Multi-Response Optimization and Experimental Investigation of the Influences of Various Coolant Conditions on the Milling of Alloy 20

: This study investigates the machining processes of Alloy 20 under different cooling conditions: Minimum Quantity Lubrication (MQL), Carbon Dioxide (CO 2 ), and the hybrid MQL + CO 2 approach. The research focuses on optimizing the cutting parameters, understanding the surface characteristics, analysing the tool wear patterns, and evaluating the chip formation. Face-centred CCD-based response surface methodology (RSM) is applied in order to identify the optimized cutting conditions. Surface roughness, tool wear, and chip morphology are examined through SEM imaging. Surface roughness characteristics reveal distinctive characteristics for each coolant condition: MQL cooling results in a relatively rough surface with tool nose degradation, CO 2 cooling shows scratches on the surface and tool chipping, and MQL + CO 2 cooling yields a smoother finish with close and continuous chip formation under the optimized conditions. This study contributes valuable insights into the complex interactions between cutting parameters and coolants, aiding in the optimization of machining processes for improved outcomes of the machining of Alloy 20. Based on the RSM outcomes, the optimal parametric settings obtained are V c = 44 m/min, f = 0.04 mm/rev, and a p = 0.43 mm.


Introduction
Supercritical Carbon Dioxide Cooling with Minimum Quantity Lubrication (scCO 2 + MQL) has proven to be highly beneficial in enhancing tool life and surface finish (R a ) while milling AISI 304L stainless steel.Wika et al. [1] found that scCO 2 + MQL increased tool life by 324% and improved R a by 30% compared to flood cooling.The tool life was improved due to lower cutting temperatures, while the R a was enhanced by reducing built-up edge formation.Cryogenic cooling using liquid nitrogen (LN 2 ) has also been shown to benefit stainless steel milling.Nalbant et al. [2] found that cryogenic cooling significantly impacts cutting forces (CF) compared to dry milling.This effect is especially pronounced at lower cutting speeds (V c ) and is attributed to the rapid cooling process inducing increased strain hardening.However, Paul et al. [3] found that cryogenic cooling reduced tool wear (TW) and improved R a compared to dry and wet machining.These benefits are attributed to lower cutting temperatures and changes in chip formation.When comparing cooling strategies in the milling of medium carbon steel, Silva et al. [4] conducted research that effectively optimize the high-speed machining of Alloy 20 for surface roughness and MRR.Higher V c , lower f, and moderate a p are generally found to optimize the responses.
Based on the literature available, it is clear that the milling of Alloy 20 is very scarce.No studies were reported on the milling of Alloy 20 under three different cooling conditions, and information regarding the optimization of the milling of Alloy 20 with RSM is also very difficult to find in the literature.This paved the way for us to carry out experiments with the optimized input parameters in order to study responses such as surface characteristics, tool wear, and chip formation.The following section contains the machining conditions used for milling Alloy 20.

Experimental Setup
For the milling experiments, a YCM EV20 CNC machine (Yeong Chin Machinery Industries Co. Ltd., Taiwan, China) was utilized.This machine has a maximum spindle speed of 8000 rpm and a power supply of 5.5 kW.These milling experiments used materials such as Alloy 20, which has 150 × 100 × 10 mm dimensions.Tables 1 and 2 provide information on the workpiece chemical composition and the mechanical properties of Alloy 20, respectively.End milling was investigated in this study using a BAP-07H tool holder (Jining Qinfeng Machinery Hardware Co., Ltd., Jining, China) to secure the APMT 1135 PDTR (CS Cutoutil Hardware Tools Co., Ltd., Changsha, China) indexable titanium aluminium nitride (TiAlN)-coated cutting inserts with a nose radius of 0.8 mm.

Hardness (HV) 222
A detailed account of the input factor levels is provided in Table 3.The face-centred central composite design (CCD) utilized to construct the design matrix.The face-centred CCD comprises 20 points, including 15 non-centre points and 6 centre points, all used for each level of the categorical factor (surface roughness), resulting in 60 runs in the design matrix (as shown in Table 4).DOE and subsequent statistical analysis were carried out using Design Expert 13 software.Cutting speed (V c ), feed rate (f ), and depth of cut (a p ) were selected as the milling parameters.The input factor levels were assigned based on a thorough literature survey and an assessment of the technical capabilities of the machine.In addition, trial experiments were conducted to find the input factors and the levels needed to mill Alloy 20, and the DOE was set based on the successful input parameters used when machining Alloy 20.A total of three trials were conducted on the input process parameter levels.Response surface methodology was utilized for establishing the designs of the milling experiments.Response surface methodology is a statistical technique that aids in determining the ideal mix of input parameters to produce the intended result.The experiments identified the most efficient combination of f, a p , and V c needed to produce the R a required by using a literature review to determine the high and low input parameters.This allowed the experiments to produce the desired level of R a .The average surface roughness (R a ) of a specific area was measured at five different locations with the help of a portable test device TR200 model (TMTeck Instrument Co., Ltd., Beijing, China).The average of the measurements was considered as the surface roughness value.The device used could measure surfaces with a cut-off length of 0.8 mm and a traverse length of 4 mm.It is common practice in industries to utilize a small amount of lubricant within the workpiece interface via the Kenco MQL setup.The air pressure and flow rates typically used are 4 bars and 10 mL/h to 100 mL/h, respectively.For cryogenic conditions, a pressure regulator is utilized to regulate the flow of LCO 2 through a nozzle of approximately 20 kg/h throughput with a self-pressurized cylinder.Figure 1 illustrates a schematic view of the experimental conditions for the milling of Alloy 20.

ANOVA
ANOVA is a useful mathematical method for testing the significance of an experiment and analysing the response [20].It helps to find out the significant parameters and signal-to-noise ratios present in minimized values of the control variables, so that the processing parameters can be optimized by ANOVA methods [21].ANOVA can be applied in order to study the performance characteristics of machining process parameters such as cutting speed, feed, depth of cut, and width of cut, with consideration to multiple responses [22].The experimental results-that is, the surface roughness observed for the three cooling environmental conditions of MQL, CO2, and hybrid CO2 + MQL-are exhibited in Table 4, while the ANOVA results for the different conditions are shown in Table 5, Table 6, and Table 7, respectively.In the analysis of variance (ANOVA) conducted for the three distinct coolant conditions, namely MQL (Minimum Quantity Lubrication), CO2, and hybrid CO2 + MQL, various cutting parameters were examined for their influences on the surface roughness.The results revealed noteworthy findings for each coolant condition.
For the MQL cooling condition, the ANOVA indicated that cutting speed and feed rate are statistically significant factors affecting surface roughness.Additionally, the significance of the squared terms, specifically the square of Vc and the square of ap, suggests that nonlinear effects play a role in the variation of surface roughness under MQL.
In the case of the CO2 cooling condition, similar trends emerged.Vc and f were identified as significant contributors to Ra, aligning with the MQL condition and including squared terms, such as the square of Vc and the square of ap, which further emphasized the role of nonlinear effects in shaping the Ra outcomes.
In the case of the hybrid CO2 + MQL cooling condition, it showcased a consistent pattern.Vc and f maintained their significance in influencing Ra.The analysis revealed that the combined effect of "f" and "ap" with the squared terms (square of Vc and square of ap) is also statistically significant.This suggests that interactions between cutting parameters and additional nonlinear effects contribute significantly to surface roughness outcomes in the hybrid cooling condition.Regression models for the surface roughness of all the cooling environment conditions are presented in equations later in this section.
The ANOVA results consistently underscored the significance of "Vc" and "f" across all three coolant conditions-MQL, CO2, and hybrid CO2 + MQL-in influencing the surface roughness.Moreover, including squared terms and interaction effects in the analysis

ANOVA
ANOVA is a useful mathematical method for testing the significance of an experiment and analysing the response [20].It helps to find out the significant parameters and signalto-noise ratios present in minimized values of the control variables, so that the processing parameters can be optimized by ANOVA methods [21].ANOVA can be applied in order to study the performance characteristics of machining process parameters such as cutting speed, feed, depth of cut, and width of cut, with consideration to multiple responses [22].The experimental results-that is, the surface roughness observed for the three cooling environmental conditions of MQL, CO 2 , and hybrid CO 2 + MQL-are exhibited in Table 4, while the ANOVA results for the different conditions are shown in Table 5, Table 6, and Table 7, respectively.In the analysis of variance (ANOVA) conducted for the three distinct coolant conditions, namely MQL (Minimum Quantity Lubrication), CO 2 , and hybrid CO 2 + MQL, various cutting parameters were examined for their influences on the surface roughness.The results revealed noteworthy findings for each coolant condition.For the MQL cooling condition, the ANOVA indicated that cutting speed and feed rate are statistically significant factors affecting surface roughness.Additionally, the significance of the squared terms, specifically the square of V c and the square of a p , suggests that nonlinear effects play a role in the variation of surface roughness under MQL.
In the case of the CO 2 cooling condition, similar trends emerged.V c and f were identified as significant contributors to R a , aligning with the MQL condition and including squared terms, such as the square of V c and the square of a p , which further emphasized the role of nonlinear effects in shaping the R a outcomes.
In the case of the hybrid CO 2 + MQL cooling condition, it showcased a consistent pattern.V c and f maintained their significance in influencing R a .The analysis revealed that the combined effect of "f " and "a p " with the squared terms (square of V c and square of a p ) is also statistically significant.This suggests that interactions between cutting parameters and additional nonlinear effects contribute significantly to surface roughness outcomes in the hybrid cooling condition.Regression models for the surface roughness of all the cooling environment conditions are presented in equations later in this section.
The ANOVA results consistently underscored the significance of "V c " and "f " across all three coolant conditions-MQL, CO 2 , and hybrid CO 2 + MQL-in influencing the surface roughness.Moreover, including squared terms and interaction effects in the analysis highlighted the complexity of the relationships between cutting parameters and R a under varying coolant conditions.These findings provide valuable insights for optimizing machining processes and selecting appropriate coolant strategies to achieve the desired surface quality in manufacturing settings.

Response Surface
Response surface methodology (RSM) is an integrated optimization methodology of mathematical and statistical techniques used for modelling and optimizing response variables, incorporating quantitative independent variables [23].RSM helps quantify the relationships between one or more measured responses and the vital input factors [24].In this study, the investigation focused on the end milling method applied to Alloy 20, utilizing tool holders designated as BAP-07H and cutting inserts featuring TiAlN coatings.The objective was to explore the machining characteristics and surface quality under different cooling conditions, specifically MQL, CO 2 , and a hybrid MQL + CO 2 approach.Figure 2 shows the surface roughness plots under different cutting parameters The findings are summarized through the analysis of 3D response surfaces for each coolant condition.The response surface for MQL revealed that low R a is associated with specific combinations of cutting parameters.A lower f and a higher V c were optimal for achieving minimal R a in the MQL coolant condition.The investigation into the CO 2 cooling condition demonstrated that low R a is attained when employing a lower a p in conjunction with higher V c .This configuration was the optimal parameter combination for achieving superior surface quality in the CO 2 coolant environment.In the case of the hybrid MQL + CO 2 approach, the 3D response surface analysis indicated that low R a is associated with specific combinations of f and a p .The optimal conditions for minimizing R a in this hybrid coolant environment were lower levels of f and a p .These results contribute valuable insights into the intricate relationships between cutting parameters and R a during end milling of Alloy 20 under different cooling conditions.The findings suggest that the optimization of machining processes can be achieved by tailoring cutting parameter combinations according to the specific coolant strategy employed, thereby enhancing the overall efficiency and quality of the machining operation, as shown in Figure 2.

Normal Probability Plot
Normal probability plots can be used to study the influences of factors.According to the normal probability plot, the points close to the line fitted to the middle group of points represent estimated factors with no significant effect on the response variable.In contrast, the points away from the straight line probably represent more important factors affecting the research objectives [25].Figure 3a represents the normal probability plot for MQL, Figure 3b represents the normal probability plot for CO2, and Figure 3c represents the normal probability plot for MQL + CO2.In the context of the experiments involving the end milling of Alloy 20 under various cooling conditions (MQL, CO2, and MQL + CO2), a critical aspect of the analysis was the examination of external studentized residuals of the normal percentage probability (Figure 3).As per the normal probability plot, the points that are close to the line fitted to the middle group of points represent the estimated factors that do not demonstrate any significant effect on the response variable.On the other hand, the points that appear far away from the straight line are likely to represent the 'real' factor effects on the surface integrity, tool wear, and chip formation.From Figure 3, it has been established that the main input factors A, B, and C and their factor interactions are quite far away from the straight line and are considered to be significant.The external residuals represent the differences between observed and predicted values, adjusted for the influence of individual data points.The assessment involved plotting these external residuals against the normal percentage probability, aiming to understand the distributional characteristics of the residuals.The findings from this analysis indicate a trend of almost linear behaviour for the MQL, CO2, and MQL + CO2 conditions.The nearly linear alignment of points on these plots suggests that the external residuals exhibit a distribution close to normal across the different coolant conditions.The relationship between external residuals and normal percentage probability is critical to validating regression model assumptions.The almost linear pattern observed across these plots for the MQL, CO2, and MQL + CO2 conditions supports the assumption of normality in the distribution of residuals.This is a key prerequisite for reliable statistical inferences derived from regression analyses.In summary, examining the external residuals with a normal percentage probability reveals an almost linear trend for the MQL, CO2, and MQL + CO2 conditions used in the experiments, as shown in Figure 3.This observation strengthens the statistical validity of the analyses, affirming the reliability of the regression models employed to investigate the end milling process of Alloy 20 under different cooling strategies.The adherence to normal distribution assumptions enhances the credibility of parameter estimates and the subsequent inferences drawn from the regression models.

Normal Probability Plot
Normal probability plots can be used to study the influences of factors.According to the normal probability plot, the points close to the line fitted to the middle group of points represent estimated factors with no significant effect on the response variable.In contrast, the points away from the straight line probably represent more important factors affecting the research objectives [25].Figure 3a represents the normal probability plot for MQL, Figure 3b represents the normal probability plot for CO 2 , and Figure 3c represents the normal probability plot for MQL + CO 2 .In the context of the experiments involving the end milling of Alloy 20 under various cooling conditions (MQL, CO 2 , and MQL + CO 2 ), a critical aspect of the analysis was the examination of external studentized residuals of the normal percentage probability (Figure 3).As per the normal probability plot, the points that are close to the line fitted to the middle group of points represent the estimated factors that do not demonstrate any significant effect on the response variable.On the other hand, the points that appear far away from the straight line are likely to represent the 'real' factor effects on the surface integrity, tool wear, and chip formation.From Figure 3, it has been established that the main input factors A, B, and C and their factor interactions are quite far away from the straight line and are considered to be significant.The external residuals represent the differences between observed and predicted values, adjusted for the influence of individual data points.The assessment involved plotting these external residuals against the normal percentage probability, aiming to understand the distributional characteristics of the residuals.The findings from this analysis indicate a trend of almost linear behaviour for the MQL, CO 2 , and MQL + CO 2 conditions.The nearly linear alignment of points on these plots suggests that the external residuals exhibit a distribution close to normal across the different coolant conditions.The relationship between external residuals and normal percentage probability is critical to validating regression model assumptions.The almost linear pattern observed across these plots for the MQL, CO 2 , and MQL + CO 2 conditions supports the assumption of normality in the distribution of residuals.This is a key prerequisite for reliable statistical inferences derived from regression analyses.In summary, examining the external residuals with a normal percentage probability reveals an almost linear trend for the MQL, CO 2 , and MQL + CO 2 conditions used in the experiments, as shown in Figure 3.This observation strengthens the statistical validity of the analyses, affirming the reliability of the regression models employed to investigate the end milling process of Alloy 20 under different cooling strategies.The adherence to normal distribution assumptions enhances the credibility of parameter estimates and the subsequent inferences drawn from the regression models.

Optimization
With the response surface methodology optimization, the recommended cutting conditions for Alloy 20 were obtained as follows: Vc of 44.3514 m/min, f of 0.04502 mm/rev, and ap at 0.435244 mm. Figure 4 indicates the optimal conditions obtained through RSM, and the following discussion is based on these obtained optimal conditions.Under these optimized parameters, the anticipated Ra values are 0.693654 for MQL, 0.665265 for CO2 cooling, and 0.620885 for the hybrid MQL + CO2 approach.These values signify the expected outcomes of surface roughness corresponding to the optimized cutting parameters for each respective coolant condition.The optimization process through RSM emphasizes the importance of tailoring cutting parameters to specific coolant strategies in order to achieve enhanced surface quality during the machining of Alloy 20.

Optimization
With the response surface methodology optimization, the recommended cutting conditions for Alloy 20 were obtained as follows: V c of 44.3514 m/min, f of 0.04502 mm/rev, and a p at 0.435244 mm. Figure 4 indicates the optimal conditions obtained through RSM, and the following discussion is based on these obtained optimal conditions.Under these optimized parameters, the anticipated R a values are 0.693654 for MQL, 0.665265 for CO 2 cooling, and 0.620885 for the hybrid MQL + CO 2 approach.These values signify the expected outcomes of surface roughness corresponding to the optimized cutting parameters for each respective coolant condition.The optimization process through RSM emphasizes the importance of tailoring cutting parameters to specific coolant strategies in order to achieve enhanced surface quality during the machining of Alloy 20.

Optimization
With the response surface methodology optimization, the recommended cutting conditions for Alloy 20 were obtained as follows: Vc of 44.3514 m/min, f of 0.04502 mm/rev, and ap at 0.435244 mm. Figure 4 indicates the optimal conditions obtained through RSM, and the following discussion is based on these obtained optimal conditions.Under these optimized parameters, the anticipated Ra values are 0.693654 for MQL, 0.665265 for CO2 cooling, and 0.620885 for the hybrid MQL + CO2 approach.These values signify the expected outcomes of surface roughness corresponding to the optimized cutting parameters for each respective coolant condition.The optimization process through RSM emphasizes the importance of tailoring cutting parameters to specific coolant strategies in order to achieve enhanced surface quality during the machining of Alloy 20.

Surface Integrity
SEM analysis was performed to determine the best of the optimal parametric levels that were obtained using the optimization methods.Microscopic surface defects caused during the machining process also impact the macroscopic parts' properties.The surface integrity is critical to functionality, longevity, and overall performance [26].And the surface integrity directly influences corrosion and fatigue resistance [27].MQL effectively reduces shear stresses caused by friction during machining [28].Cryogenic machining can effectively change the deformation mechanism of the machining process, which has a certain effect on the hardness and subsurface microstructure of the material [29].This section compares the surface integrity given by different cooling methods to determine the optimal cooling method.
Figure 5 shows a layer of the machined surface under optimal machining conditions.The surface topography analysis conducted under the optimum cutting conditions provides valuable insights into the quality and characteristics of the machined surfaces for each respective cooling environment.In the case of MQL, the surface topography reveals a comparatively rough texture.This suggests that despite the optimization efforts, the MQL cooling condition tends to result in surface irregularities and variations, potentially influenced by the specific lubrication and cooling characteristics associated with this method.Conversely, the surface topography under CO 2 cooling conditions exhibits a different characteristic, showcasing a pattern of scratches on the machined surface.This pattern implies that the CO 2 coolant environment, while optimized for other machining parameters, may introduce some scratching effects on the workpiece surface.Under the hybrid cooling condition of MQL + CO 2 , the surface topography appears to be notably smooth.This indicates that the combination of Minimum Quantity Lubrication and Carbon Dioxide as coolants, under the specified optimized cutting parameters, contributes to achieving a smoother surface finish compared to the other individual coolant environments.In summary, the surface topography analysis provides a nuanced understanding of the effects of different cooling environments on the machined surfaces under optimized cutting conditions.While MQL results in a relatively rough surface, CO 2 introduces scratches, and the combination of MQL + CO 2 yields a smoother surface finish.These observations underscore the influence of coolant strategies on the final surface characteristics of the machined Alloy 20 workpieces.
Upon conducting scanning electron microscopy (SEM) imaging for the machined samples made using the three coolants mentioned above, under the specified cutting parameters, distinct features on the machined surfaces became evident.Figure 6 shows the SEM of machined surfaces; V c = 44 m/min, f = 0.04 mm/rev, and a p = 0.43 mm.In the case of MQL, the SEM images reveal a surface characterized by scratches and damage.Scratches indicate potential abrasions or irregularities on the surface, possibly influenced by the lubrication and cooling dynamics associated with MQL.The damage observed suggests that the machining process under MQL conditions may be subject to some surface deterioration.Similarly, the SEM images for Carbon Dioxide (CO 2 ) cooling conditions exhibit surfaces marked by scratches and damage.This consistent observation of scratches implies that the CO 2 coolant environment, despite the optimized cutting parameters, introduces a scratching effect on the workpiece surface.The damage observed may also signify potential challenges associated with this cooling method in maintaining surface integrity.Under the hybrid cooling condition of MQL + CO 2 , the SEM images showcase a surface characterized by fine feed marks.These fine feed marks indicate a smoother surface texture than the scratches observed in the other conditions.This suggests that the combined effects of MQL + CO 2 as coolants under the specified optimized cutting parameters contribute to mitigating scratching and damage, resulting in a finer and more refined surface finish.In summary, SEM imaging provides a detailed visual representation of the machined surfaces under different coolant conditions.While the MQL and CO 2 conditions exhibit surfaces marked by scratches and damage, the hybrid MQL + CO 2 condition demonstrates a surface with fine feed marks, indicating a smoother and more refined outcome.These SEM observations further support the influence of coolant strategies on the surface characteristics of machined Alloy 20 workpieces, as shown in Figure 6.conducting scanning electron microscopy (SEM) imaging for the machined samples made using the three coolants mentioned above, under the specified cutting parameters, distinct features on the machined surfaces became evident.Figure 6 shows the SEM of machined surfaces; Vc = 44 m/min, f = 0.04 mm/rev, and ap = 0.43 mm.In the case of MQL, the SEM images reveal a surface characterized by scratches and damage.Scratches indicate potential abrasions or irregularities on the surface, possibly influenced by the lubrication and cooling dynamics associated with MQL.The damage observed suggests that the machining process under MQL conditions may be subject to some surface deterioration.Similarly, the SEM images for Carbon Dioxide (CO2) cooling conditions exhibit surfaces marked by scratches and damage.This consistent observation of scratches implies that the CO2 coolant environment, despite the optimized cutting parameters, introduces a scratching effect on the workpiece surface.The damage observed may also signify potential challenges associated with this cooling method in maintaining surface integrity.Under the hybrid cooling condition of MQL + CO2, the SEM images showcase a surface characterized by fine feed marks.These fine feed marks indicate a smoother surface texture than the scratches observed in the other conditions.This suggests that the combined effects of MQL + CO2 as coolants under the specified optimized cutting parameters contribute to mitigating scratching and damage, resulting in a finer and more refined surface finish.In summary, SEM imaging provides a detailed visual representation of the machined surfaces under different coolant conditions.While the MQL and CO2 conditions exhibit surfaces marked by scratches and damage, the hybrid MQL + CO2 condition demonstrates a surface with fine feed marks, indicating a smoother and more refined outcome.These SEM observations further support the influence of coolant strategies on the surface characteristics of machined Alloy 20 workpieces, as shown in Figure 6.

Chip Formation and Cutting Tool Wear
During the cutting process, the cutting speed and cooling method greatly impact tool wear.The increase in temperature in the cutting area of the tool causes the main cutting edge to move and deform, thus increasing tool wear [30].Chip formation is also affected by the machining conditions, and chip formation can damage the face of the tool, which also increases tool wear.Lubrication and cooling are effective ways to reduce tool wear [31]; lubrication methods will form a lubrication film on the tool face, which greatly protects the tool; in addition, CO2 cooling can effectively penetrate the chip area and introduce a good cooling effect.This section explores the practical impacts of new cooling methods on chip formation and tool wear.Figure 7 shows the chip morphology; Vc = 44 m/min, f = 0.04 mm/rev, and ap = 0.43 mm.Examining chip formation (Figure 7) during machining processes under various cooling conditions provides essential insights into the material removal mechanisms and overall cutting performance.Distinct chip formation characteristics were observed under the specified cooling conditions (MQL, CO2, and hybrid CO2 + MQL).Under the MQL cooling condition, chip formation was comparatively discontinuous.This suggests that the chips produced during machining under MQL are not consistently continuous, but exhibit breaks or interruptions.The discontinuous nature of chip formation under the MQL condition may be attributed to the specific lubrication

Chip Formation and Cutting Tool Wear
During the cutting process, the cutting speed and cooling method greatly impact tool wear.The increase in temperature in the cutting area of the tool causes the main cutting edge to move and deform, thus increasing tool wear [30].Chip formation is also affected by the machining conditions, and chip formation can damage the face of the tool, which also increases tool wear.Lubrication and cooling are effective ways to reduce tool wear [31]; lubrication methods will form a lubrication film on the tool face, which greatly protects the tool; in addition, CO 2 cooling can effectively penetrate the chip area and introduce a good cooling effect.This section explores the practical impacts of new cooling methods on chip formation and tool wear.Figure 7 shows the chip morphology; V c = 44 m/min, f = 0.04 mm/rev, and a p = 0.43 mm.Examining chip formation (Figure 7) during machining processes under various cooling conditions provides essential insights into the material removal mechanisms and overall cutting performance.Distinct chip formation characteristics were observed under the specified cooling conditions (MQL, CO 2 , and hybrid CO 2 + MQL).Under the MQL cooling condition, chip formation was comparatively discontinuous.This suggests that the chips produced during machining under MQL are not consistently continuous, but exhibit breaks or interruptions.The discontinuous of chip formation under the MQL condition may be attributed to the specific lubrication and cooling dynamics associated with this method, influencing the material flow and chip morphology.In the case of the Carbon Dioxide (CO 2 ) cooling condition, chip formation was observed to be greater and discontinuous.The chips generated under CO 2 are larger than those of MQL and exhibit similar continuity interruptions.The bigger and discontinuous nature of chips under the CO 2 condition may indicate specific thermal and mechanical interactions between the coolant and the workpiece material, leading to variations in chip morphology.Contrastingly, under the hybrid cooling condition of MQL + CO 2 , chip formation was noted to be close and continuous.This suggests that the chips produced under the hybrid CO 2 + MQL condition are closely connected and exhibit a more continuous flow.The close and continuous chip formation in the hybrid condition may result from the combined effects of Minimum Quantity Lubrication and Carbon Dioxide, providing a balance between lubrication, cooling, and chip evacuation, thereby influencing the overall chip morphology.The observed chip formation characteristics vary across the different cooling conditions.MQL is associated with comparatively discontinuous chips; CO 2 produces bigger and discontinuous chips; and the hybrid MQL + CO 2 condition results in close and continuous chip formation.These findings offer valuable insights into the complex interplay between cutting parameters, coolant strategies, and chip morphology, contributing to a comprehensive understanding of the machining processes under different cooling environments [32].Figure 8 shows the rake wear; Vc = 44 m/min, f = 0.04 mm/rev, and ap = 0.43 mm under the optimal machining conditions.In the examination (Figure 8) of the cutting conditions for the specified tool under various coolant environments, distinct tool wear patterns were observed.Under the Minimum Quantity Lubrication (MQL) cooling condition, the tool exhibited nose degradation and peeling signs.The occurrence of nose degradation suggests that the cutting edge of the tool's nose, which plays a crucial role in initiating the cutting process, experienced wear and deterioration.Also, peeling indicates that the tool material's layers are being separated or peeled away.These wear characteristics under the MQL condition may be attributed to the specific lubrication and cooling properties associated with MQL, potentially leading to increased friction and wear on the tool's cutting surfaces.Conversely, the tool chipped under the Carbon Dioxide (CO2) cooling condition.Chipping forms small, localized fractures or chips on the tool's cutting edges.The presence of chipping under the CO2 condition suggests that the tool may have experienced excessive localized force or stress during machining, resulting in the formation of chips on the tool's edges.The cooling dynamics of CO2 may influence the heat dissipation and chip formation processes, contributing to the observed chipping.Under the hybrid cooling condition of MQL + CO2, the tool exhibited signs of chipping similar to those observed in the CO2 condition.Chipping in the CO2 and hybrid CO2 + MQL conditions suggests that certain machining forces or conditions common to both coolant strategies contribute to this specific wear pattern on the tool.Analysing tool wear patterns under different coolant conditions reveals distinct characteristics.MQL is associated with nose degradation and peeling, while CO2 and the hybrid MQL + CO2 condition exhibit signs of chipping on the tool's cutting edges.These wear patterns provide valuable insights into the interac- Figure 8 shows the rake wear; V c = 44 m/min, f = 0.04 mm/rev, and a p = 0.43 mm under the optimal machining conditions.In the examination (Figure 8) of the cutting conditions for the specified tool under various coolant environments, distinct tool wear patterns were observed.Under the Minimum Quantity Lubrication (MQL) cooling condition, the tool exhibited nose degradation and peeling signs.The occurrence of nose degradation suggests that the cutting edge of the tool's nose, which plays a crucial role in initiating the cutting process, experienced wear and deterioration.Also, peeling indicates that the tool material's layers are being separated or peeled away.These wear characteristics under the MQL condition may be attributed to the specific lubrication and cooling properties associated with MQL, potentially leading to increased friction and wear on the tool's cutting surfaces.Conversely, the tool chipped under the Carbon Dioxide (CO 2 ) cooling condition.Chipping forms small, localized fractures or chips on the tool's cutting edges.The presence of chipping under the CO 2 condition suggests that the tool may have experienced excessive localized force or stress during machining, resulting in the formation of chips on the tool's edges.The cooling dynamics of CO 2 may influence the heat dissipation and chip formation processes, contributing to the observed chipping.Under the hybrid cooling condition of MQL + CO 2 , the tool exhibited signs of chipping similar to those observed in the CO 2 condition.Chipping in the CO 2 and hybrid CO 2 + MQL conditions suggests that certain machining forces or conditions common to both coolant strategies contribute to this specific wear pattern on the tool.Analysing tool wear patterns under different coolant conditions reveals distinct characteristics.MQL is associated with nose degradation and peeling, while CO 2 and the hybrid MQL + CO 2 condition exhibit signs of chipping on the tool's cutting edges.These wear patterns provide valuable insights into interactions between cutting parameters, tool materials, and coolant strategies, informing the optimization of machining processes for improved tool performance and longevity.
Chipping forms small, localized fractures or chips on the tool's cutting edges.The presence of chipping under the CO2 condition suggests that the tool may have experienced excessive localized force or stress during machining, resulting in the formation of chips on the tool's edges.The cooling dynamics of CO2 may influence the heat dissipation and chip formation processes, contributing to the observed chipping.Under the hybrid cooling condition of MQL + CO2, the tool exhibited signs of chipping similar to those observed in the CO2 condition.Chipping in the CO2 and hybrid CO2 + MQL conditions suggests that certain machining forces or conditions common to both coolant strategies contribute to this specific wear pattern on the tool.Analysing tool wear patterns under different coolant conditions reveals distinct characteristics.MQL is associated with nose degradation and peeling, while CO2 and the hybrid MQL + CO2 condition exhibit signs of chipping on the tool's cutting edges.These wear patterns provide valuable insights into the interactions between cutting parameters, tool materials, and coolant strategies, informing the optimization of machining processes for improved tool performance and longevity.

Conclusions
In conclusion, the comprehensive investigation into the machining processes of Alloy 20 under various cooling conditions-Minimum Quantity Lubrication (MQL), Carbon Dioxide (CO 2 ), and the hybrid MQL + CO 2 -has provided valuable insights into the intricate relationships between cutting parameters, surface characteristics, tool wear patterns, and chip formation.The key findings are summarized as follows: 1.
Based on the RSM outcomes, the optimal parametric settings obtained are V c = 44 m/min, f = 0.04 mm/rev, and a p = 0.43 mm, for which the R a value for MQL is 0.665 µm, the R a value for CO 2 is 0.693 µm, and the R a value for MQL + CO 2 is 0.620 µm.

2.
Surface roughness outcomes varied under different cooling conditions, with MQL exhibiting a relatively rough surface, CO 2 showing scratches, and the hybrid MQL + CO 2 resulting in a smoother finish under the optimized cutting parameters.

3.
Tool wear patterns were distinctive for each coolant condition.MQL was associated with nose degradation and peeling, while CO 2 and the hybrid condition displayed signs of chipping, indicating the influence of coolant strategies on tool performance.4.
Chip formation characteristics varied significantly.MQL resulted in comparatively discontinuous chips, CO 2 produced bigger and discontinuous chips, and the hybrid MQL + CO 2 condition yielded close and continuous chip formation.These observations underscore the diverse effects of coolant strategies on material removal processes.5.
Scanning electron microscopy (SEM) images revealed surface features corresponding to the coolant conditions.The MQL and CO 2 conditions showed scratches and damage, while the hybrid condition demonstrated fine feed marks, indicating a smoother surface.6.
The application of response surface methodology (RSM) identified optimized cutting conditions, providing specific parameter values for cutting speed, feed rate, and depth

Figure 1 .
Figure 1.Schematic view of the experimental conditions.

Figure 1 .
Figure 1.Schematic view of the experimental conditions.

Figure 4 .
Figure 4. Optimum conditions obtained from RSM.Figure 4. Optimum conditions obtained from RSM.

Figure 4 .
Figure 4. Optimum conditions obtained from RSM.Figure 4. Optimum conditions obtained from RSM.

Table 3 .
RSM input factors and levels.

Table 4 .
Input parameters and surface roughness.

Table 6 .
ANOVA response for CO 2 condition.