Thermal characteristics in milling Ti6Al4V with polycrystalline diamond tools

Int J Adv Manuf Technol (2014) 75:1077–1087 DOI 10.1007/s00170-014-6094-y ORIGINAL ARTICLE Thermal characteristics in milling Ti6Al4V with polycrystalline diamond tools Wencheng Pan & Songlin Ding & John Mo Received: 20 February 2014 / Accepted: 23 June 2014 / Published online: 10 August 2014 # Springer-Verlag London 2014 Abstract The low thermal conductivity and high chemical affinity of Ti6Al4V make it extremely difficult to machine. The thermal characteristics in milling Ti6Al4V with polycrystalline diamond (PCD) tools were studied in the paper. A predictive model was developed and validated to investigate the relationship between average cutting temperature and machining parameters. X-ray diffraction (XRD) method was applied to examine residual chemical components on the PCD tools. Evidences of material diffusion and chemical reaction on the PCD tool showed that some region of the cutter suffered from higher than detected temperature. Based on SEM photos of serrated chips, serration frequency was investigated. Results from chip morphology illustrated that serration frequency changed on each single chip. W, L xi, yi, zi Keywords Ti-6Al-4Valloy . PCD tool . Cutting temperature . Thermal analysis The high strength, low weight ratio, and great corrosion resistance make titanium alloy Ti6Al4V a popular material in aerospace, biomedical, marine, and chemical industries. However, due to its low thermal conductivity [1], Ti6Al4V is difficult to machine. To improve the machinability, many researches have been conducted in the past decades to study the thermal effects in milling Ti6Al4V with focuses on the analysis of cutting temperature, chemical components, and chip morphology [2, 3]. Polycrystalline diamond (PCD) is one of the advanced tool material owing to its excellent wear resistance and high thermal conductivity. PCD tools have been applied in practice for the machining of Ti6Al4V. For example, Emmanuel et al. [4] investigated the surface integrity and performance of PCD tools by applying different cooling conditions in turning processes. Amin et al. [5] found that PCD tool had better wear resistance by comparing it to tools made of carbon tungsten. Kuljanic et al. [6] investigated the life of PCD tools in end milling with a tool of 32 mm in diameter. A tool life of 381 min was achieved when the cutting speed was 110 m/min and feedrate was 0.125 mm. Anhai et al. [7] performed the analysis of tool failure mechanism in the experiment of face Nomenclature ap c f Ki m1, m2, m3 Axial cutting depth Thermal conductivity of workpiece Feed The constants of cutting temperature Three empirical parameters to calculate cutting force components qi The heat source of shear plane and flank R1, R2, α1, α2, The coefficients of cutting temperature α3, α4, α5, α6 model v Cutting speed W. Pan (*) : S. Ding : J. Mo School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Melbourne, Australia e-mail: wen254968@gmail.com α θi τ ρ The width and length of heat source The dimension of measuring point in the coordinate system of shear plane heat source or flank heat source Diffusivity of workpiece The cutting temperature which is determined by shear plane heat source or flank heat source Time Density 1 Introduction 1078 Int J Adv Manuf Technol (2014) 75:1077–1087 Table 1 Material properties of Ti6Al4V Grade Tensile strength (Mpa) 0.2 % Proof stress (Mpa) Elongation (%) Thermal conductivity (w/mk) Thermal diffusivity (10−6 m2/s) 5 895 228 10 6.51 0.509 milling Ti6Al4V with PCD tool and found that the tool failure was mainly caused by premature breakage and synergistic interaction among adhesive wear and abrasive wear. More recently, a research to find appropriate machining parameters for high-speed milling Ti6Al4V with PCD tool was carried out by Gert et al. [8]. However, regarding the thermal aspects, little research has been carried out in the public domain to investigate the relationship between the cutting temperature and machining parameters by using PCD tools in the process of milling Ti6Al4V. Various methods have been developed for the measurement of cutting temperatures. For example, Le Coz et al. [9] successfully applied a thermocouple system in the test of dry milling Ti6Al4V. By setting the thermocouple sensor on the tool tip, the system was able to directly monitor and record the dynamic temperature of the tool. In the experiment conducted by Masahiko et al. [10], the proposed system consisted of an infrared radiation pyrometer, optical fiber, and a fiber coupler. In addition, Pittala and Monno used an infrared thermal camera to directly measure the temperature of the cutting zone [11]. By comparing this method with other approaches, the infrared camera (IRC) was found easy to use and was more practical in most milling systems. Cutting temperature is sensitive to the machining parameters such as cutting speed (vc, m/min), feed (ft, mm/tooth), and axial cutting depth (ap, mm). As found by Ugarte et al. [12], by using an IRC in the milling of Ti6Al4V, the temperature rose with the increase of cutting speed. In turning EN-31 steel alloy with carbide tools, Abhang and Hameedullah found that cutting temperature rose with the increase of vc, ft, and ap [13]. Similar conclusion was made by Zhou et al. [14] through the experiment of micro-milling aluminum alloy with TiAlN tools. The effects of machining parameters have also been investigated theoretically by using analytical models. For example, Lin et al. [15] developed a thermal model for endmilling process by considering the flank rubbing effect. In their model, cutting temperature was indirectly affected by the cutting speed through the generation of thermal energy and the fraction of flank wear heat/shear plane heat. According to Cui et al. [16], Table 2 Chemical composition of Ti6Al4V the minimum transient average tool temperature could be obtained by adopting suitable cutting parameters; the instantaneous uncut chip thickness determined by the feed rate was a critical variable in the calculation of heat energy and tool-chip contact length. Chemical reaction (e.g., oxidation or graphitization) and material diffusion are two forms of damage which frequently occurred in the machining of Ti6Al4V with PCD tools [17]. By using X-ray diffraction (XRD) method, the chemical components remained on the tool can be identified and the cutting temperature can be induced indirectly by checking the temperature at which chemical reaction or material diffusion takes place. Deng et al. [18] have applied the XRD method in the study of turning Ti6Al4V with tungsten carbide (WC) tools. By examining the samples of WC tool, they found that the oxidation occurred when the sample was heated up to 800 °C. König and Neises also found that the material diffusion occurred in the process of turning Ti6Al4V by using PCD tools [19]. The result agrees to the analysis by Amin et al. [5] in milling Ti6Al4V with both WC tools and PCD tools. Serration chip is one of the important thermal characteristics in milling Ti6Al4V. Generally, serration is known as the result of adiabatic shearing (ABS), and it always occurs in the zone which experiences high strain rate [20, 21]. According to Sima and Ozel [22], adiabatic shearing bands could be observed clearly when the cutting speed was larger than 60 m/ min with the feed above 0.05 mm/rev. When the machining parameters were large enough to cause obvious chip serration, the chip serration frequency was sensitive to the machining parameters, geometrical effect, the thermal properties of the cutting tool or workpiece, and the cooling efficiency. According to the analysis conducted by Molinari et al. [23], the chip serration frequency was proportional to the cutting speed. And lower thermal conductivity could cause higher than normal serration frequency [24]. PCD has higher thermal conductivity than conventional tool materials. In the process of milling Ti6Al4V, it is important to understand how this difference will affect the shape of the chips. Unfortunately, little research has been conducted so far to analyze the serration frequency in milling titanium alloy with PCD tools. Ti6Al4V Nitrogen Carbon Hydrogen Iron Oxygen Aluminum Vanadium The rest 0.03 0.08 0.01 0.3 0.23 5.5–6.75 3.5–4.5 Int J Adv Manuf Technol (2014) 75:1077–1087 1079 Based on experimental results, this paper investigated the effect of machining parameters on cutting temperature by monitoring the temperature in the cutting region. A predictive model of cutting temperature was developed; chemical components in the PCD tools were analyzed with XRD method. By using the SEM device, the morphology of chip in different machining conditions was investigated. 2 Experiment setup 2.1 Material information The general mechanical properties and chemical compositions of Ti6Al4V are listed in Tables 1 and 2, respectively [25, 26]. The PCD material used in this research was CTB010 made by Element Six. The grain size is 10 μm. The properties of PCD are shown in Table 3 [27]. The PCD inserts were brazed on a tool body made of WC. The helix angle of the tool is 0°, and the front angle θa and clearance angle θb are 4° and 10o, respectively (Fig. 1). The diameter of the PCD tool is 6 mm. 2.2 Experiment setup The cutting experiments were carried out on a four-axis HAAS milling machine. The cutting force signal was collected through an eight-channel dynamometer (Kistler 5070) installed underneath the workpiece. The coupler was a six-channel charge amplifier (Kistler 5070). The force single was recorded via a DAQ card (National Instrument model 9257). The setup of the experimental system was illustrated in Fig. 2a. To simplify the analysis of relevant factors, the tool paths were straight lines along the edge of the workpiece. The FLIR infrared camera was fixed in the position shown in Fig. 2b. Twenty-two cutting tests were carried out. The detailed cutting parameters are listed in Table 4. Fig. 1 Geometry of the PCD tool cutting process, and it is unevenly distributed along the cutting edge of the tool. However, due to the complexity of the rotating cutting tool and the disturbance of splashing coolant, it is impossible to accurately measure the cutting temperature at the cutting edge in real-time in the milling process. In practice, it is more important to analyze material behavior and find out the relationship between cutting parameters and the cutting temperature in the cutting zone, although the temperature obtained may not be the exact real-time temperature on the cutting edge. To investigate the relationship between machining parameters and the cutting temperature, the temperature measuring system shown in Fig. 2b was set up. Point P is the measuring point which is located in the cutting zone of the tool. It is assumed that the temperature measured on point P represents the average cutting temperature in the cutting zone. The infrared image of the static milling system is shown in Fig. 3a. Figure 3b illustrates the infrared image captured in test 13. It can be seen that the measuring point (P) is at the average cutting temperature of the cutting zone in the milling process. 3 Results and analysis 2.3 Measurement of cutting temperature 3.1 Average cutting temperature Cutting temperature is an important factor that affects cutting forces. High cutting temperature may soften workpiece material and leads to the decrease of cutting force. The cutting temperature at the cutting edge is dynamically changing in the As illustrated in Fig. 4a, it can be assumed that the cutting temperature at one fixed point in the cutting zone is caused by two heat sources from the shearing plane and the flank plane. Table 3 Properties of PCD Type of PCD Grain size (μm) Elastic modulus (MPa) Hardness (Gpa) Density (g/cm3) Thermal conductivity (w/mk) CTB010 10 890–900 50 (8,000 HV) 4.12 560 1080 Fig. 2 Experimental system setup. a Dynamic cutting force measuring system. b Thermal effect monitoring system Int J Adv Manuf Technol (2014) 75:1077–1087 (b) (a) P Workpiece IR Camera ©exit ©start vc Tool ft According to Lin et al. [15], the temperature rise caused by each individual heat source at a fixed point M can be expressed as follows: θi ¼          −y2 Q xi xi −W zi zi −L i piffiffiffiffiffiffiffiffiffi e 4ατ erf pffiffiffiffiffiffiffiffi −erf pffiffiffiffiffiffiffiffi ðerf pffiffiffiffiffiffiffiffi −erf pffiffiffiffiffiffiffiffi 8cρ πατ 4ατ 4ατ 4ατ 4ατ ð1Þ where c, ρ, W, L, α, and τ are specific heat capacity, density, length and width of rectangular heat source, thermal diffusivity, and time in actual milling process; s and f indicate shear plane and friction plane of the tool—chip interface as illustrated in Fig. 4a. And the location of M in the local shearing and friction coordinate systems can be described as (xs, ys, zs) and (xf, yf, zf). Therefore, Eq. (1) can be simplified as θi ¼ K i ðx; y; z; τ ÞQi ; i ¼ s; f ð2Þ where K=HJ, and the expression of H and J are as follows: 8 > > > < −y2 i e 4ατ pffiffiffiffiffiffiffiffiffi ; i ¼ s; f 8cρ πατ         > xi xi −W zi zi −L > > : J i ¼ erf pffiffiffiffiffiffiffiffi −erf pffiffiffiffiffiffiffiffi ðerf pffiffiffiffiffiffiffiffi −erf pffiffiffiffiffiffiffiffi ; i ¼ s; f 4ατ 4ατ 4ατ 4ατ Hi ¼ ð3Þ Table 4 Cutting parameters Test number Cutting speed Vc (m/min) Axial cutting depth ap (mm) Feed rate fz (mm/rev) Material removal rate (mm3/min) Contact area (mm2) 1 2 3 4 5 6 7 8 9 10 11 12 13 65.9734 87.9646 109.9557 131.9469 153.9380 175.9292 197.9203 219.9115 131.95 131.95 131.95 131.95 131.95 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.2 0.3 0.4 0.5 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.03 0.03 0.03 0.03 0.03 105 140 175 210 245 280 315 350 126 252 378 504 630 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.003 0.006 0.009 0.012 0.015 14 15 16 17 18 19 20 21 22 131.95 131.95 131.95 131.95 131.95 131.95 131.95 131.95 131.95 0.6 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.03 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 756 84 168 252 336 420 504 588 672 0.018 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016 Int J Adv Manuf Technol (2014) 75:1077–1087 Fig. 3 Thermal images of milling process. a The image before cutting. b The thermal image of test 13 1081 (a) (b) Measuring point P Measuring point P To analyze the value of Ki, four assumptions were made in the calculation: 1. The measuring point is at the same location in each milling cycle, and the area of heat source remains the same value. Therefore, the coordination should be of the same value, i.e., the values of (xs, ys, zs) and (xf, yf, zf) are constant. 2. The measuring time is the same in each milling test, namely, the value of τ is constant. 3. The thermal parameters of the workpiece are constant. 4. W and L are equal to the values of feed per tooth and the axial cutting depth. According to assumptions 1–4, the value of H is constant. However, J is still variable when machining parameters are changed. Because the temperature measured in this experiment is considered as the average cutting temperature, the location of measuring point P can be arbitrary on the surface of the chip. Therefore, it can be assumed that xs =xf, ys =yf, zs =zf. According to the experimental measurement of tests 9–22, the location of point M in friction heat source coordinate system can be defined as xf =0.01 mm, Fig. 4 The illustration of rectangle heat source and the position of measuring point. a The position of heat source and measuring point. b The assumed position of measuring point in friction plane coordinate system yf =0.2 mm, zf =0.1 mm, and the processing time τ for one milling cycle is 3 ms. By substituting the location, machining parameters and material parameters into the expression of J, it can be obtained that the range of J with different feed and depth of cut are from 0.003 to 0.03. It is obvious that heat source Q is also an important factor in determining the value of the temperature and it is proportional to the cutting temperature. Theoretically, the heat source consists of two essential elements: the heat generated by shearing and the heat generated by friction. According to Abukhshim et al. [28], these two parts of heat can be shown as such:     Qi v; f t ; ap ¼ F i v; f t ; ap vτ; i ¼ s; f ð4Þ Then, the cutting temperature can be described as θi ¼ H J i F i vτ ð5Þ It has been known that the changes of v, ft, and ap will result in the variation of the peak values of cutting forces. According to Anayet et al. [29], the empirical function of cutting force can be expressed as 2 m3 F ¼ Avm1 f m t ap Measuring point P (a) W ð6Þ (b) xs W L fiction Heat source planes O shearing tc L zs ys P(0.2,0.2,0.3) 1082 Int J Adv Manuf Technol (2014) 75:1077–1087 Table 5 Empirical parameters Parameters’ name Values Parameters’ name Values α1 α2 α3 Rs −1.5490 −0.6144 0.1600 40235.4520/Js α4 α5 α6 Rf 1.7052 0.6273 0.1600 0.0996/Jf It is obvious that cutting force has an exponential relationship with machining parameters. And the variation of machining parameters will finally lead to the change of the average cutting temperature. By considering the sources of the cutting heat, the relationship between cutting parameters and the average temperature at point M can be demonstrated by Eq. (7): θe ¼ θs þ θ f ¼ Rs vα1 f αt 2 aαp 3 þ R f vα4 f αt 5 aαp 6 ð7Þ Fig. 6 The thermal effect of changing axial cutting depth (ap) 3.2 Prediction and analysis of cutting temperature 3.2.1 Analysis of cutting temperature where α1, α2, α3, α4, α5, and α6 are empirical constants. Rs and Rf are two functions of K1 and K2 which can be expressed as where Ci (i=s, f) is a constant in the equation; the values of Rs and Rf can be assumed as the function which is determined by the value of Ji (i=s, f). By substituting the experimental data of cutting temperature and corresponding machining parameters into Eq. (7), the values of above parameters can be calculated. The results of the calculation are listed in Table 5. The comparison between predicted cutting temperature and the experimental results is shown in Figs. 5, 6, and 7. It can be seen in the figures that the predicted cutting temperatures are reasonably accurate. In Fig. 5, the results from calculation match the experimental results at the accuracy of up to 99.5 % when the axial cutting depth is between 0.4 and 0.6 mm. Figure 5 illustrates the predicted average temperature at point P and the actual temperature at the same location with various cutting speeds. The experimental data was collected in tests 1–8 with machining parameters listed in Table 4. The increase of cutting speed in the milling tests directly led Fig. 5 The thermal effect of changing cutting speed (Vc) Fig. 7 The thermal effect of changing feed rate (ft) Ri ¼ C i K i ; i ¼ s; f ð8Þ Int J Adv Manuf Technol (2014) 75:1077–1087 1083 Fig. 8 The abrasive damage on flank of PCD tool Flank wear of PCD tool to the rise of cutting temperature. The range of cutting temperature was found to be between 137 to 220 °C. Through generating more heat in the milling process, both shearing and friction contributed to the increase in temperature caused by higher cutting speed. Due to the poor thermal conductivity of Ti6Al4V, there was a significant increase in the average temperature at point P at the final stage. To investigate the effect of axial cutting depth on cutting temperature, six cutting tests (tests 9–14) were carried out in the same milling system. The results are plotted in Fig. 6. Because the increase of axial cutting depth caused the increase of contact area between the PCD tool and Ti6Al4V Abrasive wear fd PCD Tool Hard friction area Ft workpiece, which resulted in the generation of more heat, it can be seen in Fig. 5 that the temperature raises from 100 to nearly 200 °C. The thermal effects of feed rate are shown in Fig. 7. The data are the results of tests 15–22. Similar as the effect of increasing axial cutting depth, by applying larger feed, the interface area of front tool cutting plane and workpiece increased and this led to the rise of cutting temperature. The three-dimensional image of the PCD insert in Fig. 8 was taken by using the Alicona Microscope. It can be seen in the image that the flank of the PCD tool was damaged by abrasive wear which was the result of serious frictions during the machining process. Such great change of flank wear had not been found in tests 9–14. It is possible that the damage at the flank of the tool was caused by the built-up edge (B.U.E) and chipping. Then, the irregular surface of worn flank would result in the generation of more heat at the later stage as illustrated in Fig. 9. Therefore, it can be concluded that the flank of the tool, if more prone to damage with the increase of feed and the average cutting temperature, would rise due to the additional heat generated by the damaged surface. 3.2.2 FEA model Ti6Al4V Workpiece Fig. 9 The illustration of friction area on tool flank To investigate temperature distribution on the cutting tool in addition to analyzing the average temperature in the cutting 1084 Int J Adv Manuf Technol (2014) 75:1077–1087 Fig. 10 The FEM result of milling process. a The 3D milling model of test 14. b The average cutting temperature nephogram of cutter (a) (b) Cutting zone Tool Ti6Al4V zone, a three-dimensional finite element analysis (FEA) model (Fig. 10a) was developed by using the same machining parameters and cutting tool as applied in test 14. The JohnsonCook stress flow expression was used to describe the material behavior of Ti6Al4V. Material parameters A, B, n, C, m, and friction coefficient are listed in Table 6 [30]. It can be seen that the highest temperature in Fig. 10b which is close to 500 K (227 °C) is higher than the average cutting temperature measured in test 14. Because the temperature measured in the cutting region is the averaged cutting temperature, theoretically it should be lower than the temperature at the cutting edge. 3.2.3 Discussion Similar experiments have been conducted by some other researchers as well. For example, Balkrishna et al. [31] found that the temperature increased with the increase of cutting speeds when the applied cutting speed was lower than 150 m/min, but the temperature dropped when the cutting speed became higher. The little difference between their results and our findings was caused by the different thermal conductivity of different tool materials. In Balkrishna’s experiment, WC other than diamond cutting tools was applied. The thermal conductivity of PCD is about five times higher than that of tungsten carbide (WC). Therefore, the temperatures Table 6 Johnson–Cook parameters and friction coefficient A B C n m μ 1,070 MPa A1 0.0395 845MPa A2 1.0072 0.025 A3 1.9234 0.58 A4 0.014 0.75383 A5 3.87 0.67 measured in our experiments were lower than those obtained with WC tools. 3.3 Residual chemical components on the PCD tool Four PCD tools were examined with XRD method to analyze the chemical components that remained on the tool surface. These tools were brand new before they were used in the experiments. The average machining time in each test was 3 min. Figure 11a, b shows the XRD results of tool 1 and tool 2 which were used in test 1 and test 8, respectively. Machining parameters of these eight tests were listed in Table 4. The cutting temperature in test 8 was higher than that in test 1 due to the higher cutting speed applied. The chemical components that remained on tool 1 were found to be the original materials: tungsten carbide, carbon (diamond), and cobalt (Co). More chemical elements such as TiC and W2C were detected on the surface of tool 2. Theoretically, these materials can only be formed in chemical reactions at an elevated temperature of up to 500 °C or higher. Therefore, it can be concluded that when high cutting speed was applied, the local temperature on the edge of the PCD cutter was high enough to initiate chemical reactions. Figure 11c, d shows the XRD results of PCD tool 3 and tool 4 which were applied in test 9 and test 14. Compared to test 14, smaller axial cutting depth was used in test 9 while the other machining parameters were of the same. According to previous results, the increase of axial cutting depth can cause the rise of cutting temperature. Cutting temperature in test 14 would be higher than that in test 9. From Fig. 11d, it can be seen that chemical reaction did occur in test 14; new material TiO2 and WO3 were found on the PCD surface of tool 4. However, examinations of PCD tool 3 (Fig. 11c) have not shown any new components. It indicates that no chemical reactions occurred in test 9 and the cutting temperature was low. PCD tool applied in test 9 was found to remain in good condition. Int J Adv Manuf Technol (2014) 75:1077–1087 1085 (a) (b ) (c) (d ) Fig. 11 Four XRD results of used PCD tools. a PCD tool used in test 1. b PCD tool used in test 8. c PCD tool used in test 9. d PCD tool used in test 14 3.4 Micromorphology of chips and the frequency of chip serration Figure 12 shows one of the chips collected in the experiments. It can be seen that two different sections existed on this chip. The two sections with different serration frequencies were separated by a clear boundary, which indicated that the chip formation suffered a great change during the material removing process. The different adiabatic shearing frequencies of the two sections were 0.44×103 KHz and 2.199×103 KHz, the latter is nearly five times higher than the former. Most chips of this experiment have the similar serration frequency. Similar as most other chips collected in the experiments, the change in serration frequency on this sample occurred at the potion of 25 % of total length (lTotal). Figure 13a shows the clear boundary existing between the two sections. By examining the dynamic cutting force in Fig. 13b, it can be found that the cutting force rose dramatically at the beginning of the milling cycle, but it decreased slightly in region A, as shown in Fig. 13b. In the milling process, the strain rate varies all the time because of the change in the thickness of uncut chips. Since the strain rate can significantly affect the chip formation, the unstable strain rate was one of the factors that caused the sudden change in frequencies. Meanwhile, more heat was accumulated and the heat could not be dissipated or taken away by the coolant due to the extremely low thermal conductivity of Ti6Al4V. Therefore, it is reasonable to conclude that the generated heat would provide the energy for changing chip serration frequency. 4 Conclusions This paper investigated the thermal characteristics in milling Ti6Al4V with PCD tools which include average cutting temperature, chemical components, and chip morphology. A predictive model was developed to calculate cutting temperature 1086 Fig. 12 The two sections with different adiabatic shearing frequencies. a The morphology of chip sample 1 with clear separation boundary of two different serration frequencies. b The magnified image of boundary between two sections. c Section A with 0.44×103 KHz. d Section B with 2.199×103 KHz Int J Adv Manuf Technol (2014) 75:1077–1087 (a) Boundary Section B Section A (b) Section A Boundary Section B (c) (d) of PCD tools to investigate the relationship between cutting temperature and machining parameters. By defining the measuring point, the values of cutting temperature can be monitored experimentally with the infrared camera device. Experimental results show that the temperature increase with vc, ft, and ap. Results from the model match the data measured in the cutting experiments. Chemical analysis was performed by using XRD method to check residual material on PCD tools. New chemical Fig. 13 Two sections of the different frequencies. a Sections with different frequencies of sample 2. b Dynamic cutting force of sample 2 components such as TiC and TiO2 were detected on some PCD tools and indicated that local cutting temperatures at the cutting edge were higher than 500 °C in these cutting tests. Various chip serration frequencies were observed on individual chips. The maximum difference of frequency between two sections was five times. The dramatically changing frequency was the result of heat accumulation and the change of chip thickness. The frequency change was found taking place at the position of 25 % of the total chip length. 2.199×103 KHz (a) (b) A l≈25% l total Section A Section B t≈25% Ttotal Int J Adv Manuf Technol (2014) 75:1077–1087 References 1. Manouchehr V, Fredrik S, Mathias A, Jan-Eric S (2013) A method for identification of geometrical tool changes during machining of titanium alloy Ti6Al4V. Int J Adv Manuf Technol 67:339–348 2. Rosemar B, Alisson DS, Machado R, Emmanuel OE, John B, Wisley FS (2013) Tool life and wear mechanisms in high speed machining of Ti–6Al–4V alloy with PCD tools under various coolant pressures. J Mater Process Technol 213:1459–1464 3. Mohd Hadzley AB, Izamshah R, Sarah AS, Nurul Fatin M (2013) Finite element model of machining with high pressure coolant for Ti6Al-4V alloy. Procedia Eng 53:624–631 4. Emmanuel OE, John B, Rosemar B, Da Silva O, Akir C (2007) Surface quality of finished turned Ti–6Al–4V alloy with PCD tools using conventional and high pressure coolant supplies. Int J Mach Tools Manuf 47:884–891 5. Nurul Amin AKM, Ahmad FI, Nor Khairusshim MK (2007) Effectiveness of uncoated WC–Co and PCD inserts in end milling of titanium alloy—Ti–6Al–4V. J Mater Process Technol 192–193: 147–158 6. Kuljanic, Fioretti M, Beltrame L, Rosa P, Miani F (1998) Milling titanium compressor blades with PCD cutter. Ann ClRP 47(1):61–64 7. Anhai L, Jun Z, Dong W, Jiabang Z, Youngwang D (2013) Failure mechanisms of a PCD tool in high-speed face milling of Ti6Al4V alloy. Int J Adv Manuf Technol 67:1959–1966 8. Gert AO, Guven A, Nico T (2011) The performance of PCD tools in high-speed milling of Ti6Al4V. Int J Adv Manuf Technol 52: 929–935 9. Le Coz G, Marinescu M, Devillez A, Dudzinski D, Velnom L (2012) Measuring temperature of rotating cutting tools: application to MQL drilling and dry milling of aerospace alloys. Appl Therm Eng 36: 434–441 10. Masahiko S, Takashi U, Hisataka T (2007) An experimental technique for the measurement of temperature on CBN tool face in end milling. Int J Mach Tools Manuf 47:2071–2076 11. Pittalà GM, Monno M (2011) A new approach to the prediction of temperature of the workpiece of face milling operations of Ti-6Al-4V. Appl Therm Eng 31:173–180 12. Ugarte A, M’Saoubi R, Garay A, Arrazola PJ (2012) Machining behaviour of Ti-6Al-4V and Ti-5553 alloys in interrupted cutting with PVD coated cemented carbide. Procedia CIRP 1:202–207 13. Abhang LB, Hameedullah M (2010) Chip-tool interface temperature prediction model for turning process. Int J Eng Sci Technol 2(4): 382–393 14. Xuance Z, Qingshun B, Kai Y, Zhi L (2010) Relationship between cutting temperature and cutting parameters of micro-milling. World Acad Sci Eng Technol 46 1087 15. Lin S, Peng FY, Wen J, Liu YZ, Yan R (2013) An investigation of workpiece temperature variation in end milling considering flank rubbing effect. Int J Mach Tools Manuf 73:71–86 16. Cui XB, Zhao J, Pei ZQ (2012) Analysis of transient average tool temperatures in face milling. Int Commun Heat Mass Transfer 39: 786–791 17. Machado AR, Wallbank J (1990) Machining of titanium and its alloys—a review. Proc Inst Mech Eng B J Eng Manuf 53:204 18. Deng JX, Li YS, Song WL (2008) Diffusion wear in dry cutting of Ti–6Al–4V withWC/Co carbide tools. Wear 265:1776–1783 19. König W, Neises N (1993) Turning TiAl6V4 with PCD. Ind Diam Rev 53(1):85–88 20. Puerta JD, Velásquez Bolle B, Chevrier P, Geandier G, Tidu A (2007) Metallurgical study on chips obtained by high speed machining of a Ti–6 wt.%Al–4 wt.%V alloy. Mater Sci Eng A 452–453:469–474 21. Miguélez MH, Soldani X, Molinari A (2013) Analysis of adiabatic shear banding in orthogonal cutting of Ti alloy. Int J Mech Sci 75: 212–222 22. Sima M, Ozel T (2010) Modified material constitutive models for serrated chip formation simulations and experimental validation in machining of titanium alloy Ti–6Al–4V. Int J Mach Tools Manuf 50: 943–960 23. Molinari A, Soldani X, Miguélez MH (2013) Adiabatic shear banding and scaling laws in chip formation with application to cutting of Ti–6Al–4V. J Mech Phys Solids 61:2331–2359 24. Baker M (2003) The influence of plastic properties on chip formation. Comput Mater Sci 28:556–562 25. American Society for Testing and Materials (ASTM), “Standard Specification for Titanium and Titanium Alloy Strip, Sheet, and Plate”, ASTM B265-99 26. Costan A, Dima A, Ioniţă I, Forna N, Perju M, Agop M (2011) Thermal properties of a Ti-6Al-4V alloy used as dental implant material. Optoelectron Adv Mater Rapid Commun 5:1 27. Collins JL, Cook MW, Ninnis T (2011) New developments in ultrahard machining of wood and non-metals. Ind Diam Rev 61(588):49–62 28. Abukhshim NA, Mativenga PT, Sheikh MA (2006) Heat generation and temperature prediction in metal cutting: a review and implications for high speed machining. Int J Mach Tools Manuf 46:782–800 29. Anayet UPM, Nurul Amin AKM, Faris WF (2009) Prediction of tangential cutting force in end milling of medium carbon steel by coupling design of experiment and response surface methodology. J Mech Eng 40:2 30. Umbrello D (2008) Finite element simulation of conventional and high speed machining of Ti6Al4V alloy. J Mater Process Technol 196:79–87 31. Balkrishna R, Chinmaya RD, Yung CS (2011) An experimental and numerical study on the face milling of Ti–6Al–4V alloy: tool performance and surface integrity. J Mater Process Technol 211:294–304