Cutting tool wear minimization in drilling operations of titanium alloy Ti-6Al-4V

Cutting tool wear during drilling operations can cause damage to cutting tools, machine tools, and workpieces which should be analyzed and minimized. Cutting tool wear impacts not just tool life but also the quality of the final product in terms of dimensional accuracy and surface integrity. High mechanical and thermal loads are generated during drilling operations of difficult-to-cut materials such as Ti-6Al-4V alloy which can reduce the life of cutting tool during chip formation process. Thus, to increase the accuracy of drilled parts from titanium alloy Ti6-Al-4V, the cutting tool wear during drilling operations should be accurately predicted in order to be minimized. Application of virtual machining systems is developed in the study in order to predict and minimize the cutting tool wear during drilling operations of titanium alloy Ti-6Al-4V. To predict the tool wear during drilling operations, cutting forces and temperature are calculated. Then, the finite element method (FEM) is utilized to predict the tool wear using the analytical model of Takeyama–Murata and updating the cutting tool geometry during chip formation process. To minimize the cutting tool wear during drilling operations, the optimum drilling parameters of feed rate and spindle speed are obtained using the Taguchi method-based response surface analysis algorithm. As a result, optimized drilling parameters are used in order to minimize the cutting tool wear during drilling operations. To validate the study, the experimental works are implemented to the sample workpiece from titanium alloy Ti6-Al4-V and the values of tool wear are then measured. To present the effectiveness of the proposed virtual machining system in minimization of cutting tool wear, the obtained results with and without optimized machining parameters are evaluated and compared. So, precision and productivity in drilling operations of titanium alloy Ti6-Al4-V can be enhanced using the developed virtual machining system in the study.


Introduction
Drilling is a technique that involves removing undesirable materials using a multi-point instrument in order to create a specified hole on the workpieces. It is a major operation in the final assembly process when screws are utilized to link the components together in order to give the product its final shape. Millions of holes are needed to be produced for riveted and bolted joints during the assembly process of the aircraft's structures. So, the drilling operation is considered the most challenging operation among all the other machining process in the aerospace industries. 1 Fatigue resistance, density, fracture toughness, strength, and corrosion resistance are major design criteria for aerospace structures. 2 The poor hole quality can create cracks within the airframe structure and reduces reliability of produced aircraft's structures. 1 Tool wear has a significant impact on not only life of cutting tool but also quality of produced parts in terms of dimensional accuracy and surface integrity. In continuous chip generation processes, the cutting tool's gradual tool wear is created due to abrasion, adhesion, diffusion, chemical erosion, and galvanic action. 3 These phenomena during chip formation process are under influence of chosen cutting parameters, such as speed of cutting and feed rate. Moreover, during machining operations of difficult-to-machine materials like titanium alloy Ti6-Al-4V, high mechanical and thermal loads are generated which can decrease the performance and cutting tool life during chip formation process. Due to chemical, physical, and mechanical characteristics of titanium alloys, the alloys are widely used in aerospace and automotive industries. These alloys are distinguished by high melting temperature, strong corrosion and creep resistance, high wear resistance, and high strength at increased temperatures. As a consequence, titanium alloys are employed in applications that need great fatigue strength and corrosion resistance due to mechanical properties of alloys. However, the manufacturing process of parts from titanium alloys are expensive due to rapid tool wear, catastrophic failure, or plastic deformation of the cutting tool during chip formation process. 4 So, advanced virtual machining system which can predict and minimize cutting tool wear during drilling operations of titanium alloy Ti6-Al-4V can provide a key tool in increasing the precision and productivity of component production process utilizing drilling operations.
Numerical modeling of tool wear in drilling operations of Inconel 718 is proposed by Attanasio et al. 5 to investigate the impact of tool wear on a machined surface in terms of flooding and cryogenic cooling drilling operations. To analyze the effects of machining parameters on rate of tool wear during drilling operations of float glass using rotary ultrasonic machining operations, chipping volume during chip formation process is studied by Sharma et al. 6 In order to estimate and optimize tool wear during MQL-assisted milling operations of Inconel 718 superalloy, application of the evolutionary methodologies is studied by Singh et al. 7 Monitoring and prediction of tool wear based on the acoustic signal during milling operations is presented by Liu et al. 8 in order to accurately predict the cutting tool wear regarding the different milling parameters. Tool wear estimation and cutting parameter optimization using the innovative adaptive neuro fuzzy inference system-particle swarm optimization (ANFIS-PSO) approach for smart machining is presented by Xu et al. 9 in order to predict and minimize the tool wear using smart milling operations.
The impact of ultrasonic-aided drilling on tool wear and drilling parameter optimization is studied by Yarar and Karabay 10 to minimize the tool wear during the ultrasonic-assisted drilling operations. A unique approach for predicting and measuring coated cutting tool wear during turning operations of Inconel DA 718 is developed by Capasso et al. 11 to accurately predict tool wear during different cutting conditions. Real-time tool wear tracking system using a cutting condition independent methodology is proposed by Nouri et al. 12 to decrease the failure rate of cutting tool during milling operations. Multi-sensor signals and the Mahalanobis-Taguchi System are used by Rizal et al. 13 in order to classify and identify cutting tool wear during milling operations. Artificial intelligence approaches are utilized by Shankar et al. 14 in order to estimate cutting tool wear during milling process. In order to investigate the effect of machining variables on rate of cutting tool wear during process of chip formation throughout milling operations, the influence of cutting temperature on cutting tool wear is investigated by Maruda et al. 15 Cutting tool wear in turning operations is numerically modeled by Rech et al. 16 to investigate the effects of local tribological loading on the wear rate of cutting tool. Estimation of cutting tool wear size regarding different cutting conditions using machine learning approaches is investigated by Shen et al. 17 in order to extend life of cutting tool during machining operations. Zhao et al. 18 evaluate and investigate the influence of cutting-edge radius in order to reduce tool wear during hard turning operations of AISI 52100 steel alloys. Deep learning and temperature signals are used by He et al. 19 in order to predict tool wear and enhance cutting tool life during turning operations. Tool wear simulation during chip formation process is studied by Maruda et al. 20 in order to minimize the failure rate of cutting tool due to tool wear during turning operations of AISI 1045 carbon steel.
Soori et al. [21][22][23][24][25][26] described virtual machining approaches and methodologies for evaluating and improving machining operations in virtual environments. Soori and Arezoo 27 proposed a review in machining that caused residual stress in order to assess and decrease residual stress throughout metal cutting operations. Soori et al. 28 presented an enhanced virtual machining approach for improving surface characteristics of turbine blades during five-axis end milling operations. Soori and Asamel. 29,30 reviewed and analyzed current advancements in research efforts to investigate the mechanical properties of components in cutting operations as well as friction stir welding (FSW) procedures. Soori and Asamel 31 evaluated the applications of computer-aided process planning (CAPP) in industrial systems in order to enhance productivity in process of part manufacturing. to reduce deflection inaccuracy and residual stress in five-axis CNC milling operations of turbine blades, Soori and Asmael 25 proposed a virtual machining methodology. Soori and Asmael 26 created a virtual machining system to assess and reduce cutting temperatures throughout milling operations of difficult-to-cut components. To examine and modify the optimization method of machining parameter during different machining operations, recent advancements from the published articles is reviewed by Soori and Asmael. 32 Soori and Arezoo 33 analyze the applications of virtual machining technologies in milling and turning CNC machine tools in order to improve productivity in component production process using machining operations. An assessment of machining-generated residual stress is analyzed by Soori and Arezoo 27 in order to assess and minimize residual stress throughout metal cutting operations. To increase cutting tool life during machining operations, several approaches of tool wear prediction are studied by Soori and Arezoo. 34 To reduce the deflection error in five-axis milling of impeller blades, Soori and Asmael 35 proposed an advanced virtual machining technique. A sophisticated virtual machining technique was established by Soori et al. 28 in order to enhance surface quality during five-axis milling operations of turbine blades. To increase the efficiency of energy consumption during part production process, the quality and transparency of data across the supply chain, and precision and reliability throughout component manufacture, Dastres et al. 36 recommended evaluating radio frequency identification (RFID)-based wireless manufacturing systems.
According to analysis of the previous research works, the prediction and minimization of tool wear during the drilling operations using the virtual machining systems is not studied. As a result, in order to increase the accuracy as well as efficiency of component manufacturing utilizing the applications of virtual machining systems in drilling operations, the research work is original and new methodology.
To reduce cutting tool wear while drilling titanium alloy Ti6-Al-4V, a virtual machining system is created in the research work. In order to predict the tool wear, the cutting forces and temperature are calculated during the drilling operations. The coupled Eulerian-Lagrangian approach is used to simulate the impact of coolants on the estimation of cutting temperature throughout drilling operations of titanium alloy Ti6-Al-4V. In order to calculate tool wear during the chip generation process, the finite element method (FEM) is then utilized using Takeyama-Murata analytical model. The geometry of the cutting tool is then modified regarding the obtained values of tool wear at each position of the cutting tool throughout drilling operations. The method is then repeated until the completion of drilling operations in order to achieve the new cutting tool geometry regarding the calculated values of tool wear during drilling operation. In order to minimize the tool wear, the Taguchi method-based response surface analysis algorithm optimization methodology is utilized in order to obtain the optimized cutting parameters of cutting speed and feed rate during drilling operations. The experimental works are then implemented to the sample workpiece from titanium alloy Ti6-Al-4V in order to validate the effectiveness of the proposed virtual machining system in the study.
The SOIF XJP-2B optical microscope is then used in order to measure. The values of tool wear during drilling operations. As a consequence, the experimental as well as predicted results with and without optimized machining variables are compared in order to present the effectiveness of the developed virtual machining system in the study in terms of cutting tool wear minimization using virtual machining systems.
Cutting forces in drilling operations and Arrheniustype tool wear models are presented in sections 2 and 3 respectively. The Jonson-Cook Model for the Ti6Al4V alloy is described in section 4. In section 5, a surface roughness model during drilling operations of titanium alloy is described. Taguchi optimization method of drilling parameters is presented in section 6. Section 7 presents the proposed virtual machining methodology in order to predict and minimize tool wear during drilling operations. The experimental works and simulation of the tool wear during drilling operations are presented in the section 8. Finally, the results of research work are presented in section 9.

Cutting forces in drilling operations
Mathematical modeling and experimental study of thrust cutting forces during drilling operations of a titanium alloy is presented by Glaa et al. 37 The cutting force differential components in three directions of radial, tangential, and zenith, are calculated as follows: where K rc , K tc and K ψc are the cutting force constants in the radial, tangential, and zenith directions. dA is the chip sheared section by the flute j of the tool which can be presented as 37 Δb is the differential chip width as Δb = dz cos κ . Also, h j (t) is the undeformed chip thickness faced by the tool's flute j in one rotation which is the combination of the "static" and "dynamic" chip thicknesses as 37 where f z is the rate of feed per flute and T is the flute passage duration time as T = 60 N t n . So, the components of the differential forces produced by the damping influence in the three directions of radial, tangential, and zenith can be presented as 37 where [C d ] is the factor's damping matrix as 37 where C r kj , C t kj and C ψ kj describe the cutting damping components in the radial, tangential, and zenith directions. As a consequence, the workpiece was subjected to the total of the differential shear stresses and the differential damping forces in the radial, tangential, and zenith directions as 37 The three differential cutting force components of x, y, and z axes are characterized as follows: 37 The overall cutting forces can be calculated as follows: 37 where F p is an additional force which is added to the F z . Also, the F p for the workpiece with Ti6-Al-4V alloy is obtained by experimental works as 37 where V f = fn is the rate of feed (mm/min) and S is the section of the extruded chips.

Arrhenius-type tool wear models
To simulate the rate of cutting tool wear considering the cutting temperature, the Takeyama-Murata's model is presented as 38 where A is a pre-exponential constant, E a is the energy of activation, R is the universal gas constant, and T is cutting temperature in Kelvin. The abrasive term is calculated by considering the feed rate and sliding speed during chip formation process. According to the model, contact normal stress and sliding speed between cutting tool and chip are related to the tool wear rate as 38 where A is a pre-exponential constant, σ n is contact stress which is normal, and υ s is speed of sliding. Also, B indicates the cumulative temperature-dependent due to the thermal softening and wear asperities diffusion into the workpiece, as well as the chance of a wear particle forming. As a result, similar to Takeyama and Murata's model, an Arrhenius-type model is employed and simplified to either of the replaceable wear/time or wear/distance versions as 38 and where A is a pre-exponential constant, w is unit of volume, s is sliding distance, R is the constant of universal gas, and E a is activation energy.

Johnson-Cook model
The effect of hardness due to stress, rate of strain, and heat relaxing on the stress of the component's flow throughout deformation are described using the three variables in the Johnson-Cook model. The three variables describe the effect of hardness due to stress, rate of strain, and heat relaxing on the stress of the component's flow throughout deformation. Due to the obvious method's versatility in FEM analysis, it is used to assess the deformation inclinations of different materials. The Johnson-Cook model is 39 where ε is equal strain of plasticε andε0 are the equal and basis strain rates of plastic, T, T m , and T 0 are the temperature of cutting area, temperatures of melting and experimental room, respectively. The m is index of softening with heat, while the hardening index of the strain is N. A, B, and C are the material's rate of elastic modulus, strain, and strain responsiveness, respectively. According to the Johnson-Cook model, the three influencing elements of strain, strain amplitude, and temperature are completely independent of each other, limiting any one of them from having a cumulative effect. Such strain rate dependency is difficult to anticipate using the usual J-C constitutive model. The updated Johnson-Cook model studies the interplay between deformation temperature and strain rate on flow stress, significantly improving the model's prediction accuracy over the original Johnson-Cook model. 40 The modified Johnson-Cook model is suggested by Lin and Chen 41 to address the problems of the Johnson-Cook model as equation (15), where A 1 , B 1 , B 2 , C 1 , λ 1 , and λ 2 are characteristics of material, and the other parameters have the same quantities as in the Johnson-Cook model. The modified Johnson-Cook model for cutting titanium alloy Ti6-Al-4V as equation (16) is presented by Ren et al. 42 using the firefly algorithm σ = 724.7 + 683.1ε 0.47 1 exp (ε 3.7758 ) where parameters D and P are introduced to describe the effect of dynamic recrystallization and recovery mechanisms on flow stress, respectively. The parameters of D and P can be calculated as equations (17) and (18) Middle surface roughness Exit surface roughness = 0.030284 N − 23.03896 f where N and f are known as spindle speed and feed rate, respectively.

Taguchi optimization method of drilling parameters
The Taguchi method is a strong and efficient optimization technique that can significantly increase process performance with a minimal number of tests. The optimization process decreases rework, production, and cycle time expenses in manufacturing processes by determining the optimal values of the objective functions. Figure 1 presents the flowchart of Taguchi optimization technique.
The signal-to-noise ratio (S/N) for each control component is calculated in order to ascertain the impact of drilling settings on the response characteristic. The signals demonstrate the evolution of the effect on average replies. The noises are a measurement of the impact of noise elements on variations from average responses, which take into consideration the sensitivity of the experiment's output to noise. There are many kinds of quality standards used in the response analysis process, including the nominal-the-better, the lower-the-better, and the higher-the-better. The lowerthe-better criteria is used to select the S/N ratio in order to where n is the number of times the experiment was repeated and y i is the averaging of the measured value of the experimental data.

Virtual machining system to predict and minimize tool wear during drilling operations
In order to predict and minimize the cutting tool wear during drilling operations, application of virtual machining systems is developed in the study. Virtual machining systems use input data such as cutting tool geometries and alloys, workpiece materials, and drilling variables to forecast tool wear during drilling operations. Next, the cutting forces and temperatures during the chip generation process are computed in order to predict cutting tool wear during drilling operations. Figure 2 shows the flowchart for calculating cutting force and cutting temperature. The FEM is then utilized in order to estimate the angles and geometry of the cutting tools, namely the rake, flank, and cutting-edge nose. Next, the values of cutting tool wear are assessed utilizing analytical Takeyama-Murata's model. Regarding the determined values of tool wear at each location of the cutting tool throughout drilling operations, the geometry of the cutting tool is subsequently modified. In order to achieve the new cutting tool shape regarding the tool wear during drilling operation, the procedure is then continued until the end of drilling operations. Figure 3 shows the flowchart of virtual machining system for cutting tool wear prediction during drilling operations.
Cutting tool wear during drilling operations is increased by enhancing the drilling parameters of feed rate and/or cutting speed during chip formation process. A little variation in cutting speed can significantly change the rate of tool wear during chip formation process. 45 The Taguchi method-based response surface analysis approach is then used to obtain the optimized drilling parameters of feed rate and speed of spindle in terms of cutting tool wear minimization during drilling operations. The initial goal of optimization is to minimize cutting temperature, which can be implemented by reducing cutting pressures during chip formation process of drilling operations. As a consequence, the optimized drilling parameters of feed rate and spindle speed are calculated in order to minimize cutting tool wear during drilling operations of titanium alloy Ti6-Al4-V. The complete methodology of the study in minimization of tool wear during drilling operations is shown in Figure 4.

Validation and simulation
In order to validate the developed virtual machining system in the study, drilling tests were performed using the Neway VM1304H vertical milling machine tool center under internal cooling condition. The carbide Sandvik coromant with round shank, two cutting edges and coolant through is the drill bit which is used in the excremental works of the study. The specification of used drill bit in the experiments is shown in Figure 5.
The parameters of drilling operations in the experiments are cutting speed (vc) 24 m/min and feed rate (f) 0.11 mm/rev. The workpiece material in the experiment is titanium alloy Ti6-Al-4V. The used coolant in drilling operations is composed of 95% water and 5% synthetic cutting fluid which is delivered to the cutting zone with a pressure of 20 bars. Figure 6 shows the drilling operations of sample workpiece from titanium alloy Ti6-Al-4V.
Finite element model of drilling operations is implemented using the Abaqus R2016X FEM analysis software in order to predict the cutting tool wear during drilling operations. The simulations are carried out using a configurable mesh density and a minimum element size of 1 µm. A workpiece with chip shape is mesh generated with 240,000 tetrahedral components and the drilling cutting  tool is also mesh generated with 150,000 tetrahedral elements. Moreover, the cutting region is mesh generated with an extremely fine mesh in order to present accurate temperature distributions of drilling operation using FEM. The impacts of coolants on the cutting temperature distributions during drilling operations of titanium alloy Ti6-Al-4V are then determined by applying the coupled Eulerian-Lagrangian approach. Figure 7 shows the FEM-Simulation of temperature distribution during drilling operations of titanium alloy Ti6-Al-4V.
The FEM simulation of cutting zone temperature distribution during drilling operations of titanium alloy Ti6-Al-4V is shown in Figure 8.
The error bar for the FEM simulation of cutting temperature during drilling operations of titanium alloy Ti6-Al-4V is shown in Figure 9. Figure 10 shows the simulated and actual pattern of flank wear in cutting tool after 8 min of drilling operations of titanium alloy Ti6-Al-4V.
To measure the tool flank wear in the experiments, the SOIF XJP-2B optical microscope is utilized. The microscope measurement range is 0-50 mm, the digital step of the microscope micrometer, and the maximum permissible error during measuring process are 0.001 µm and ±3 µm, respectively. In order to measure cutting tool flank wear during drilling operations, microscopic visualization method based on the ISO standard for tool life testing 3685:1993 is utilized. Figure 11 shows an optical microscope view of a drilling cutting tool after 8 min of drilling titanium alloy Ti6-Al-4V. Figure 12 shows the measured cutting tool flank wear in the region of A from the Figure 11 after 8 minutes of drilling operation of Titanium alloy Ti6Al4V.
The measured and FEM simulation of cutting tool wear during drilling operations of titanium alloy Ti6-Al-4V is shown in Figure 13.
In order to reduce cutting tool wear during drilling operations, the Taguchi method-based response surface analysis approach is used. The "lower-is-better" category has been utilized to determine the S/N ratios for cutting tool wear during drilling operations. So, the optimized drilling parameters of cutting speed and feed rate are calculated in order to minimize cutting tool wear during chip formation process. The S/N ratios for the average tool wear of 90 holes regarding the different drilling parameters of feed rate and cutting speed after 15 min of drilling operation are obtained and presented in Table 1.
The high value of S/N ratio corresponds to better performance during drilling operations regardless of the category of the performance characteristics. Therefore, the level with the greatest S/N ratio can be considered the optimal level of the process parameters. As a result,  using the maximum S/N ratio during optimization process, the optimized drilling parameters of feed rate and cutting speed are obtained as 0.11 mm/rev and 15 m/min, respectively. Figure 14 shows the measured and FEM-simulation of cutting tool wear during drilling operations of titanium alloy Ti6-Al-4V using optimized drilling parameters.

Conclusion
An application of virtual machining system is developed in the study in order to minimize cutting tool wear during drilling operations of titanium alloy Ti6-Al-4V. To calculate tool wear during drilling operations, cutting forces and temperature are determined. The impacts of  coolants on the prediction of cutting temperature throughout drilling operations of titanium alloy Ti6-Al-4V are determined utilizing coupled Eulerian-Lagrangian approach. Then, the FEM is used to predict tool wear during chip formation process. The geometry of the cutting tool is subsequently modified regarding the determined values of tool wear at each location of the cutting tool during drilling operations. As a result, the modified geometry of cutting tool is obtained in order to be used in terms of minimization process of tool wear during drilling operations. To minimize the tool wear, the Taguchi method-based response surface analysis algorithm is utilized and optimized drilling parameters of feed rate and cutting speed are obtained. A sample workpiece made of titanium alloy Ti6-Al-4V is machined in order to   demonstrate the effectiveness of the proposed virtual machining technology in minimization of tool wear during drilling operations. To validate the created virtual machining system in the process of tool wear prediction and minimization, the predicted and experimentally measured cutting tool wear during drilling operations are compared and analyzed. As a result, 1. The developed virtual machining system in the study can accurately predict tool wear during drilling  operations and 97.53% compatibility is also obtained by comparing the results of virtual machining system and experimental data of tool wear during drilling operations. 2. Using the S/N ratio according to the criterion lower-thebetter in the optimization process, the optimized drilling parameters of feed rate and cutting speed are obtained as 0.11 mm/rev and 15 m/min, respectively. 3. Using the optimized machining parameters, 25.8% reduction in the cutting tool wear during drilling operations of titanium alloy Ti6-Al-4V is achieved. 4. The developed virtual machining system can decrease the cutting rate of tool failure by decreasing the rate of tool wear during drilling operations which can decrease the cost of part production using drilling operations. 5. Accuracy, as well as productivity in drilling operations of titanium alloy Ti6-Al-4V, can be increased by employing the developed virtual machining system in the study. 6. The effects of different cutting fluid properties on the quality of machined parts can also be analyzed using virtual machining systems in order to obtain the optimized machining parameters regarding the influence of cutting fluid properties on the tool wear and surface roughness during drilling operations. So, the cost of part production using the drilling operations can be analyzed and minimized in terms of productivity enhancement of manufacturing process. This is the concept of future research work of the authors.

Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.