Research on the Effect of Micro-Pit Parameters on Tool Wear in Turning GH4169

Abstract

Tools with micro-textures have found wide application in cutting difficult machining materials. The cutting performance of tools is closely related to the arrangement, morphology, and size parameters of micro-textures. In this research, micro-pit tools were used in turning GH4169 in spray cooling. The effect of micro-pit parameters on tool wear was investigated through simulation and cutting experiments. In simulation, a model of cutting GH4169 in spray cooling was built to analyze the wear of micro-pit tools with different parameters, and the optimal combination of micro-pit parameters with excellent anti-wear performance was obtained: when the distance between the micro-pit and tool nose is 60 μm, the diameter of micro-pits is 70 μm, and the pit spacing is 100 μm. In the cutting experiment, micro-pit textures with different parameters were fabricated by femtosecond laser, and cutting experiments were conducted in spray cooling to analyze the wear on the rake face of micro-pit tools. Furthermore, Ansys Fluent was used to simulate the dynamic pressure of oil film on the surface of micro-pits, and the anti-wear mechanism of micro-textured tools was verified. This research provides technical reference for the design and development of micro-textured tools.

1. Introduction

Nickel-based superalloy GH4169 possesses comprehensive properties, including high toughness, high strength, good wear resistance, corrosion resistance, and high-temperature oxidation resistance, making it widely used in the aerospace, nuclear, and petroleum industries [1]. However, due to its high-temperature strength, low thermal conductivity, and high plasticity, the high cutting temperatures and cutting forces that occur in machining may easily lead to work hardening. As a result, severe tool wear and reduced tool life are liable to happen to its processing [2]. In recent years, researchers have introduced various methods to improve tool wear resistance, with tool modification and cooling condition optimization showing significant effects [3]. Therefore, the use of appropriate cutting tools and cooling methods is critical for the reduction of cutting temperature, the decrease in tool wear, and prolonged tool life in machining GH4169.

As minimal quantity lubrication (MQL) technology, spray cooling demonstrates remarkable advantages among all the cooling methods. It delivers pressurized cutting fluid in an atomized mist form to the cutting zone, effectively and uniformly enhancing heat transfer to achieve superior cooling and lubrication. This approach not only reduces tool wear but also minimizes cutting fluid consumption for improved environmental sustainability. Ganesh S. Kadam [4] carried out an experiment of turning Inconel 718 with cemented carbide cutting tools to explore the effects of steam mist parameters on the cutting process. The results show that as the steam mist parameters such as the nozzle diameter, spacing, and pressure increased, the cooling and lubricating effects of the steam mist were significantly enhanced, and surface roughness was effectively reduced. Ramanuj Kumar [5] investigated the turning of AISI D2 steel with carbide tools in impingement spray cooling. Results show that the evaporation of atomized cutting fluid provides remarkable cooling effects and a lower tool temperature, and reduced wear can be achieved. Qinglong An [6] compared a cold mist jet with a cold air jet, flood cooling, and MQL in machining titanium alloy. It was proved that a cold mist jet offers a better cooling capacity that substantially reduces the cutting temperature in high-speed titanium machining while improving tool life and surface quality. Bangfu Wu [7] studied tool wear behavior when milling ultra-high-strength steel in different cooling conditions. The experiments show that ultrasonic atomization of cutting fluid achieved the best anti-wear performance of tools and resultant milling force, along with an optimal surface quality.

In recent years, the design of micro-textured cutting tools based on bionics has attracted extensive attention from researchers worldwide. By precision machining techniques, including electrical discharge machining (EDM), photolithography, and laser processing, optimized geometric patterns and structural arrangements can be fabricated on the rake face of tools to obtain improved cutting properties. Many scholars have investigated the cutting performance of micro-textured tools through cutting experiments and finite element analysis. Saraf G [8] created micro-columnar textures on tungsten carbide cutting tools and carried out turning experiments on Ti6Al4V. The results reveal that the tool–chip contact area is significantly reduced, the temperature rise of the cutting tool decreases, and the width of the flank wear is reduced. Zhenglong Fang [9] compared tool wear, material adhesion, and chip formation in turning nickel-based superalloys cut by micro-textured tools and non-textured tools, and micro-textured tools exhibited superior cutting performance. Mustapha Mukhtar Usman [10] performed comparative turning experiments on 304 stainless steel cut by micro-textured tools, investigating the cutting performance of micro-textured tools in both ultrasonic elliptical vibration cutting and conventional cutting conditions. The experimental results showed that micro-textured tools outperform non-textured tools in overall machining performance. Sharma [11] reviewed the tribological advantages of texture surfaces. The research shows that tools with micro-pits or linear grooves can effectively reduce the cutting force and friction coefficient and lower the cutting temperature while extending tool life. Darshan [12] fabricated pit-pattern textured tools and confirmed that compared to non-textured tools, the textured tools reduced cutting force and rake face wear while improving the workpiece surface quality.

Studies demonstrate that the performance of micro-textured tools is primarily governed by three key factors: texture morphology, arrangement patterns, and dimensional parameters.

In terms of texture morphology, Kawasegi N [13] fabricated transverse and longitudinal micro-grooves on WC-Co carbide turning tools to investigate texture orientation effects when machining aluminum alloy Al5052. Results show that textures perpendicular to the chip flow direction reduce cutting forces, whereas parallel textures generate forces comparable to or slightly higher than non-textured tools. Hui Yang [14] developed two bionics-based textures (U-shaped grooves and diamond pits) on carbide tools for machining 45 steel, with comparative wear analysis revealing distinct tribological properties and cutting performance across texture morphologies. Guolong Wu [15] engineered three textures (pit, groove, and mesh) for tribological property research, identifying laser texturing as an effective method to reduce friction and wear.

Regarding the arrangement patterns of micro-textures, Xin Yu [16] proposed a design of micro-textures with different density distributions to adapt to different friction states in the tool–chip interface, and maintain excellent friction reduction and wear resistance as well. After turning experiments on superalloy GH4202, the results demonstrated that the parameters of textures in different areas of the rake face are related to the machining performance and mechanisms. Compared with non-textured tools and uniformly distributed textured tools, the properly designed variable-density textures enabled MTTs to exhibit superior wear resistance and chip-breaking capability in machining GH4202 superalloy. Gajrani K [17] designed various micro-texture arrangements on WC-Co turning tools, including parallel grooves and perpendicular grooves. Cutting experiments on hardened AISI H-13 steel revealed that when the chip flow direction remained unchanged, tools with the greatest number of micro-textures in contact with chips showed significantly reduced cutting and feed forces. Hao X [18] fabricated uniform textures, variable-density textures, combined textures, and variable-density combined textures on triangular carbide turning tools. When machining Ti6Al4V titanium alloy, results indicate that the region close to the cutting-edge experiences more severe friction and wear. Sun J [19] studied the effect of mixed texture on the performance of cutting pure iron with carbide cutting tools. In the mixed texture, the grooves can be used as supplement channels of lubricating oil. The grooves are connected to each other, and the lubricant flows along the grooves to the end when squeezed. More lubricant stays near the cutting edge, and less lubricant is found between the adjacent grooves. In contrast, pit texture provides a relatively enclosed space; lubricant flows from the edge of the pit to the surrounding areas. The oil supply along the cutting edge comes only from limited numbers of pits, which is difficult to meet the demand for. The design of mixed textures combines the advantages of both groove and pit textures to achieve a uniform coating of the lubricating oil. The design improves the cutting performance of the tool.

Research on dimensional parameters of micro-texture also received attention. Hossam A. Kishawy [20] proposed a novel mechanism to describe their influence on cutting performance. The study revealed that among various parameters, the distribution and width of micro-grooves exhibited the most significant effects. When micro-grooves were located farthest from the cutting edge (200 μm) with the narrowest width (30 μm), the cutting force reached its minimum; conversely, the maximum cutting force occurred when micro-grooves were closest to the cutting edge (50 μm) with the widest dimension (60 μm). Comparatively, optimally parameterized micro-textured tools achieved a 12% reduction in cutting force. Qinghua Li [21] investigated micro-texture effects on polycrystalline cubic boron nitride tools when machining hardened GCr15 steel in terms of tool wear and surface roughness. The team designed two different micro-pit textures with an identical pit-depth of 5 μm. Results indicate that micro-pits with d = 80 μm outperformed those with d = 120 μm in improving surface quality and reducing tool wear. Salman K [22] employed the Response Surface Methodology (RSM) to optimize the parameters of micro-textured cemented carbide inserts for thread turning of aluminum 7075 aerospace alloy, using cutting force as the key evaluation index. Through Analysis of Variance (ANOVA) and Box–Behnken design, the optimal micro-texture parameters were determined: a width of 93.4 μm, a depth of 15 μm, and spacing of 50 μm. Significantly, the micro-hole textured inserts demonstrated superior performance compared to both micro-groove texture and conventional inserts during the machining process.

Extensive research demonstrates that the use of micro-textured cutting tools in machining effectively lowers cutting temperatures and reduces cutting forces while improving surface quality and extending tool life. However, few studies are found currently on micro-textured tools when machining superalloys in spray cooling. Investigating the influence of micro-texture parameters on tool wear resistance holds significant importance and warrants further exploration. In this study, turning experiments were conducted on nickel-based superalloy GH4169 using micro-pit textured tools with varying parameters in spray cooling. The research analyzes the effects of micro-pit parameters on tool wear, identifies predominant wear patterns and mechanisms, and provides technical support for the design optimization of micro-textured tools.

2. Design of Micro-Texture Parameters of Pits

2.1. Micro-Pit Parameter and Distribution of Pit Texture

Some previous studies on texture morphologies were conducted by the research team [23]. The experiment and simulation results show that micro-pit textured tools exhibit the smallest variation range in wear depth compared to tools with other texture morphologies. The studies also demonstrate that the wear area on the rake face of those textured tools displays a fan-shaped distribution—wider near the tool nose and progressively narrowing with increasing distance from the tool nose, with the maximum wear depth occurring farther from the tool nose [23].

Accordingly, this study designed fan-distributed micro-pit textures on a tool with a radius of 0.8 mm, as shown in Figure 1. The three dimensional parameters include the distance from the top micro-pit to the tool nose (Parameter A, termed as edge distance), the diameter of micro-pits (Parameter B), and the pit spacing (Parameter C).

2.2. Micro-Pit Textured Tools and Their Numbering

Three single-factor experiments were designed and conducted to study the effects of micro-pit texture parameters. The designed micro-pit textured tools with different texture parameters are shown in

Table 1. Combination scheme of the micro-pit parameters.

Tool No.	A/μm	B/μm	C/μm
1	-	-	-
2	40	40	100
3	60	40	100
4	80	40	100
5	100	40	100
6	60	30	100
7	60	40	100
8	60	50	100
9	60	60	100
10	60	70	100
11	60	40	80
12	60	40	100
13	60	40	120
14	60	40	140

. Tool No. 1 is a non-textured tool. All the micro-pits were processed at a depth of 30 μm.

3. Simulation Analysis of Tool Wear with Different Micro-Pit Parameters

3.1. Establishment of Cutting Simulation Model of Micro-Pit Textured Tool

3.1.1. Construction of Cutting Geometric Model

A geometric model of micro-pit tools was established in a 1:1 scale in the Deform-3D module. A mesh refinement of the pit textures was carried out. To improve simulation efficiency, the cylindrical workpiece was simplified into a thin-walled annular rotating body, and the tool was simplified into the part of the tool nose. The simplification of the cutting model is illustrated in Figure 2.

3.1.2. Workpiece Material Model

Corresponding to GH4169, Inconel718 in the American material grade was selected to be used in the simulation. In view of the strain hardening, strengthening, and thermalization of material, the constitutive model of Johnson–Cook is applied to the simulation to provide cutting conditions similar to the real ones. The mathematical expression for the constitutive model is shown in Equation (1).

$$\overline{\sigma }=\overline{\sigma }(\overline{\epsilon }, \stackrel{.}{\overline{\epsilon }}, T)=\left(A+B{\overline{\epsilon }}^n\right)\left[1+C\ln \left({\displaystyle \frac{\dot{\overline{\epsilon }}}{{\dot{\overline{\epsilon }}}_0}}\right)\right]\left[1-{\left({\displaystyle \frac{T-T_r}{T_m-T_r}}\right)}^m\right]$$

(1)

In the equation, $\overline{\sigma }$ is the flow stress; $\overline{\epsilon }$ is the equivalent plastic strain; $\stackrel{.}{\overline{\epsilon }}$ is the equivalent plastic strain rate; T is time; T_r is the room temperature; T_m is the melting temperature of the material; A is the initial yield stress; B is the hardening modulus; C is the strain rate correlation coefficient; m is the thermal softening coefficient; and n is the material constant. The J-C parameters of the workpiece are listed in

Table 2. Parameters of the Johnson–Cook constitutive model of Inconel718.

Materials	A/Mpa	B/Mpa	m	C	n	Tm/°C
GH4169	860	683	1	0.01	0.47	1260

.

3.1.3. Tool–Chip Friction Model

This simulation examined the cutting process of nickel-based superalloys using carbide micro-textured tools. In machining, the tool nose heated up faster than the rake face of the tool, and a temperature gradient was formed, the normal stress ratio dropped, and a sliding friction between the tool and chips occurred. To ensure simulation accuracy, a mixed-slip friction model was adopted, with its mathematical formulation provided in Equation (2).

$$\left\{\begin{array}{l}{T}_f=\mu {\sigma }_n (\mathrm{Sliding} \mathrm{zone}, \mu {\sigma }_n\le {\tau }_n)\\ T_f={\tau }_n (\mathrm{Sticking} \mathrm{zone}, \mu {\sigma }_n\ge {\tau }_n)\end{array}\right.$$

(2)

In the Equation, T_f is friction stress; ${\sigma }_n$ is normal stress; and μ is the friction coefficient. This simulation takes μ as 0.6 [24]; ${\tau }_n$ is the ultimate shear stress of the workpiece.

3.1.4. Tool Wear Model

Being applicable to the process of continuous cutting, the Usui model was adopted as the tool wear model in this study. This model simulated the real working conditions of high strain rates, temperatures, and substantial pressures. The mathematical formulation of this model is presented in Equation (3).

$$w={{\displaystyle \int apVe}}^{-{\displaystyle \frac{b}{T}}}dt$$

(3)

In the Equation, w is the wear depth; p is the tool–chip interface stress; V is the slip velocity; T is the interface temperature; and dt is the time increment. The material constants a (1 × 10⁻⁶) and b (855) are determined by the material properties of tools. In this study, referring to the results reported in reference [24], they are verified by cutting experiments and regression analysis, and are applicable to the tool wear model.

3.2. Simulation of Spray Cooling

Since the pre-processing module of the Deform v11.0 software cannot directly configure the spray cooling parameters, the research team utilized ANSYS Fluent 2022 R1 to model the spray cooling process. The spray pressure varied between 0.1 MPa and 0.3 MPa, and the flow rate was controlled within the range of 1.58 L/h to 3.16 L/h. A simulation-based temperature analysis experiment was carried out, and the cutting temperature measured by the thermocouple was compared with the simulation results to verify the accuracy of the model. The study indicates that when the spray pressure is 0.2 MPa and the flow rate 3.16 L/h, the simulated cutting temperature reaches the lowest, 114.64 °C, which is close to the temperature of 121.06 °C measured in the experiment. With these parameters, the equivalent convective heat transfer coefficient was 3137.37 W/(m²·K) [25], and this figure was imported into Deform-3D as the thermal boundary condition for spray cooling in the tool wear simulation, thus determining the optimal spray cooling parameter combination that minimizes the cutting temperature.

To ensure the comparability of simulation results and minimize interference from other parameter settings, a standardized computational configuration was implemented for all micro-textured tools with different micro-pit parameters. The simulation parameters were uniformly set as follows: total analysis steps of 1500 with a step increment of 0.01, ambient temperature maintained at 20 °C, and a constant friction coefficient of 0.6.

3.3. Wear Simulation Analysis of Micro-Pit Textured Tools

To minimize potential errors induced by simulation parameter settings, standardized across all 14 groups of tools, designed micro-pit textured tool simulations had identical operating conditions. Maintained constant for all wear simulation tests were the cutting parameters: set at v = 90 m/min was the cutting speed, fixed at f = 0.1 mm/r was the feed rate, and kept as ap = 0.2 mm was the depth of the cut. Presented in Figure 3 are the resulting wear simulation cloud diagrams for all 14 groups of tools configurations.

We analyze and organize the variation range of wear depth on the rake face of 14 groups of micro-textured tools. The results are shown in Figure 4.

Analyzing tools No. 2~No. 5, it is found that when the pit diameter and pit spacing are fixed, and edge distances are of 40, 60, 80, and 100 μm, respectively, the wear depth of the rake face makes unremarkable changes. When the edge distance is 60 μm, it shows the least wear depth on the rake face. Analyzing tools No. 6~No. 10, when the edge distance and pit spacing are fixed, and the pit diameters are 30, 40, 50, 60, and 70 μm, respectively, it is found that as the pit diameter increases, the wear depth of the rake face gradually decreases. When the pit diameter is 70 μm, it makes the least wear depth on the rake face. Analyzing tools No. 11~No. 14, when the edge distance and the diameter of the pits are fixed and the pit spacing is 80, 100, 120, and 140 μm, respectively, the wear depth of the rake face makes unremarkable changes. When the pit spacing is 100 μm, it makes the least wear depth on the rake face.

According to the tool wear cloud diagram, it is found that the wear depth of the No. 10 tool is evenly distributed, and the change in the wear depth is minimal in the area closer to the tool nose than other tools. And the maximum wear depth is away from the nose of the tool; such a distribution helps reduce tool wear and increase the service life of the tool. Therefore, the edge distance is 60 μm, the pit diameter is 70 μm, the pit spacing is 100 μm, the corresponding size is the best pit micro-texture, the tool anti-wear effect is the best, the wear distribution is uniform, and the wear depth variation range is the smallest.

4. Cutting Experiment in Spray Cooling

4.1. Experimental Design for Spray Cooling Machining Tests

This study conducted turning experiments on nickel-based superalloy GH4169 using micro-pit textured tools in spray cooling conditions, investigating the influence of different micro-pit parameters on tool wear behavior and validating the anti-wear performance of micro-textured tools. A single-factor experiment was adopted, with the edge distance (Parameter A), pit diameter (Parameter B), and pit spacing (Parameter C) serving as independent variables. The tool number and corresponding micro-texture parameters are detailed in Table 1. Based on different combinations of the micro-pit parameters presented in the text, a femtosecond laser was used to process the micro-pit texture on the rake face. The processing machine is Pharos-femtosecond-lasers (produced by Light Conversion, model PH1-15). The processing conditions are listed as follows: repetition rate of 40 kHz, energy of 30 μJ, and spot movement speed of 0.5 mm/s.

4.2. Conditions of the Experiment

In order to analyze the influence of different micro-pit parameters on tool wear, the research group used a CKA6140 CNC lathe to machine the GH4169 material under spray cooling conditions. The workpiece has a size of Φ120 × 300 mm. The tool holder adopted is a Sandvik DCLNR 2525 M12 turning tool holder. The cutting tool is a CNMA120408—KR 3225 diamond-shaped turning tool. Micro-textures with different micro-pit parameters were machined on the rake face by femtosecond laser and measured by a scanning electron microscope (SEM). The actual machined tools conform to the designed micro-pits.

The spray parameters are as follows: the nozzle outlet pressure is 0.3 MPa, the flow rate is 3 L/h, and the cutting fluid is a mixture primarily composed of Master and Castrol. Uniform cutting parameters are maintained throughout all experimental groups: the cutting speed v = 90 m/min, the feed rate f = 0.1 mm/r, the depth of cut ap = 0.2 mm, and the machining duration is constant at 30 s. The experiment setup is shown in Figure 5.

4.3. Analysis of Experimental Results

Figure 6 presents the wear morphology on the rake faces of 14 tool groups after 30 s of turning GH4169. The corresponding SEM images were acquired using a Hitachi SU3500 scanning electron microscope manufactured by Hitachi, Ltd. in Japan, which operated in the secondary electron (SE) mode. The accelerating voltage was 15.0 kV, the working distance was 6.5 mm, and the magnification was 90×. The wear regions were then processed using ImageJ 1.6.0 software, where each region was divided into discrete rectangular units. The pixel dimensions were calibrated based on the built-in scale bars in the SEM images, allowing for accurate measurement of the equivalent wear band width and band length. Based on these quantified results, a comparative assessment indicates that all micro-pit tools (Tools No. 2~No. 14) exhibit significantly reduced wear severity compared to the non-textured reference tool (Tool No. 1).

To further investigate the effects of different micro-texture parameters on the wear extent of the rake face, this study employs the differential element method to calculate the wear zone area. Specifically, the wear region is discretized into n small rectangular elements, where the width of the i-th element is l_i, and its measured height is h_i. The total wear area S can then be determined as:

$$S=l_1\times h_1+l_2\times h_2+\dots +l_n\times h_n={\displaystyle \sum _{i=1}^n{l}_i\times h_i=w\times l}$$

(4)

$$l=l_1+l_2+\dots +l_n={\displaystyle \sum _{i=1}^n{l}_i}$$

(5)

In the Equation, S represents the equivalent rectangular wear zone area, w denotes the equivalent width of the rectangular wear band, and l corresponds to the equivalent length of the rectangular wear zone. The calculated wear area results for the rake faces of all micro-pit tool groups are systematically presented in Figure 7.

Observation of tools No. 2~No. 5 shows that when the pit diameter and spacing remained constant, the wear area on the tool’s rake face decreased as the edge distance increased, with tool No. 4 exhibiting a 6.9% reduction in wear area compared to tool No. 2. Observation of tools No. 6~No. 10 reveals that with constant edge distance and pit spacing, the wear area decreased as the pit diameter increased, and tool No. 10 showed a 26% decrease in wear area relative to tool No. 6. Observation of tools No. 11~No. 14 demonstrates that with a fixed edge distance and pit diameter, the wear area increased with increasing pit spacing, and tool No. 11 had 18% less wear area than tool No. 14.

Experimental data indicate that for micro-pit textures, the pit diameter is the primary aspect affecting tool wear. Excessively large pit spacing and edge distance conversely lead to severe tool wear. As shown in Figure 7, tool No. 10 demonstrates the smallest wear area, with its wear located farther from the tool tip, exhibiting consistent trends with simulation results. Therefore, the micro-pit tool with a 60 μm edge distance, 100 μm spacing, and 70 μm diameter shows the optimal anti-wear performance.

A comparative study between dry cutting and spray cooling cutting was conducted. Tool wear on the rake face under different cutting conditions is shown in

Table 3. Tool wear on rake face under different cutting conditions.

	Tool No. 1	Tool No. 9	Tool No. 10
Dry cutting
Spray cooling

. The tool wear area of spray cooling cutting is significantly smaller than that of dry cutting.

5. Wear Mechanism of Micro-Pit Textured Tool

To further analyze the wear of micro-pit tools, the researchers used a Hitachi scanning electron microscope SU3500 to conduct a scanning analysis on the tools. Figure 8 shows the wear morphology and the enlarged wear area of the rake faces of tool No. 1 and tool No. 10, captured by the scanning electron microscope. The results indicate that both adhesive wear and micro-chipping occurred on the rake faces of both non-textured and micro-pit textured tools. However, micro-pit tools show the least wear, and the wear area was smaller. As can be seen from Figure 8b, the adhesive wear was mainly concentrated inside and near the pits. After the adhesives filled and covered some of the pits, they gradually spread outward.

To further analyze the wear of micro-textured tools, the researchers used a Hitachi scanning electron microscope SU3500 to conduct a scanning analysis on the tools. The imaging conditions were 15.0 kV voltage, a working distance of 8.4 mm, and a magnification of ×200 under SE mode. Figure 8 shows the wear morphology and the enlarged wear area of the rake faces of tool No. 1 and tool No. 10 captured by the scanning electron microscope. The results indicate that both adhesive wear and micro-chipping occur on the rake faces of both non-textured and micro-pit textured tools. However, the micro-textured tools are less worn and have a smaller wear area. As can be seen from Figure 8b, the adhesive wear mainly occurred inside and near the pits. After the adhesives fill and cover some of the pits, they gradually spread outward.

The anti-wear mechanism can be explained by Figure 9, which demonstrates that the embedded micro-pit textures effectively retain cutting fluid during the cutting process. The stored fluid is gradually released and evenly distributed on the tool–chip interface, forming a stable lubricating barrier that significantly reduces the direct contact area between the tool and chips, thereby decreasing friction. Experimental results further reveal that larger pit diameters enhance this effect, as they allow more cutting fluid to be stored and maintained within the textures. Consequently, a thicker and more continuous lubricating film is formed, which improves the load-bearing capacity, reduces interfacial shear stress, and serves as a thermal buffer to delay heat transfer to the cutting edge. These factors collectively minimize both frictional and thermal wear. At the same time, the cutting fluid retained in the micro-textures improves cooling efficiency, lowering the cutting zone temperature and reducing diffusion wear at the tool–workpiece interface. By simultaneously improving lubrication and heat dissipation, particularly due to the larger pit diameters that enhance fluid retention and reduce the real contact area, the micro-textures effectively reduce the tool wear rate while enhancing cutting performance and extending tool life.

From the above experiments, it can be concluded that the micro-pit tool has excellent tribological properties. To further verify the experiment conclusions, Ansys Fluent was used to conduct a further simulation analysis of the dynamic pressure of the oil film on the micro-textured surface [26]. Taking the planar friction pair as the research object, the pressure distribution of the oil film on the surface of a single micro-pit was studied. Among them, the density of the lubricating oil was set at 930 kg/m³, the flow velocity of the lubricating oil was set at 1.5 m/s, and the inlet oil pressure was set at 150 kPa. The simulation result diagram of the micro-texture pressure and the trace diagram of the flow through the inside of a single texture are shown in Figure 10a,b.

As is shown in Figure 10a, when lubricant enters the interior of the micro-pit, the increased space causes a reduction in hydrodynamic pressure. As lubricant flows out of the pit, the pressure increases when moving from divergent gaps to convergent gaps. In the simulation, a surface integral report was generated, showing that a single micro-pit oil film surface can provide upward bearing capacity. From the flow streamlines in Figure 10b, it is observed that due to the regular circular micro-texture morphology, the vortex exhibits well-defined symmetry with stable pressure fluctuations.

6. Conclusions

In this study, micro-pit tools were used in cutting GH4169 in spray cooling. The textures of micro-pits in different parameters were designed on the rake face. Based on simulation and experimental analysis, the effect of micro-pit textures in three different parameters on tool wear is revealed, and the conclusions are drawn as follows:

(1) Tools with micro-pits of different parameters were applied in cutting. A simulation model of cutting was established. The simulation model was verified by experiments. The simulation and experiment results indicate that (1) among the three parameters, B (the diameter of micro-pits) has a significant impact on the wear of the rake face: as the pit diameter increases, the wear area of the rake face gradually decreases; (2) the other two parameters (the distance between the top micro-pit and the tool nose, and the pit spacing) have little effect on the wear of the rake face.

(2) In comparison with non-textured tools, micro-pit tools bear a better anti-wear capacity. When micro-pits are applied, the tool–chip contact length can be reduced, and more lubricating fluid can be stored. An effect of micro-pool dynamic lubrication is formed, which effectively reduces the friction at the tool–chip interface and improves the anti-wear performance of the rake face.

(3) With the investigation of 13 designed micro-pit tools, the optimal parameter combination is obtained from the simulation and experiment results. When the distance between the micro-pit and the tool nose is 60 μm, the diameter of micro-pits is 70 μm, and the pit spacing is 100 μm, the best anti-wear performance can be achieved.

This article reveals the effect of micro-pit tools with different parameters on tool wear. The conclusion of the article was drawn from a series of experiments and simulations, and it provides technical reference for both the machining of GH4169 and the application of micro-textured tools.