Analysis of Tool Temperature Distribution in Turning Processes

Transcription

1 Analysis of Tool Temperature Distribution in Turning Processes Indra Jufri Nurraksana 1, Gaguk Jatisukamto 2, Agus Triono 3 1,2,3 Department of Mechanical Engineering, Faculty of Engineering, University of Jember, Indonesia Abstract Heat is generated by friction between tool and work piece in machining processes. The tool temperature is influenced by frictional force and material work piece. The previous research used cutting speed (Vc), depth of cut (DoC) and feeding (f) as a variable process. The purpose of this research is to analyse effect of nose angel toward temperature distribution. The research method is used St 37 steel material as a work piece with of 100 mm in length and 25 mm in diameter. The nose angle tools consist of: 30 o, 40 o, 50 o,60 o. High speed steel tool characteristic are: thermal conductivity = 50 W/mK; density = 86 kg/m 2 ; specific heat = 4851 J/kg o C. The infrared thermometer is used to measure tools temperature. Finite element method is used to simulate tools temperature distributions. The results shows that the angle of the tool 30 0 has the highest temperature of C. The cutting temperature is depent on nose angel where the smaller of nose angel temperature becomes larger cutting temperature. Keywords HSS (High Speed Steel), Temperature distribution, Turning, Finite Element, Modelling. I. INTRODUCTION Energy in the machining process generates heat and distributed in tool, work piece and chip [1]. Heat received that lasted continuously will affect tool life [2]. Corner pieces produce mechanical and thermal loads are significant and the chemical reactions that affect growth temperature of the tool [3]. The heat generated of cutting process is the effect of plastic deformation of the work piece and the friction between the cutting tool and work piece [4]. The heat distribution affected the strength, hardness, wear resistance and service life. The heat on the material surface influenced the tool wear [5]. Cutting temperature is influenced by three main zones, namely primary shear deformation zone, secondary shear deformation zone and tertiary shear deformation zone. Shear deformation is the largest heat zone in any machining processes than the others. Heat continued to form shear deformation zone. Tertiary shear deformation zone produces less than 5% of the total heat generated during the machining process takes place as shown in Figure 1 [6]. The peak temperature on the surface of the intersection is located along the cutting edge and surface machining. The totally heat is determined by the temperature of the heat source and increasing shear deformation resulting from friction tool and work piece [7]. Basically, the surface temperatures are approaching the average temperature on the tool or work piece [8]. Chip Tool Figure Work 1. piece Tool Temperature 2017, All Rights Reserved 22

2 The heat value of the tool received work piece and fury depending on dimensions, thermal conductivity and cutting conditions [9]. Temperature and thermal gradients is a critical factor in determining the borders of each cutting process [10]. Good temperature control in the machining process can improve the properties of the material, especially the surface hardening [11]. Finite element modeling method most widely used in modeling the temperature because it can provide more detailed information about the stress, strain, strain rate and cutting temperature[12]. Grzesik said the model is a clone system that is used to investigate, calculate and explain the actual system. The purpose of modeling to reduced the loss of a system [13]. This study aims to determine the temperature distribution using a finite element analysis on transient thermal conditions. Infrared thermometer was used to determine the tool temperature. II. MATERIAL AND METHOD In this research St 37 steel was as a used to work piece material. The chemical properties and the material composition St 37 are shown in Table 1 and Table 2 respectively. The dimension of the work piece is shown in Figure 2. Tabel 1. Material properties St 37 (DIN 1629 St37) Elements % C 0,170 Si 0,170 Mn 0,350 P 0,025 S 0,020 Cr 0,250 Ni 0,250 Cu 0,250 Table 2. Mechanical Properties Material St 37 Tensile Strength (MPa) 350 Yield Strength (MPa) 235 Elongation (%) 25 ϕ25 mm 100 mm Figure 2. Work piece Dimension The cutting conditions employed are: cutting speed (Vc) = 725 m/min, depth of cut (DoC) = 2 mm and feed rate (f) = 0.36 mm/put. Three levels of nose angle at 30 0, 40 0, 50 0 and 60 0 were 2017, All Rights Reserved 23

3 Infrared thermometer was used to measure cutting temperature. The infrared thermometer specification is shown in Table 3. Table 3. Specifications of infrared thermometer Measurement range C to C Accuracy ± 1.5% or C Resolution C Emissivity Figure 3. Parts tool angle [14] Figure 3 shows tool angel sections in turning. High cutting temperatures effect the level of the tool wear. A factor affecting is the geometry tool wear, tool material and cutting conditions. Geometry tool is a form of different angles that will affect the tool dimensions. Work piece material and tool also affect the magnitude of temperature-related pieces of thermal conductivity. Objects that have low thermal conductivity it will cause a high cutting temperatures so it can accelerate the tool wear. Selection of standard size using the tool angel shown in Table 4. Mas ud [14] was used Table 4 as a reference in selecting materials HSS included in the steels category, and then we chose the yellow line in Table 4. Cutting tool positions shows at Figure 4. Table 4. Recommended tool angle [13] Material Back Rake Side Rake End Relief Side Relief Side and End Cutting Al and Mg Alloys Copper Alloys Stells Stainless Stell High Temp Alloys Refractory Alloys Titanium Alloys Cast Iron , All Rights Reserved 24

4 Figure 4. Cutting Tool positions Dry cutting was used in this study to determine the thermal effects in the machining process. Conduction numeric modeling approach with the following formula: 0,44 0,22 C. ks. v.. A θ e= ( C o 0,44 0, 56 ) [14] λw. Ccw where: θe = Tool Temperature k s λ w = ks11. b i-j.h -(i+j) = The thermal conductivity of the work piece C cw= Specific volumetric heat the work piece A = Cross-sectional area III. RESULT AND DISCUSSION Figure 5 shows the average value of the biggest heat on tool nose angle 30 0 amounted to C, while the averages value of the smallest heat at nose angle 60 0 of C. The heat value at a nose angle of 40 0 has a meaning value C and at a nose angle 50 0 has a value of C. Average Temperature Figure 5. Results of temperature measurement The tool nose angle of 30 0 experiments 1 has a smaller value, the repeating values are occurred the greater heat. This phenomenon occurs because the treatment time trial dimensional nose angle tool still intact whereas in experiments 2 and 3 is not done anymore grinding tool cut angle geometry so began suffering from wear and result in temperature, cut into increased value. The increase temperature that occurs due to friction during the cutting process takes place even 2017, All Rights Reserved 25

5 Figure 6. Temperature distribution nose angel 30 0 Figure 6 is a simulation result of temperature distribution on the tool at nose angle of 30 0.The temperature distribution showed its highest value of 44.3 o C and concentrated at the tip of the tool with smaller dimensions compared with other variable tool angle. As a result of the centralized heat the tool tips possibility to experience greater wear. The tool wear can affect the quality of the work piece surface and the impact on surface roughness will be less good. The sharp tool nose angle caused the heat centered of tool in the end and the resulting of continuous chip. Figure 5 shows a colour change in the chip due to high cutting temperatures. Figure 7. Temperature distribution nose angel 40 0 Figure 7 shows the simulation results with a nose angle Results shown are similar to a tool cut angle 30 0.Heated distributed wider than the nose angle 30 0 As a result, the temperature becomes smaller pieces of cut angle , All Rights Reserved 26

6 Figure 8. Temperature distribution nose angel 50 0 Figure 8 below which show the simulation results temperature distribution on the tool. The nose angle 50 0 has a higher value than an angle of 40 0 and an angle of This phenomenon can occur as a result of treatment of the work piece is used detracted from the cutting process has happened before so that an increase in temperature. Temperature can affect all the material near the cutting area, and can reflect on the overall temperature. Surface roughness is very important because it deals directly with the age of the materials used, if the material gets a load cycles with a certain number of cycles it will be fractured as a result of surface roughness that is less good. The dimensional accuracy is also difficult to sustain. The sculpture wearing is due to the effect of high temperatures. At the nose angle 60 0 has a value of temperature, the lowest when compared with the nose angle 30 0, 40 0 and The heat that arises during a cutting process are distributed to the tool so it is not centre on the tool tip just because the shape of the corner pieces are not too sharp. Shape chip short cutting results - short shows that growth is not sustainable heat and some of the heat go wasted along chip. Figure 9 below shows the results of simulation of the cutting process with a nose angle Tool wear with an angle of 60 0 becomes smaller when compared with other cutting angle variation with the largest temperature value of C. The quality of the surface is also better because the temperature is not too great and the cutting surface roughness becomes better. Figure 9. Temperature distribution nose angel , All Rights Reserved 27

7 IV. CONCLUSIONS The cutting process temperature is generated by plastic deformation and friction between tool and work piece. Temperature is influence by frictional force, dimension and material. The result shows that cutting temperature is depent on nose angel. The largest temperature is generated from 30 o nose angel of 44,3 0 C. The result of modeling temperature distributions shows that 30 o has centred heat in the end of tools. Cross-section areas on the simulation results have an important role in analysing the temperature distribution. This study can not indicate the extent of the actual extent of cross-sectional approach. The next research use simulation to show the cross-sectional area which is close to the actual area so that it can perform more analysis of the tool temperature distribution. REFERENCES I. Kara, F., Aslantaş, K., & Çiçek, A. (2016). Prediction of cutting temperature in orthogonal machining of AISI 316L using artificial neural network. Applied Soft Computing, 38, II. Gosai, M. & Bhavsar, SN, Experimental Study on Temperature Measurement in Turning Operation of Hardened Steel (EN36). Procedia Technology, 23, pp Dosbaeva, GK et al., 2015 Cutting temperature effect on PCBN and CVD coated carbide tools in hard turning of D2 tool steel. International Journal of Refractory Metals and Hard Materials, 50, pp.1-8. III. Baohai, W., In, C., Xiaodong, H., Dinghua, Z., & Kai, T. (2016). Cutting tool temperature prediction method using analytical models for end milling. Chinese Journal of Aeronautics, 29 (6), IV. Shihab, SK et al., RSM-based Study of Cutting Temperature During Hard Turning with Multilayer Coated Carbide Insert. Procedia Materials Science, 6, pp V. Thakare, A. & Nordgren, A., Experimental Study and Modeling of Steady State Temperature Distributions in Coated Cemented Carbide Tools in Turning. Procedia CIRP, 31, pp VI. Bapat, PS., Dhikale, P.D.,S.M, Shinde., A.P.Kulkarni., S.S, Chinchanikar A Numerical Model to Obtain Temperature Distribution During Hard Turning of AISI Steel. Materials Today: Proceedings, 2 (4-5), pp VII. Garcia-Gonzalez, JC, Moscoso-Kingsley, W. & Madhavan, V., Rake Face Temperature When Machining with Coated Cutting Tools. Procedia Manufacturing, 5, pp VIII. Benabid, F., Benmoussa, H. & Arrouf, M., A Thermal Modeling to Predict and Control the Cutting Temperature. The Simulation of Face-milling Process. Procedia Engineering, 74, pp IX. Islam, C., Lazoglu, I., & Altintas, Y. (2015). A Three-Dimensional Transient Thermal Model for Machining. Journal of Manufacturing Science and Engineering, 138 (2), X. Davies, MA, Ueda, T., M'Saoubi, R., Mullany, B., & Cooke, AL (2007), On The Measurement of Temperature in Material Removal Processes. CIRP Annals - Manufacturing Technology, 56 (2), XI. Abukhshim NA, Mativenga PT, Sheikh MA. Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining. International Journal of Machine Tools and Manufacture 2005; 46/7: XII. Daoud, M., Chatelain, JF & Bouzid, A., Effect of rake angle-based Johnson-Cook material constants on the prediction of residual stresses and temperatures in Al2024-T3 induced machining. International Journal of Mechanical Sciences, 122, pp XIII. Grzesik, W., Heat in Metal Cutting. Advanced Machining Processes of Metallic Materials, pp XIV. Mas ud, M., Bambang, P.,Agus,SP Modelling HSS tool Temperature in turning with K type thermocouple and St , All Rights Reserved 28