The workpieces in this experiment are tungsten–nickel–iron alloy W95Ni3.5Fe1.5 and copper monolithic bullets whose dimensions are ɸ13.1 mm in diameter and 25 mm in length. The workpiece used is described in Supplementary Figures S2A, B. The physical and chemical properties of the tungsten–nickel–iron alloy W95Ni3.5Fe1.5 and copper monolithic bullets are listed in Supplementary Tables S1, S2, respectively.

Hardinge designed and built series turning centers for making bullet profiles close to tolerance limits, as indicated in Supplementary Figures S2C–F. The computer numerical control (CNC) lathe machine in the Central Institute of Tool Design (CITD), MSME Tool Room, Government of India, Hyderabad, was used to machine the bullet profiles. The machine specifications are highlighted in Supplementary Table S3. The A2-5 spindle nose, with a horsepower of 15 kW and high spindle speeds, allowed wide trial variations before finalizing the factor variables. The machining was carried out using an A4SM short-projection Kennametal tool, which is depicted in Supplementary Figures S2G–I. The insert used for machining is a titanium aluminum nitride-coated tool, as bullet profile-making requires high hardness and a stable tool holder for the given dimension of the workpiece. The design data of the workpiece for the bullet module are depicted in CAD, and drawing images are depicted in Supplementary Figures S2J, K. The bullet profile machined for the WNF and CM bullets is depicted in Supplementary Figures S2L, M.

Dry machining is classified as a clean manufacturing technique. In dry machining, the components used for material cutting, the tool, and the parameters are evaluated carefully before the operation begins (Sastry et al., 2019a). As dry machining involves high friction, a coated tool makes a vast difference in curtailing friction (Sastry et al., 2019b). Although dry machining is classified as green and clean-environment machining, its significant disadvantage lies in the tangling of chips generated in the tooltip, affecting the cutting zone area and creating a poor surface finish (Sastry et al., 2020a) and excess temperature, which induces wear (Praveen Raj Navukkarasan et al., 2021). Considering these two aspects, the cutting process and its associated parameters should be optimized for the specific machining and workpiece material conditions.

Taguchi’s design technique was adopted to condense the number of required iterations. The orthogonal array set of Taguchi is widely adopted for many manufacturing/machining problems (Sastry et al., 2019a), as it efficiently classifies and identifies the factors and responses as independent planes (Sastry et al., 2019b). Furthermore, reducing the number of experiments reduces the cost and time of analyzing all the experiment runs. With the addition of signal-to-noise (S/N) ratio, the individual traits of the factors are well established in this design (Sastry et al., 2020a). For machining bullets for defense applications, the responses are cutting temperature (T_c), surface roughness (R_a), and hardness (VHN). The nose radius and depth are kept constant based on the machining profile. The factors and responses are showcased in Supplementary Table S4. The orthogonal array with factors and responses for dry machining of WNF and CM bullets is tabulated in Supplementary Table S5.

Supplementary Table S5 shows that WNF material’s temperature and surface roughness decrease and hardness increases in each of the experimental conditions compared to CM machining conditions. To ensure a common vector space that will bring in all the responses and factors in one vector plane is obtained, a multi-criteria method is used to obtain conditions close to ideal for machining the bullet profile.

Step 1. The TOPSIS method is considered the ideal mechanism for appropriately culling the alternatives as it works toward a normalized value. Simo’s weighting procedure is used to allocate the rank of each output response, tabulated in Supplementary Table S6.

Supplementary Tables S7, S8 use the following equation to develop the normalized performance matrix (r_ij): r i j = X i j ∑ i = 1 m X i j 2 i = 1 , 2 , … … 27 ;   j = 1 , 2 , … … 5 , where i = number of alternatives (experimental runs), j = number of criteria (output responses), and x_ij = normalized value of the ith experimental run associated with the jth output response.

Step 2. The product of the normalized value merges the weighted normalized matrix (ϑij) into the weighted values:

The weighted matrixes are highlighted in Supplementary Tables S7, S8 for dry machining of WNF and CM tubes.

Step 3. Every option that is an ideal alternative to the best alternative performance ( S + ) and the worst alternative performance (S ⁻) was ascertained. If the jth criterion has a decisive outcome,

where S ⁺ delineates a decisive (positive) ideal solution, tabulated in Supplementary Table S9.

Step 4. In this progression, the execution of the criteria has been estimated as the best elective separation (D⁺ _ij) from the S ⁺ solutions and the worst elective separation (D⁻ _ij) from the S ⁻ values. The D⁺ _ij and D⁻ _ij values are resolved utilizing the accompanying condition. Supplementary Table S11 shows the attainment of each alternative under the ideal and unfavorable conditions in dry machining conditions for CM and WNF.

where i = 1, 2, 3 ….27.

Step 5. The closeness coefficient (C_i) values are obtained for each alternative using the accompanying equation

The ideal alternative is conscripted according to the preference rank-ordered by the C_i value, which is very important to the ideal solution, as highlighted in Supplementary Table S11. The respective input values are tabulated in Supplementary Table S12. After the machining operation, the close-to-ideal solution is evaluated. Supplementary Table S12 is further sectioned based on the characterization requirement by using the wire-EDM facility for microstructure, surface morphology, chip study, and residual stress analyses. The samples are cleaned, polished, and etched to clearly depict the surface after machining in dry conditions to ensure no undue chips are present during inspection. The tool wear was analyzed to understand the effect of the machining conditions. X-ray diffraction (XRD) using a central XRD facility was done to understand the compressive stress on the machined surface for the CM and WNF material.

The Taguchi method was adopted for the repetitive processes with a smaller, better signal-to-noise ratio. The graphic and its respective values are tabulated in Tables 1, 2.

Analysis results of speed and feed concerning cutting temperature, surface roughness, and microhardness for dry machining conditions at a significance level of 0.05 (confidence level of 95%) are tabulated in Tables 3, 4 for CM and WNF, respectively. The rate commitment of each factor determined from analysis of variance (ANOVA) was utilized as the measure for determining the impact of each factor.

From Tables 1, 2, applying the Taguchi method, the smaller and more significant the signal-to-noise ratio, the better. For ideal cutting temperature and microhardness, a speed of 2,500 rpm and a feed of 0.059 mm/min are the ideal cutting parameters for dry machining conditions. A speed of 2,000 rpm and a feed of 0.055 mm/min and a speed of 2,500 rpm and a feed of 0.059 mm/min are the ideal cutting parameters for surface roughness for CM and WNF, respectively, with significance given toward a smaller signal-to-noise ratio. From ANOVA (Tables 3, 4), it is found that feed plays a prominent role in determining the cutting temperature in dry machining. Meanwhile, speed plays an important role in determining surface roughness and microhardness.

From the graphical data represented in Figure 1, the WNF shows 3.01%–27.95% lower machining temperatures, 24.88%–61.85% increased surface roughness, and 9.45%–34% increased microhardness values than the CM material, as indicated in Supplementary Table S13 (Sastry et al., 2019a).

The temperature is attributed to the material’s density factor and softness (Sastry et al., 2019a). The WNF bullet profile density is lower than the CM bullet, which aids in the machining condition with the presence of a lower number of inclusions (Chandrasekhara Sastry et al., 2021; Praveen Raj Navukkarasan et al., 2021; Bairapudi et al., 2022; Pradeep et al., 2022; Su et al., 2022; Sundeep et al., 2022). Additionally, the minimal presence of sulfur, a consequence of delicate grain structures, and the uniform secondary distribution of particles aid in machinability at lower temperatures for WNF profiles. With a high presence, copper material increases temperatures drastically due to the attenuation in cutting forces experienced during machining (Sastry et al., 2020a). The addition of a small percentage of tin compensates for this increase, but a small addition would not form the β′ phase as that would increase hardness, leading to the formation of a duplex and thereby causing a decrease in cutting temperature (Sastry et al., 2020a; Sastry et al., 2020b). An increase in cutting temperature, as with an increase in speed values, has an overall effect on the increased surface roughness of the machined bullet profile, as is witnessed in the case of the CM bullet profile, which is a determinant factor (Evans and Bryan, 1999; Sastry et al., 2020a). The cutting temperature in the machining zone is essential as it directly affects surface roughness and microhardness properties (Sastry et al., 2019a; Sastry et al., 2019b; Rajamanickam et al., 2020). Because copper is soft and has several stress inducers, it increases the temperature during machining, causing drastic material surface changes, as depicted in the morphology section. The presence of stress inducers and many inclusions leads to the presence of coarse grains that substantially increase the temperature. This temperature increase has a profound effect on the machining zone, as the tool, which is a rigid material, will impart a higher cutting force on the softer copper material, thereby increasing the tensile residual stress in the material (Sastry et al., 2019b). The CM bullet profile has a lower microhardness value owing to its inherent softness, which is a significant drawback compared to the WNF material. With further machining at higher speeds, high tensile stresses are applied due to the augmented temperature of machining and disoriented surge in surface roughness (waviness pattern); a decrease in the microhardness value is observed, as indicated in the CM bullet profile (Sastry et al., 2020a). A detailed analysis of the tool wear and workpiece surface morphology is required to understand the ramifications of the responses to the bullet machining factors.

A temperature increase in the machining zone when making the bullet profile significantly affects the cutting tool (Sastry et al., 2019b; Sastry et al., 2020a). Cutting temperature increases with increased cutting speed and feed and affects the workpiece material and the tool.

The tool life is diminished by micro-voids in the surface of the CM alloy, which can be seen during the machining cycle. The zinc combines with sulfur compounds to form zinc sulfide inclusions. These inclusions cause the formation of micro-holes in the surface. The presence of tin and nickel increases the hardness of the surface. However, due to its inherent softness, forming a built-up edge is unavoidable (Sastry et al., 2019b), causing flank wear, which increased by 47.53% in CM compared to WNF, as indicated in Supplementary Table S14. Substantial flank wear is witnessed in the case of copper alloy, as indicated in Figure 2, and a waviness pattern develops in and around the region of the machining zone. Generally, crater wear conditions are ascertained due to chemical attack or interaction during the machining operation. Crater wear is not witnessed when making WNF bullets. However, in the case of CM tubes, a significant amount of deterioration on the surface is witnessed in the tool area around the crater regions indicated in Figure 2B (Sastry et al., 2019a). The chemical reaction between sulfides and inclusions induces this. The crater and flank wear is also attributed to the increase in abrasion, as the CM material’s softness causes attenuation in surface roughness and an increase in cutting force due to the presence of inclusions. The nickel in the WNF acts as a self-lubricant, which causes a decrease in temperature during bullet making (Sastry et al., 2019b). The crater wear component is abated by 24.89% in the WNF compared to the CM owing to its lower cutting temperatures and nickel acting as a lubricant (Sastry et al., 2020a).

During bullet making, the chip slides over the tool-rake surface. The quality of the surface is important because an unsmooth surface causes friction in the firing nozzle, which nullifies the attributes of an ideal bullet profile (Chandrasekhara Sastry et al., 2021; Praveen Raj Navukkarasan et al., 2021; Bairapudi et al., 2022; Pradeep et al., 2022; Sundeep et al., 2022). A chip may be formed along the surface curls and exits along the rake face. The workpiece residual stress in the sub-surface plays a vital role in determining the solid-phase removal during bullet profile-making (Su et al., 2022). The friction coefficient witnessed in the WNF is higher than that in the CM material, owing to its high hardness and self-lubricating properties. Because less heat is generated at the tool–chip interface, fewer craters and micro-holes are observed in Figure 3 for WNF.

With an increase in hardness value and temperature ascertained during the making of the bullet profile in the area of the tool–chip–workpiece interface, stress is induced on the sub-layers of the workpiece. This stress is in the form of tensile/compressive factors Sastry et al., 2020b; Jhansi et al., 2023; Umadevi et al., 2023. With an increase in temperature owing to the hardness of the workpiece, the tool wear increases, risking failure during the machining cycle (Navukkarasan et al., 2020). The integrity of the surface is also affected by the effect of localized temperature, which augments the presence of residual tensile stress (Gopinath et al., 2021; Praveen Raj Navukkarasan et al., 2021). The amount of residual stress must be calculated, as it determines the surface integrity of surface and sub-surface characteristics that determine the application of the bullet (Chandrasekhara Sastry et al., 2021; Sundeep et al., 2022). For bullet profiles designed to pierce armor shields, concrete blocks, and other objects, it is essential to assess the residual factor on the surface of the workpiece. A central XRD facility was used, and a simultaneous sin²ψ method was used to calculate the residual stress factor in the sub-surface of the workpiece, as indicated in Supplementary Table S15 (Figure 4).

Supplementary Table S15 shows a compressive residual stress attenuation of 38.23% in the WNF bullet profile compared to the CM material. From the slope of the curve shown in Figure 4 and the calculation of the same using the sin²ψ method, it is observed that the induced stress is compressive (Praveen Raj Navukkarasan et al., 2021). Additionally, the increase in width of the XRD plot indicates that the stress factor has increased in the compressive factor in the case of the WNF bullet compared to CM material (Chandrasekhara Sastry et al., 2021). The tool life is increased as tensile stress is reduced, as indicated in Figure 2, as the temperature of machining is lower in the WNF than in the CM, causing less tensile stress in the machining zone. Furthermore, the nickel that is the primary alloying element in the tungsten alloy has high hardness and, aided by the presence of chromium, leads to a fine grain size in the machining region. The average grain size of WNF is 53 µm compared to CM grains at 92 μm, which aids in pinning the austenite grain boundaries observed when making tungsten alloy (Bairapudi et al., 2022; Pradeep et al., 2022; Sundeep et al., 2022). Fine grain will induce higher microhardness and thereby increase the factor of stress (compressive factor), as it will not allow load or applied stress from an external part to go through subsequent layers of the bullet profile. With the decreased hardness of the CM material, owing to its soft nature and coarse structure, the compressive factor is minimal, and this causes the strength of the bullet profile to be susceptible to substantial friction in real time. The minimal peak width indicates a higher dislocation density owing to a higher tensile residual stress factor and an increase in microstrain in the material due to the machining cycle (Evans and Bryan, 1999; Su et al., 2022). When making bullet profiles or test pieces for piercing, high impact resistance, secondary aging/heat treatment conditions, or alternative grades of copper should be used to induce the characteristics required for the operation.

The increase in gun culture, such as through unlicensed arms sales across the globe, hinders public and premises’ security. This opens a wide range of research on the development of sophisticated arms that are easy to handle, have less mass, have high thrust velocity, and have high bullet penetration (Jena et al., 2019). This motivated us to analyze the performance of the two fabricated pistol bullets in terms of penetration into aluminum targets of different thicknesses. The bullet dynamics at the contact point of the aluminum target plate are analyzed using finite element analysis (FEM). The study considered the size, velocity, and angular velocity of the fabricated CM and WNF bullets. The angle of impact was 0° to obtain maximum velocity and achieve maximum penetration through the target. The FEM analysis considers the detailed geometry and a relevant CAD model of a bullet with dimensions of 25 mm × 13.1 mm, as shown in Supplementary Figure S2K, for the CM and WNF bullets. The two aluminum targets are 100 × 100 × 3 mm and 100 × 100 × 9 mm cuboids with a density of 2.7 g/cc, Young’s modulus of 70 GPa, and Poisson’s ratio of 0.33, as shown in Supplementary Table S16. The properties of the CM and WNF bullet are mentioned in Tables 1, 2. The masses of the bullets were 119.1 g and 146.5 g, respectively, for the CM and WNF bullets. The non-linear dynamic ballistic impact analysis was performed on Abaqus software.

The target is fixed in Lancaster (U₁ = U₂ = U₃ = R₁ = R₂ = R₃ = 0), and the bullet’s velocity has assigned a muzzle velocity of 350 m/s in all the cases with a period of 100 µs. The analyses of both the bullets are instituted from the contact point of the target as shown in Figures 5A, G and Figures 5D, I for the CM and WNF bullets to nullify the deceleration of air friction. The 2D quad and 3D hexahedral meshing are used for the bullet and the aluminum target plates, respectively. Although free mesh increases the number of components and computational cost, the differences in constraints between models that use a 2D triangle or 3D tetrahedral elements are proportionally more minor. As stated above, using 2D quad or 3D hexahedral elements can help reduce element use, solution precision, and computational time (Kumar et al., 2017). Figures 5B, E, J show the penetration point of both CM and WNF bullets through the 3-mm and 9-mm aluminum targets. Both the bullets penetrated through the 3-mm aluminum target, as seen in Figures 5G, E, with a difference in time as indicated during penetration. The CM bullet penetrated the 3-mm aluminum target at 75 µs and traveled a distance of 27.58 mm from the initial point. A penetration time of 75 µs with a low traveling distance of 24.33 mm is observed in the WNF bullet. Because both bullets penetrated the 3-mm targets, the thickness of the target was increased to 9 mm to observe the failure. Figures 5H, J show the impact analysis of both bullets through the 9-mm aluminum targets. From Figure 5H, we can observe the penetration failure of the CM bullet, which deformed the target plate of 28.73 mm without completing the path of the target. The WNF bullet has penetrated through the 9-mm target with a penetration time of 50 µs and a traveled distance of 16.33 mm through the target, as shown in Figures 5K. Figures 5C, F show the final position of the CM and WNF bullets through the 3-mm aluminum target, and Figure 5K shows the final position of the WNF bullet at 100 µs. The CM and WNF bullets traveled a distance of 30.21 mm and 29.42 mm, respectively, through the 3-mm target and 28.73 mm and 31.01 mm, respectively, in the 9-mm aluminum target. All the details regarding the material, size, and properties considered for the analysis are tabulated in Table 5. Based on the above simulation, the optimum results were achieved from the WNF bullet over conventional copper bullets, which can penetrate a 9-mm aluminum target. Designing a short-range bullet with this novel WNF material can improve the penetration capacity. A real-time ballistic impact analysis can be performed with these novel bullet materials to further study the firing range of these bullets.