 0.30 3 484.00 0.36 0.30 4 553.00 0.36 0.30 5 484.00 0.33 0.10 6 553.00 0.33 0.10 7 484.00 0.33 0.50 8 553.00 0.33 0.50 9 518.50 0.31 0.10 10 518.50 0.36 0.10 11 518.50 0.31 0.50 12 518.50 0.36 0.50 13 518.50 0.33 0.30 14 518.50 0.33 0.30 15 518.50 0.33 0.30 16 518.50 0.33 0.30 17 518.50 0.33 0.30 3.0 RESULTS AND DISCUSSION 3.1 Tool Wear Model Table 3 shows the measurement of wear recorded for each machining trial. According to Table 3, minimum wear occurred at 553 m/min for cutting speed, 0.36 mm/tooth for feed rate and 0.30 mm on depth of cut (Trial No 4). The highest rake wear recorded was around 141µm near to the upper-contact zone while the central region recorded was around 108µm flank wear. On the other hand, maximum wear occurred at 518.50 m/min on cutting speed, 0.31 mm/tooth for feed rate and 0.5 mm on depth of cut (Trial No 11). Table 4 shows the analysis of variance (ANOVA) to analyse the significant parameters and potential interactions that affected tool wear. Based on p-value of less than 0.1, cutting speed, feed rate, axial depth of cut, interaction between cutting speed and feed rate, interaction between cutting speed and axial depth of cut, interaction between axial depth of cut and feed rate, cutting speed quadratic term, feed rate quadratic term and axial depth of cut quadratic term can be found significant to influence the tool wear value. The prediction model to represent the effect cutting parameters on the tool life can be denoted as coded equation of: 𝑇𝑜𝑜𝑙 𝑊𝑒𝑎𝑟 (𝑚𝑚) 4.49928 10 6 𝑉𝑐 2 7.76842 𝐹𝑧 2 3.26087 10 4 𝑉𝑐 𝑎𝑒 4.45560 10 3 𝑉𝑐 4.97984 𝐹𝑧 0.15283 𝑎𝑒 1.85279 Where unit for cutting speed, Vc in m/min, Feed rate, Fz in mm/tooth and Axial depth of cut, ae in mm unit 19
Jurnal Tribologi 24 (2020) 15-26 Table 3: Experimental design and result of tool wear. Trial Cutting Feed Rate, Depth of Tool No Speed, Fz cut, ap Wear Vc (m/min) (mm/tooth) (mm) (mm) 1 484.00 0.31 0.30 0.047 2 553.00 0.31 0.30 0.043 3 484.00 0.36 0.30 0.040 4 553.00 0.36 0.30 0.030 5 484.00 0.33 0.10 0.046 6 553.00 0.33 0.10 0.033 7 484.00 0.33 0.50 0.048 8 553.00 0.33 0.50 0.044 9 518.50 0.31 0.10 0.046 10 518.50 0.36 0.10 0.034 11 518.50 0.31 0.50 0.053 12 518.50 0.36 0.50 0.040 13 518.50 0.33 0.30 0.048 14 518.50 0.33 0.30 0.052 15 518.50 0.33 0.30 0.051 16 518.50 0.33 0.30 0.049 17 518.50 0.33 0.30 0.050 Source Model Cutting Speed, A Feed Rate, B Depth of Cut, C 2 A 2 B AC Residual Lack of Fit Pure Error Cor Total R-Squared Adj RSquared Table 4: ANOVA analysis table for Tool Wear Sum of Mean F p-value df Squares Square Value Prob F -4 -5 7.115 x 10 6 1.186 x 10 29.40 0.0001 1.201 x 10-4 1 1.201 x 10-4 29.78 0.0003 2.531 x 10-4 8.450 x 10-5 1 1 2.531 x 10-4 8.450 x 10-5 62.74 20.95 0.0001 0.0010 1.211 x 10-4 9.953 x 10-5 2.025 x 10-5 4.034 x 10-5 3.034 x 10-5 1 1 1 10 6 1.211 x 10-4 9.953 x 10-5 2.025 x 10-5 4.034 x 10-6 5.057 x 10-6 30.03 24.67 5.02 0.0003 0.0006 0.0490 2.02 0.2581 1.000 x 10-5 7.519 x 10-4 0.9463 0.9142 4 16 2.500 x 10-6 significant Not significant 20
Jurnal Tribologi 24 (2020) 15-26 Further analysis to determine the optimization parameters were executed based on the 3D and perturbation plots as shown in Figure 3. The plot shows that the minimum wear recorded at 0.022 mm, which located at interchanged reference point, correspond to cutting speed (553 m/min), Feed rate (0.36 mm/tooth) and axial depth of cut (0.1 mm). Such minimum point represents optimal conditions to produce the lowest tool wear based on the experimental design. Figure 4 shows 3D plot interaction between cutting speed and depth of cut. This plot is varying in cutting speed and depth of cut while feed rate is kept constant at 0.36 mm/tooth. Figure 3: Perturbation plot for the parameters A, B and C. Figure 4: 3D plot interaction between cutting speed and depth of cut, at the feed rate of 0.36 mm/tooth. In order to evaluate the reliability of the model developed, several machining trials were held using another range of parameters as shown in Table 5. The results from calculated and collected experimental data were compared. It shows that error between prediction value and actual value 21
Jurnal Tribologi 24 (2020) 15-26 are in range 2% to 9% error, which is less than 10% error conditions. This indicate that the mathematical model can be used and predict value of tool wear within confidence interval. Table 5: Validation data of tool wear. Machining Parameters Prediction Value Cutting Speed Feed Rate Depth of Cut (m/min) (mm/tooth) (mm) 500 0.32 0.2 0.050 520 0.34 0.4 0.049 540 0.35 0.4 0.042 Actual Value Error (%) 0.052 0.054 0.041 5 9 2 3.2 Wear Mechanisms Figure 5 shows the tool wear pattern that occurred at a cutting speed of 518.50 m/min, feed rate of 0.33mm/tooth and depth of cut of 0.30 mm. Wear area in Figure 5 can be divided into main observation area (A), left upper-contact zone (B), right upper-contact zone (C) and central zone (D). For most of the machining trials, the wear scar area demonstrated almost similar pattern where the wear generated focused at the central and the flank face where the major contact appeared. Wear at the central region initiated with rubbing action at the tool-workpiece contact. On this stage, the rotating cutting tools shear the metals, slowly remove the workpiece material according to the depth of cut. As the rubbing process prolonged, the temperature at the contact edge started to increase. The increment of heat should weaken the cutting tool edge as a result of thermal softening. Slowly, small amount of materials at the cutting tool edge started to detach in minor removal. Further rubbing process demonstrated accumulation of edge material removal of cutting tool, resulting wear to develop from central to the left and right upper-contact zones (Dolinsek and Kopac, 2006) Further observation throughout cutting tool nose radius detected dominant wear mechanisms starting with coating delamination, abrasion wear and chipping as shown on Figure 6. Coating delamination started when repetitive rubbing between cutting tool and workpiece resulting coating layer at the tool’s nose radius unable to resist friction and high temperature. As the machining prolonged, the coating layer had been delaminated and exposed the tool’s substrate to the cutting loads. As the substrate exposed without any protection, the other wear mechanism such as abrasive wear, adhesive wears, built up edge and chipping takes place. Abrasion wear occurred due to hard particles that rub the cutting tool and leaves the groove formation at the flank wear of the cutting tool (Norfauzi et al., 2018; Chintha et al., 2019). This process generally leads to the premature tool failure and affected to the machined surface. On the other hand, chipping is a failure mode in a form of crack on the cutting edge of the cutting tool (Wang et al., 2020). The chipping process begins from mechanical crack on the cutting edge which can gradually propagate deep into the cutting edge. Many factors contributed to the chipping processes such as impacts from cutting tool, cyclic and thermal load from milling process, material properties and thermal shocked (Schweinoch et al., 2015; Tiago et l., 2019). In addition, the combination of the crater wear and flank wear also contributed to the chipping or fracture. In this study, chipping may cause by the mechanical load from the rotational cutting tool (high feed rate and low cutting speed) at the upper-contact region. At higher feed rate (with low cutting speed), the impact force will increase as a result of larger amount of material need to be removed. Higher mechanical impacts from the rotational cutting tool provided severe fracture at the flank edge as the cutting tool unable to resist the load (Dolinšek et al., 2001). 22
Jurnal Tribologi 24 (2020) 15-26 Another significant observation throughout the cutting tool edges demonstrated the existence of adhesive wear in most of cutting conditions. Figure 7 presents some evidence adhesive wear which occur at the highest cutting speed of 518.50 m/min, feed rate of 0.33 mm/tooth and depth of cut of 0.30 mm. Adhesive wear is a formation layer welded on the wear surface during machining process. Normally, the attachment of molten layer is one of the indicators to determine the formation of this wear mechanism. The existence of adhesive wear is highly dependent on cutting speed and depth of cut. Increasing cutting speed enabled faster rotational contacts between cutting tool and workpiece. Such conditions promoting less time for heat generated to be dissipated, resulting softening condition of workpiece material which facilitate molten layer to be adhered on the cutting tool. On the other hand, increasing depth of cut enabled the thickness of the removed material sliding along cutting edge, increasing the temperature at the rake face and facilitating attachment of molten metal as a result of material plastic flow (Alabdullah et al., 2016). The appearance of molten layer attached on the tool surface could alter the tool-chip contact as well as cutting force. Changes in the tool-chip contact may affect shearing actions and surface finish of the machined component while change in the cutting force may increase the risk of tool breakage (Azlan et al., 2017). 4.0 CONCLUSIONS Series of machining trials were conducted to develop a model that correlate cutting parameters and tool wear when machining HTCS-150 using 20 mm TiAlN ball nose end mill coated carbide. Further observation on tool wear mechanisms were presented to analyse the interaction between cutting tool and HTCS-150 at high temperature. Based on the experimental results, specific conclusions have been concluded as below: 1. From the experimental data of RSM, empirical models were developed, and the confirmation experiments were performed, which were found within 90% confidence interval. 2. The optimal run conditions which provide lowest tool wear correspond to cutting speed (553 m/min), Feed rate (0.36 mm/tooth) and axial depth of cut (0.1 mm). 3. The results indicate that wear on the cutting tool started at the central and the flank face where the major contact appeared before generated to the near upper-contact zone. 4. Observation on the cutting edge shows that coating delamination, abrasive wear, chipping were dominant wear mechanisms on cutting tool. Further machining also observed molten layer attachment on the flank face, which lead to adhesive wear mechanism. 23
Jurnal Tribologi 24 (2020) 15-26 Figure 5: (a) Tool wear pattern occur when machining HTCS-150 (cutting speed: 518.50 m/min, feed rate: 033mm/tooth and 0.30 mm depth of cut) with main observation area (b) left uppercontact zone (c) right upper-contact zone (d)and central flank. 24
Jurnal Tribologi 24 (2020) 15-26 Figure 6: Coating delamination, minor Abrasion wear and chipping (Cutting speed: 484.0 m/min; feed rate: 0.36 mm/tooth and depth of cut: 0.30 mm). Figure 7: The formation of adhesive layer on tool insert during machining process of machining HTCS-150 at 518.50 m/min cutting speed; 0.33 mm/tooth feed rate and 0.30 mm depth of cut ACKNOWLEDGEMENT The authors would like to thank Faculty of Manufacturing Engineering and Universiti Teknikal Malaysia Melaka (UTeM) for their support that enabled this work to be carried out through the grant of FRGS/1/2017/TK03/FKP-AMC/F00341. REFERENCES Alabdullah, M., Polishetty, A., & Littlefair, G. (2016). Impacts of wear and geometry response of the cutting tool on machinability of super austenitic stainless steel. International Journal of Manufacturing Engineering, 2016. 25
Jurnal Tribologi 24 (2020) 15-26 Araújo, R. P., Rolim, T. L., Oliveira, C. A., Moura, A. E., & Silva, J. C. A. (2019). Analysis of the surface roughness and cutting tool wear using a vapor compression assisted cooling system to cool the cutting fluid in turning operation. Journal of Manufacturing Processes, 44, 38-46. Azlan, U. A. A., Hadzley, M., Tamin, N. F., Noor, F. M., Azhar, A. A., Yusoff, M. R., & Noriman, N. Z. (2017). Observation of built-up edge formation on a carbide cutting tool with machining aluminium alloy under dry and wet conditions. In MATEC Web of Conferences (Vol. 97, p. 01076). EDP Sciences. Chintha, A. R., Valtonen, K., Kuokkala, V. T., Kundu, S., Peet, M. J., & Bhadeshia, H. K. D. H. (2019). Role of fracture toughness in impact-abrasion wear. Wear, 428, 430-437. Dolinšek, S., & Kopač, J. (2006). Mechanism and types of tool wear; particularities in advanced cutting materials. Journal of Achievements in Materials and Manufacturing Engineering, 19(1), 11-18. Dolinšek, S., Šuštaršič, B., & Kopač, J. (2001). Wear mechanisms of cutting tools in high-speed cutting processes. Wear, 250(1-12), 349-356. Ghiotti, A., Bruschi, S., Medea, F., & Hamasaiid, A. (2016). Tribological behavior of high thermal conductivity steels for hot stamping tools. Tribology international, 97, 412-422. Gopalsamy, B. M., Mondal, B., & Ghosh, S. (2009). Taguchi method and ANOVA: An approach for process parameters optimization ofhard machining while machining hardened steel. Hadzley, A. M., Azahar, W. W. M., Izamshah, R., Shahir, K. M., Amran, A. M., & Afuza, A. A. (2016, February). Response Surface Methodology Approach on Effect of Cutting Parameter on Tool Wear during End Milling of High Thermal Conductivity Steel-150 (HTCS-150). In IOP Conference Series: Materials Science and Engineering (Vol. 114, No. 1, p. 012015). IOP Publishing. Klocke, F., Arntz, K., Cabral, G. F., Stolorz, M., & Busch, M. (2011). Characterization of tool wear in high-speed milling of hardened powder metallurgical steels. Advances in Tribology, 2011. Koshy, P., Dewes, R. C., & Aspinwall, D. K. (2002). High speed end milling of hardened AISI D2 tool steel ( 58 HRC). Journal of Materials Processing Technology, 127(2), 266-273. Norfauzi, T., Hadzley, A. B., Azlan, U. A. A., Faiz, M. M., Naim, M. F., & Aziz, A. A. (2018). Comparison machining performance of Al2O3, ZTA and ZTA doped Cr2O3 cutting tools on AISI 1045. Materials Research Express, 6(1), 016547. Nurul Fatin, M. R., Mohd Hadzley, A. B., Izamshah, R., Abdullah, R., & Amrand, M. A. (2015). An Experimental Study of Wear Mechanism on High Speed Machining of FC300 Gray Cast Iron Using TiAlN Coated Carbide Cutting Tool. In Applied Mechanics and Materials (Vol. 761, pp. 257-261). Trans Tech Publications Ltd. Rovalma (2012). Manual HTCS-150. 06 ed. Teressa. Schweinoch, M., Joliet, R., Kersting, P., & Zabel, A. (2015). Model-based investigation of thermal loading in milling processes including chatter. Procedia CIRP, 35, 85-90. Wang, W., Biermann, D., Aßmuth, R., Arif, A. F. M., & Veldhuis, S. C. (2020). Effects on tool performance of cutting edge prepared by pressurized air wet abrasive jet machining (PAWAJM). Journal of Materials Processing Technology, 277, 116456. Zainol, A., & Yazid, M. Z. A. (2018). Review of development towards minimum quantity lubrication and high speed machining of aluminum 7075-T6. Journal of Advanced Manufacturing Technology (JAMT), 12(1 (1)), 129-142. 26
Jurnal Tribologi 24 (2020) 15-26 Received 27 September 2019; received in revised form 18 November 2019; accepted 22 January 2020. To cite this article: Rashid et al. (2020). Tool wear model and wear mechanism when machining TiAlN ball end mill . The authors found that the tool life when machining AISI D2 is lower than machining AISI H3. An .
Tool wear is gradual and depends on tool and workpiece materials, tool shape, cutting fluids, process parameters, and machine tools Two basic types of wear: Flank wear and Crater wear Tool Wear (d) (e) (a) (b) (c) Figure 20.15 (a) Flank and crater wear in a cutting tool. Tool
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Tool wear Index, feed marks and surface finish Type of wear depends MAINLY on cutting speed If cutting speed increases, predominant wear may be “CRATER”wear else “FLANK”wear. Failure by crater takes place when inde
tool wear mechanisms were observed using the tool maker’s microscope and scanning electron microscope. The tool wear was found to be more rapid at larger radial depth of cuts at all three cutting speeds. It was also found that the main wear mechanisms presen
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