Minimization of Temperature in Cutting Zone: A Case Study of Hard Milling of SKD 61 Steel

The heat generated during metal cutting is a major factor affecting the cutting forces, tool life, and chip formation mode. In this research, the Taguchi method was applied to find the optimal values of cutting parameters in hard milling of SKD 61 steel to minimize cutting temperature under cutting oil and Al2O3 nanofluid MQL condition. The effects of cutting parameters including cutting speed, feed rate and depth of cut were investigated by using an L9 array of Taguchi method. The signal-to-noise (S/N) ratios and analysis of variance (ANOVA) were applied to analyze the influence of input factors on the cutting temperature. The study result shows that cutting speed is the most influential factor, which gives statistic significant effect on cutting temperature. The speed contributes 52.55 % of total effect under cooling condition of MQL with cutting oil and 53.77 % of total effect under cooling condition of MQL with Al2O3 nanofluid. Additionally, the effectiveness in cutting heat reduction of cutting oil MQL was compared with Al2O3 nanofluid MQL based on experimental measurement of cutting temperature. According to the analysis, the Al2O3 nanofluid – MQL is a better option for the cooling conditions during hard milling of SKD 61 steel.


Introduction
Cutting fluids are employed in the machining process to improve the tribological processes occurring at the interface of the tool and work-piece. Cutting fluids play a role as both lubricants and coolants. The cutting fluid improves the tool life, machined surface of the work-piece and the process as a whole. In addition, it also removes heat and debris generated during cutting. In traditional machining, cutting fluid has been supplied ưith an amount flooding cutting zone. It is named wet machining. The wet machining has several adverse effects such as environmental pollution, damaging the health of operators, increasing production costs related to coolant costs and product cleaning costs [1,2]. Reducing or even eliminating cutting fluid is a new trend in metal cutting that attracts great interest in manufacturing and research. Dry machining is thought to be capable of removing lubricant during machining with the advancement in cutting tool material technology. Dry machining is a good solution with many advantages especially in environmental and health issues [1,[3][4][5]. However, high heat generated during dry cutting is a problem that has a negative impact on tool wear and tool life [6,7]. Minimum quantity lubrication (MQL) is a good solution for both dry cutting and wet cutting. With a minute amount of cutting fluid pulverized in a flow of air directed at the cutting zone during the cutting process, MQL provides with many superior advantages compared to traditional cutting [1,8,9]. The MQL in machining not only can obtain the same surface quality as the conventional cutting process with the grinding process under proper parameters but also increases economic efficiency by reducing the lubricant-related costs, increases productivity and eliminates negative environmental impacts [10,11].
It is well known that heat produced during metal cutting is an important factor affecting the performance of the cutting tool. The thermal phenomena in the cutting process play a key role in controlling tool wear, surface integrity, and machining precision. Many economic and technical issues are directly or indirectly affected by heat during cutting. Shaw et al. believes that excessive heat is a cause of cutting tool wear and damage to the machined surface [12]. Moreover, the heat on the tool face is the main factor affecting the size and stability of the build-up-edge. Therefore, controlling and minimizing cutting heat is the concern of many researchers. In an experimental study of Davoodi, B., and Tazehkandi, A. H. [13], the authors surveyed and optimized the cutting parameters in dry and wet machining conditions aluminum alloy 5083 to eliminate the cutting fluid. A conclusion was given that cutting conditions with the highest cutting speed and lowest undeformed chip thickness result in the least tool tip temperatures in both dry and wet machining. In another study, Raviraj Shetty et al. carried out the experimental investigations of the turning of discontinuously reinforced aluminum composites under three conditions of cooling such as dry, oil-water emulsion, and steam lubricated condition [14]. They concluded that the effect of the lubrication condition is the greatest on the cutting temperature followed by cutting speed. In addition, the cutting temperature increases with cutting speed and feed rate. In an overview study of cutting temperature [15], Da Silva, M. B., and Wallbank, J. reported that the effect of the cutting parameters including the cutting speed, the feed rate, and the depth of cut will lead to an increase in temperature.
In order to enhance the thermal conductivity of cutting fluid, a new technology in MQL machining called nanofluid was introduced by Choi in the use of nanoscale solid particles (less than 100 nm) to add to the cutting fluid in 1995 [16]. The nanoparticle-based cutting fluid has overcome the weakness of conventional cutting fluids which have poor conductivity [17]. The nanoparticles added to the base fluid enhance the thermal conductivity by adding very minute volumetric concentration [18,19] and, therefore, increase the efficiency of heat exchange [20][21][22].
The effect of cutting parameters on cutting temperature as well as examining the machining efficiency of nanofluid application has been studied in many studies. However, investigation of the effect of the cutting parameters on the cutting temperature under the condition of Al 2 O 3 nanofluid has not been mentioned. Hence, this is the motivation of the authors to investigate the influence of cutting parameters on cutting temperature under Al 2 O 3 nanofluid with MQL condition. Al 2 O 3 was chosen to be added into cutting oil because of its high performance in reducing cutting force, improving surface roughness, tool wear and chip morphology when compared to conventional cutting fluids. In this study, the Taguchi method was used to find the optimal values of cutting parameters in hard milling of SKD 61 steel to minimize cutting temperature under two cooling conditions such as MQL with cutting oil and MQL with Al 2 O 3 nanofluid. The effectiveness in cutting heat reduction of Al 2 O 3 nanofluid -MQL was compared to cutting oil -MQL based on experimental measurement of cutting temperature.

Experimental procedure
The experiments were carried out on a Victor V-Center-4 vertical machining center. The cutting tool used in the machining test is the φ10 TiAlN coated-end mill with four flutes rake angle of 12 o , and helix angle of 35 o . The workpiece is an SKD 61 steel block with dimensions of 150mm × 100mm × 40mm. The workpiece material compositions are shown in Table 1. The hardness of the workpiece is 50HRC. The MQL parameters chosen are 90ml/h for the flow-rate, 3kg/cm 2 for the air-pressure and CT232 cutting oil for the lubricant. The angle of the MQL nozzle selected is 60 o . The Al 2 O 3 nanoparticle size is 20nm. The concentration of nanoparticle in the fluid is 2 wt%. In order to achieve a homogeneous dispersion and stable suspension, the mixture of cutting oil and nano-particles was stirred within 12 hours by using a magnetic stirring device. Measurement data of cutting temperatures is collected by using an infrared camera model IRM_P384A3-20 of Ching Hsing Computer -Tech Ltd. The experiments were carried out at room temperature of about 25 o C. The experiments are described in detail in Table 2. The input factors and levels used during the hard milling of SKD 61 steel are given in Table  3.

Results and Discussions
In experimental research, it is necessary to design the experiment correctly to obtain reliable results. In this study, the Taguchi method was used to design the experiment and analyze the influence of cutting parameters on the temperature in the cutting zone. L 9 orthogonal array was selected to organize the testing procedure. In the Taguchi approach, the signal to noise (S/N) ratio is used to analyze the results. S/N ratio has three types including the bigger is the better, the smaller is the better, and the nominal is the better. Because of minimizing the cutting temperature, the smaller is the better type is selected and calculated by the following formula: (1) Where: y i is the observed data, n is the number of experiments that are repeated.
The hard milling processes of SKD 61 steel were conducted under two cooling conditions including MQL with cutting oil and MQL with Al 2 O 3 nanofluid. The results of the cutting temperature and S/N ratio given by Minitab 17 software are shown in Table 4. In Table 4, the input factors include the cutting velocity (v), the feed rate (f), and depth of cut (d

Minimizing of Cutting Temperature under MQL with Cutting Oil Condition
The S/N response given by the Taguchi method is applied to determine the most effective one of input factors on the response factor. The highest values of S/N show the optimum level of each input factor. The analysis of the S/N response is depicted in Figure 1. As shown in Figure 1, the S/N response analysis shows that, under MQL with cutting oil, the optimal condition of cutting parameters to minimize the temperature is the cutting speed of 40 m/min, the feed rate of 0.01 mm/tooth, and the depth of cut of 0.2 mm. This optimal machining mode corresponds to experiment No. 1 for T 1 shown in Table 4. The result of the cutting temperature in the experiment No.1 is 38.3 o C, being the lowest value of T 1 . It proves the reliability of the analytical results.
The ANOVA results for the effect levels of the input factors on cutting temperature are shown in Table 5. As shown in Table 5, the cutting velocity is the most influential factor on the cutting temperature followed by the depth of cut under the cooling condition of MQL with cutting oil. The percentage contribution to the total effect of these factors is 52.55% and 46.2 %, respectively. The effect of the speed and the depth of cut on the temperature have statistical significance with a P-value less than 0.05. On the other hand, the effect of the feed rate on the temperature is negligible with a 1.1% contribution. With a P-value greater than 0.05, the effect of feed rate has no significant difference.   Figure 2 depicts the analysis of S/N response for the cutting temperature under MQL with Al 2 O 3 nanofluid condition. Similar to the condition of MQL with cutting oil, when applying MQL with Al 2 O 3 nanofluid condition, the optimal condition of cutting parameters to minimize the temperature is the cutting speed of 40 m/min, the feed rate of 0.01 mm/tooth, and the depth of cut of 0.2 mm. This optimal machining mode corresponds to experiment No. 1 for T 2 shown in Table 4. The result of the cutting temperature in the experiment No.1 is 35.1 o C, being the lowest value of T 2 . It proves the reliability of the analytical results. Table 6 shows the ANOVA results for the effect levels of the input factors on cutting temperature under MQL with Al 2 O 3 nanofluid condition. According to the ANOVA results, the most important factor influencing the temperature is recorded to be the cutting speed with 53.77% contribution. Following the cutting speed is the depth of cut with a 35.11 % contribution. The effect of these factors has statistical significance with a P-value of less than 0.05. The effect of the feed rate on the temperature is negligible and has no significant difference with a 4.17% contribution and P-value greater 0.05.

Effect of the Cutting Parameters on the Temperature
The influence of the cutting parameters such as the speed, the feed rate, and the depth of cut on the temperature in the cutting zone can be noted by the analysis of Figure 3. Clearly, under both cooling conditions, the temperature raised by the increase of all cutting parameters. This is in agreement with the results of previous studies such as those of M. Hirao and of M. Mia and N. R. Dhar [23,24]. As shown in Figure 3, the temperature increases sharply by an increase in the cutting speed. It is explained that the heat generated in the cutting zone does not have enough time to spread to the surrounding environment with the increase of cutting speed [12,24]. The increase in the depth of cut also causes a marked increase in the temperature. However, the change of cutting temperature is slight with the increase in feed rate. Figure 3 confirms that the cutting spees, followed by the depth of cut, has the greatest effect on the cutting temperature. The effect of feed rate is negligible.

Comparison of Effectiveness in Cutting Temperature Reduction of Two Cooling Conditions
The effectiveness in cutting temperature reduction of Al 2 O 3 nanofluid -MQL was compared to cutting oil -MQL based on experimental measurement of cutting temperature as shown in Figure 4. It can be easily observed that the cutting temperature when using the cooling condition of Al 2 O 3 nanofluid -MQL is lower than that of cutting oil -MQL. It can be explained that the nanoparticles added to the base fluid enhance the thermal conductivity by adding very minute volumetric concentration and, therefore, increase the efficiency of heat exchange. Therefore, the Al 2 O 3 nanofluid -MQL is a better option for the cooling conditions during hard milling of SKD 61 steel.

Conclusions
In this study, the Taguchi method was used to find the optimal values of cutting parameters in hard milling of SKD 61 steel to minimize cutting temperature under two cooling conditions such as MQL with cutting oil and MQL with Al 2 O 3 nanofluid. The results obtained in this context are listed as follows:  Under both cutting conditions, lower cutting-speed, lower feed-rate, lower depth-of-cut, and lower hardness, it resulted in minimum cutting temperature. The optimal cutting parameters for minimizing the temperature in cutting zone are the cutting speed of 40 m/min, the feed rate of 0.01 mm/tooth, and the depth of cut of 0.2 mm.  In both cooling conditions, the cutting speed is the most influential factor on the cutting temperature followed by the depth of cut. The cutting temperature when using the cooling condition of Al 2 O 3 nanofluid -MQL is lower than that of cutting oil -MQL, the Al 2 O 3 nanofluid -MQL is a better option for the cooling conditions during hard milling of SKD 61 steel.