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International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN 2249-6890 Vol. 3, Issue 1, Mar 2013, 241-252 ©TJPRC Pvt. Ltd.
THREE DIMENSIONAL THERMAL MAPPING OF SINGLE POINT CUTTING TOOL USING FINITE ELEMENT METHOD AND ITS EXPERIMENTAL VERIFICATION GOURAB CHAKRABORTY1, SATYABRATA PODDER2 & UTTAM ROY3 1,2
Mechanical Engineering Department, Brainware Group of Institutions, Kolkata, West Bengal, India 3 Mechanical Engineering Department, National Institute of Technology, AP, Yupia, India
ABSTRACT Over the years, metal cutting researchers have developed a number of modeling techniques among which the Finite Element Method (FEM) has particularly become the most popular tool for simulating metal cutting processes. It is already known that during machining, the maximum temperature generated is on the chip-tool interface. Though majority of the heat generated is taken away by the chip, the amount of heat distributed in the work piece greatly affects the quality of machined part. In this study, the temperature distribution in the single point cutting tool is simulated using Finite Element Methods. For this, a special experimental set up has been fabricated where lathe turning of a single point cutting tool was carried out in dry condition as today’s manufacturing industry would like to embrace dry machining for both environmental and economic reasons. The temperature reading is taken using Alumel-Chromel (k type) thermocouple with the help of a Datalogger (DT-85). This temperature reading was further used as input for 3-D transient thermal modeling of the HSS cutting tool during machining.
KEYWORDS: Thermal Mapping, Single Point Cutting Tool, FEM INTRODUCTION The knowledge on the temperature distribution in tool is a matter of great importance due to the severe effects of intense local heat generated during machining which could affect the heat treatment or artificial aging properties, hardness and residual stresses of the material, all of which affect the fatigue life of the component. For the past fifty years metal cutting researchers have developed many modeling techniques including analytical techniques, slip-line solutions, empirical approaches and finite element techniques. In recent years, the finite element method has particularly become the main tool for simulating metal cutting processes [1, 2]. Finite element models are widely used for calculating the stress, strain, strain-rate and temperature distributions in the primary, secondary and tertiary sub-cutting zones. In consequence, temperatures in the tool, chip and work piece, as well as cutting forces, plastic deformation (shear angles and chip thickness), chip formation and possibly its breaking can be determined faster than using costly and time consuming experiments. It is especially important that FEM analysis can help to investigate some thermo dynamical effects occurring in the cutting zone which, as so far, cannot be measured directly [2]. An example for such effects is the influence of cutting tool rake surface on the heat transfer and friction, and resulting cutting temperature distribution in the chip and the tool. It should be noted that the majority of previous orthogonal metal cutting simulations is devoted to uncoated carbide tools and now the opposite trend to consider single and multiply coatings has been observed [2-4]. In fact, the first completed work focusing on the evaluation of a predictive orthogonal cutting model for coated carbide tools with multiple coating layers using the FEM was presented by Yen et al [2]. The main finding from this simulation was that for AISI 1045 steel the predicted steady-state interface temperatures are in good agreement with the
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experimental values given in ref. [5] within 5-11% difference. During a cutting process the mechanical energy due to the plastic deformation developed at the primary shear plane and at the chip–tool interface is converted into heat. Studies have shown that the chip and the environment dissipate a great deal of this heat while the reminiscent is conducted both into the work piece and into the cutting tool. However, this small quantity of heat conducted into the tool (8–10% of the total heat rate) is enough to create high temperatures near the cutting edges, which in same cases can reach the level of 11000C [6]. As a result of the high temperatures developed at the tool surfaces critical tool wear, short tool life and poor work piece surface integrity will generally impair productivity. This fact makes the cutting temperature field identification fundamental on the quality of the finished product. However, direct measurements of temperatures at the tool–chip–work piece interfaces are very difficult due to the cutting movement and the small contact areas involved. Conventional experimental methods such as infrared pyrometer [7], embedded thermocouple [8] and tool–work piece thermocouple usually present problems [6]. The infrared pyrometer can represent a good solution if some limitations, like sensor resolution and chip interference near the cutting zone, are alleviated [9,10]. In the other hand the use of the tool–work piece thermocouple are limited to tools that can conduct electricity. In addition the thermocouple does not measure the temperature at a specific point, but an average temperature at the heat affected zone between the tool and the work piece. Due to these experimental difficulties many analytical and numerical methods solution have been employed to predict machining temperature [11, 12]. Tay [12] has classified the methods of calculation of the temperature generated during steady machining as: the moving heat source method, the image sources method, the finite difference method, the semi-analytical methods and the finite element method. Due to the irregular tool geometry, the majority of numerical techniques use finite element method [13-18]. Analytical Model of Single Point Cutting Tool Heat generation while machining has significant influence on machining. It can increase tool wear and thereby reducing tool life. It gives rise to thermal softening of cutting tool. It is commonly accepted that both the wear and failure mechanisms which develop in cutting tools are predominantly influenced by temperature and it also results in modification to the properties of work piece and tool material such as hardness. In order to predict the wear and failure characteristics of a tool, it is necessary to quantify the temperatures which develop during the cutting operation. In machining operations, mechanical work is converted to heat through the plastic deformation involved in chip formation and through friction between the tool and work piece. Considering a continuous type chip, as the cutting speed increases for a given rate of feed, the chip thickness decreases and less shear energy is required for chip deformation so the chip is heated less from this deformation. About 8085% of the heat generated in shear zone. The chip-tool interface zone, where secondary plastic deformation, due to friction between the heated chip and tool takes place. This causes a further rise in the temperature of the chip. This chip-tool interface contributes 15-20% of heat generated. The work-tool interface zone 3, at flanks, where frictional rubbing occurs. This area contributes 1-3% of heat generated. Several methods have been used for measuring the temperatures generated during metal cutting operations. ToolChip Thermocouple Technique is one of them. The numerical methods were successfully applied in calculating the temperature distribution and thermal deformation in tool, chip and work piece. Especially, the finite element and boundary element methods can deal with very complicated geometry in machining; they have great potential to solve the problems in practice. In metal cutting, severe deformations take place in
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the vicinity of the cutting edge of the tool because of the high temperatures resulting from machining operation. These elevated temperatures have a negative impact on tool life, and quality of surface. The present work deals with the formulation of three-dimensional governing equation for heat conduction used to obtain the temperature distribution on the face of the tool, to be used for obtaining the hardness at the various positions on the tool. The eight nodes brick elements have been used for the FEM modeling. Experimental Planning The direct experimental approach being expensive and time consuming, to study machining processes, especially when a wide range of parameters like tool geometry, materials, cutting conditions, etc are included; an alternative approach, the finite-element method (FEM) is utilized to find the thermal mapping. FEM is one of the most frequently and widely used tool to analyze and find out the results. Several finite-element techniques has been utilized for accurate and efficient modeling of the machining process considering material specific non-linear analysis, mesh rezoning techniques, tool wear modeling, residual stress prediction, etc. Immense heat and high temperature generation during the machining process is taken into the consideration to find out the cause of unsatisfactory tool life, poor surface finish and limitations on cutting speed. To analyze the effect of work surface temperature during machining over surface roughness, a 3-Dimensional Transient Thermal Finite Element Model has been used here with the help of commercially available FEM software ANSYS 13.0. To perform the necessary experiments, an entire cutting process is considered that is to be simulated by FEM in ANSYS from the initial to the transient phase. The work piece material of choice, high speed steel, is modeled as thermo elastic-plastic, while the flow stress is considered to be a function of strain, strain-rate and temperature to represent better the real behavior in cutting. Friction between the tool and chip is of Coulomb type with the value of 0.5. The material as specified in table 01 has been machined in a lathe by a single point cutting tool high speed steel having tool rake angle (degree) 00, tool clearance angle (degree) 200 and measured cutting edge radius (µm) 17-33 µm. Table 1: High Speed Steel Material Properties Density Coefficient of Thermal Expansion Specific Heat
8.17g/cc 1.2e-005 0C-1 434 J kg-1 0C-1
The schematic diagram of the experimental set up is illustrated in the figure 01. As discussed earlier, during the time of turning a huge heat generation takes place in the tool chip interface. Most of the produced heat approximately 85% is carried away by the chip. But rest of heat flows through the tool, hence temperature of the tool is increased. This temperature of tool is being recorded by K- type thermocouple wires. Type K (Chromel{90% nickel and 10% chromium}– Alumel{95% nickel, 2% manganese, 2% aluminium and 1% silicon}) is the most common general purpose thermocouple with a sensitivity of approximately 41 µV/0C and chromel is positive relative to alumel. The Fe-K type (J-type) thermocouple is used for sensing the temperature of the coil. For typical metals used in thermocouples, the output voltage increases almost linearly with the temperature difference (∆T) over a bounded range of temperatures. For precise measurements or measurements outside of the linear temperature range, non-linearity must be corrected. The nonlinear relationship between the temperature difference (∆T) and the output voltage (mV) of a thermocouple can be approximated by a polynomial:
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(1) The data taker DT80 range of data acquisition and logging instrument is used to measure and record the temperature reading as recorded by thermocouples. A personal computer attached to the data logger is further used to monitor the system. The aim of the experiment is to collect temperature from 3 different points of the high speed steel tool at the time of turning a mild steel bar.
Figure 1: Schematic Diagram of Experimental Set-Up for Tool Temperature
Figure 2: Experimental Set Up of Lathe Turning Operation In figure 2 the experimental set up has been shown. A mild steel bar is held in the 3 jaw chuck of the lathe machine. Turning operation is done by the high speed steel tool. 3 thermocouples are attached in the shank face of the cutting tool at different points. The thermocouples are further connected into the slots of data logger DT85. The data logger is further connected to the computer, where the temperature readings are cataloged with a 1 second interval. In figure 2 and figure 3 the views are elaborated. Here three k-type thermocouples are attached on the shank portion of the single point cutting tool. The data logger is basically current sensitive device; hence the meter reading will be dependent on the e.m.f. generated by tool-work-thermocouple. The thermoelectric power of the circuit is usually small and estimated by calibrating the circuit against a reference thermocouple (Alumel-Cromel K type). The tool-work thermocouple technique is the best method for measuring the average chip-tool interface temperature during metal cutting. The benefits of using the tool-work thermocouple are its ease of implementation and its low cost as compared to other thermocouples.
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Figure 3: K Type Thermocouples Attached with Tool at the Time of Turning Experimental Results The turning operation of high speed steel cutting tool with 00 rake angle used to operate a turning operation on Mild steel round bar under following conditions. Table 2: Cutting Conditions Velocity Depth of Cut Feedrate
v t f
720 rpm 2mm 0.3m/rev
The temperatures were recorded from the shank surface by the k type thermocouple at 2.5 mm distance from the rake face. The position of the thermocouples in the shank face of the single point cutting tool is shown below in the figure 6.1. The temperature readings were recorded as below in the table 3.
Figure 4: Thermocouple Position in the Shank of the Single Point Cutting Tool
Steps 1 2 3 4 5
Table 3: Average Temperature Reading of Thermocouples Cutting Temperature [°C] Speed Time [s] Thermocouple Thermocouple Thermocouple (rpm) Reading 1 Reading 2 Reading 3 0 22 22 22 720 1 22 22 22.7 720 2 22.1 22.59 24.43 720 3 22.7 23.1 27.38 720 4 23.9 23.8 33.01 720 5 24.09 24.37 34.77 720
Feed Rate (m/rev) 0.3 0.3 0.3 0.3 0.3 0.3
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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
6 7 8 8.9 9 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9 10
25.7 26.48 26.64 29.7 30.01 31.2 32.28 32.84 33.58 32.01 32.67 33.06 34.01 35.99 36.06
Table 3:Contd., 25.9 26.79 27.86 30.01 30.7 31.46 32.9 33.7 34 34.91 35.98 36.99 38.7 39.1 39.07
35.64 39.1 43.49 46.9 48.3 49.9 51.8 53.57 54.02 54.94 55.49 56.04 57.18 59 59.13
720 720 720 720 720 720 720 720 720 720 720 720 720 720 720
0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
The temperatures of the thermocouple positions in three different shank positions are plotted in the graph, which is shown in the figure 6.2. The temperature plotting indicates that the thermocouple close to the rake surface shows the highest temperature pick up.
Figure 5: Temperature at Various Times at Three Different Points of the Shank Face Results Obtained from FEM Software (ANSYS) Temperature Distribution Figure 6 shows the thermal distribution in ANSYS. It shows the highest temperature at tool rake surface i.e. 3220 C, as conduction and convection both take place during the cutting, the temperature decreases through the shank face.
Figure 6: The Temperature Distribution of the Single Point Cutting Tool
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Heat Flux In figure 7 the heat flux vectors are shown. The heat flux vectors are flowing from the chip tool interface to the rest of the tool. The ansys temperature distribution shows that the bottom part of the shank is at 220C, so at the bottom part of shank the heat flux vectors are in reverse direction.
Figure 7: The Heat Flux Vectors Flowing from the Tool Chip Interface In figure 8 the total heat flux is shown by ANSYS. Here it is also clear that the maximum heat flux is present at the chip tool interface and the rest of the heat flux flows through the tool.
Figure 8: Total Directional Heat Flux Amount in the Cutting Tool Normal Stress Due to the forces present in turning operation a stress is developed in the single point cutting tool. In figure 9 ANSYS shows the normal stress developed along x- axis.
Figure 9: The Normal Stress Evolved During Cutting along X Axis
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Total Deformation Due to high amount of heat is generated in the chip tool interface, a deformation due to heat is certain. Ansys predicts the deformation in the single point cutting tool. Figure 10 shows the deformation in the cutting tool.
Figure 10: Total Deformation of the Cutting Tool as Analyzed in ANSYS
DISCUSSIONS The relationship between machining parameters and temperature generated at tool work piece interface has been calculated using the empirical relations as given analytical model with the help of a commercial software ANSYS. The reason behind the generation of high temperature at the contact zone of tool edge radius is mainly because of the extrusion of work material and friction between tool edge radius and work piece. After that, the fresh cut chip will flow into second deformation zone, where it will be continued to be extruded and will come in more contact with the tool, resulting in a greater friction. Therefore, the temperature in chip is generally higher than other contact zones, and its average temperature in normal machining conditions is high enough like 625˚C approximately. As the experimentation has been carried out in dry condition i.e. without the application of cutting fluid, the heat dissipation is considerably less. To understand the nature of temperature rise in a particular node, the temperatures of global maxima as well as of global minima for that particular node are to be plotted against iterations.
Figure 11: Time vs. Temperature - Global Maximum
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Figure 12: Time vs. Temperature - Global Minimum It could be noted that, a global maximum is the highest value of the function within the entire domain; there can only be one global maximum whereas a global minimum is the lowest value of the function within the entire domain and there can only be one global minimum. In contrast to the global minima, a local minimum value of a function is the lowest value of a function within a very small interval; there can be more than one local minimum within the domain of the domain whereas a local maximum value of a function is the highest value of a function within a very small interval and there can be more than one local maximum within a domain. In some cases, the global maximum of a function is the same as one of the local maximums of the function, and the global minimum of a function is the same as one of the local minimums of the function. Global maximums and global minimums can be found at the endpoints of a closed domain; local maximums and local minimums cannot be found at the endpoints of a closed domain.
CONCLUSIONS During a cutting process the mechanical energy due to the plastic deformation developed at the primary shear plane and at the chip–tool interface is converted into heat. Studies have shown that the chip and the environment dissipate a great deal of this heat while the reminiscent is conducted both into the work piece and into the cutting tool. However, this small quantity of heat conducted into the tool (8–10% of the total heat rate) is enough to create high temperatures near the cutting edges, which in some cases can reach the level of 11000C. As a result of the high temperatures developed at the tool surfaces critical tool wear, short tool life and poor work piece surface integrity will generally impair productivity. This fact makes the cutting temperature field identification fundamental on the quality of the finished product. However, direct measurements of temperatures at the tool–chip–work piece interfaces are very difficult due to the cutting movement and the small contact areas involved. Conventional experimental methods such as infrared pyrometer, embedded thermocouple and tool–work piece thermocouple usually present problems. The infrared pyrometer can represent a good solution if some limitations, like sensor resolution and chip interference near the cutting zone, are alleviated. In the other hand the use of the tool–work piece thermocouple are limited to tools that can conduct electricity. In addition the thermocouple does not measure the temperature at a specific point, but an average temperature at the heat affected zone between the tool and the work piece.
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Due to these experimental difficulties many analytical and numerical methods solution have been employed to predict machining temperature. Tay has classified the methods of calculation of the temperature generated during steady machining as: the moving heat source method, the image sources method, the finite difference method, the semi-analytical methods and the finite element method. Due to the irregular tool geometry, the majority of numerical techniques use finite element method. One thing that the models (unsteady or steady state) have in common is that the generated heat source must be known or defined a priori considering the basic machining parameters such as rake angle, cutting speed and feed rate. Some method also assume that all the heat generated during machining appeared in two regions (primary shear plane and interface) and they can be obtained from the product of the frictional forces along the rake face and along the shear plane by the shearing and chip velocity, respectively. Unfortunately in real machining processes the heat flux generated at the chip–tool interface are unknown and strongly dependent on the cutting condition and on the types of workpiece and cutting tool used. The temperature readings recorded at the shank by the thermocouples (fig 04) is mentioned in the table 03. The readings were recorded between 360 c and 590 c. in figure 06 the ANSYS temperature distribution is shown. The shank position where thermocouples were attached, in ANSYS thermal distribution, it shows the temperature range as 220c to 550c. By comparing both the experimental result and ANSYS thermal distribution, it can be concluded that both the results are showing good agreement with one another.
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