Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 913 ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT ORIGINAL RESEARCH ARTICLE OPTIMIZATION OF ARC WELDING PARAMETRIC INFLUENCE ON MECHANICAL PROPERTIES OF DISSIMILAR METALS B. J. Olorunfemi1, B. S. Adeleye1, K. A. Bello1 and O. T. Oginni2 1Department of Mechanical Engineering, Federal University Oye-Ekiti, Nigeria. 2Department of Mechanical Engineering, Bamidele Olumilua University of Education, Science and Technology, Ikere- Ekiti, Ekiti State, Nigeria. *Corresponding author's email address: oginni.olarewaju@bouesti.edu.ng ARTICLE INFORMATION ABSTRACT Welding dissimilar metals require technical expertise to achieve moderate cost, quantity, and quality, but selecting the right parameters is challenging due to various operating conditions. The paper optimized welding process parameters for two dissimilar metals, INCONEL 625 and GL E360, focusing on mechanical properties like tensile strength and hardness. The welding process parameters were optimized using Gas Metal Arc Welding power sources, Flux Cored Wire Electrode (FCWE), design experts, and response surface methodology, and tensile strength and hardness tests were conducted. At the anticipated optimal process welding parameters of 52.86 m/s welding speed, 5.28 m/min welding feed rate, and 23.16 volts, three confirmation experiments were carried out. The study revealed that the tensile strength and hardness of the welding process significantly influenced response variables, ranging from 380 MPa to 500 MPa. The most noticeable effect was observed at a welding speed of 52 m/s, a feed rate of 5.6 m/min, and a voltage of 26 V. The empirical model's tensile strength and hardness were validated using experimental results, and the software predicted 53 welding speed, 5 welding feed rate and 23 voltages. The welding process parameters significantly impacted tensile strength and hardness, while the welding feed rate parameter had the least impact on both. Submitted: 04 May, 2023 Revised: 12 June, 2024 Accepted: 20 June, 2024 Keywords: Feed rate Hardness Optimal process Tensile strength Welding parameter © 2024 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved. 1.0 Introduction Joining different materials is acknowledged as a challenge for the development of new structural components within the production industry (Stoll and Benner, 2021). The criterion for welding dissimilar components requires suitable joining expertise (Zhang-Yang et al., 2020). Fusion welding is a commonly used method for joining dissimilar steels (Zhang et al., 2020; Cooke et al., 2019). Optimizing weld parameters for such fusion weld joints will help in achieving a sound weld joint free of weld defects and improve productivity (Li et al., 2021).Metal joining is the process of joining two metal parts either temporarily or permanently with or without the application of heat and pressure by welding, soldering, brazing, riveting, adhesive bonding, assembling with bolts, and seaming (Dark et al., 2021). Welding is the process of joining similar and dissimilar metals or other materials by applying heat, pressure, and filler materials. In the fusion welding process, coalescence is done by melting two parts to be joined and applying filler metals to the welded joints to provide strength. The fusion welding process is classified as the arc welding process, the resistance welding process, the radiant welding process, and the thermoelectric welding process. Manufacturers are focused on joining dissimilar materials to reduce manufacturing costs and build lightweight components. Steel structures are lighter and more cost- effective when their structural components are made of different steels (Luo et al., 2022). Chemical, petrochemical, nuclear, power generation, and other industries use a variety of dissimilar steel joints (Johnson and Murugen, 2020; Kumar et al., 2023). Joining dissimilar steels is typically more difficult than joining similar steels (Beygi et al., 2023; Sivasubramani et al., 2021). This is caused by changes in chemical composition and thermal expansion coefficients. Tungsten inert gas welding (TIG) (Raju and Kumar, 2022), is an arc welding AZOJETE December 2024. Vol.20(4):913-925 Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria. Print ISSN: 1596-2490, Electronic ISSN: 2545-5818 www.azojete.com.ng mailto:oginni.olarewaju@bouesti.edu.ng mailto:oginni.olarewaju@bouesti.edu.ng http://www.azojete.com.ng/ Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 914 process that provides outstanding welding with a coalescence of heat generated through an electric arc between a tungsten electrode and the steel (Assefa et al., 2022). There are five basic welding joint types commonly used in the industry, including butt joint, tee joint, corner joint, lap joint, and edge joint welding, as shown in Figure 1 (Buffa et al., 2022). Lap joints are commonly used for sheet metal, as depicted in Figures 1 and 2. Gas Metal Arc Welding (GMAW) is a semi-automatic or automatic arc welding process in which a continuous and consumable wire electrode and a shielding gas are fed through a welding gun (Khrais et al., 2023). It is developed for welding aluminium and other non-ferrous materials (Devanathan et al., 2022). The various welding processes are shown in Figure 3. Welding is commonly used in the areas of pipe welding and joints, automotive production and maintenance, manufacturing, shipbuilding, construction, railroad tracks, and underwater welding, both for ferrous and non-ferrous metals (Bossle et al., 2023). Friction stir lap welding (FSLW) involves the joining of alloys in a solid-state manner, which can mitigate the challenges due to melting and solidification (Bossle et al., 2023; Satputaley et al., 2021; Patel et al., 2020; Mou et al., 2021; Tesfaye, 2023; Kannan et al., 2019; Ramaden and Boghdadi, 2020). The process of GMAW requires a welding gun, a source of electric power supply, an electrode wire feed unit, and a source of shielding gas (Alagarsamy and Kumar, 2019). The advantages of gas metal arc welding include no flux. Applications of gas metal arc welding are found in semi-automated or automated industrial applications, commercially available metals, deep groove welding of plates and castings, and welding light gauge metals. Figure 1: Lap welding joints Figure 2: Fillet weld Figure 3: Various types of welding process (Buffa et al., 2022) The importance of welding dissimilar metals for operation cost reduction, quality, and productivity in the welding process parameters had been studied, but it did not find out the effect of these parameters on the mechanical properties of dissimilar metal wed joints. It is necessary to determine the right GMAW parameters and processes for dissimilar metals involving high-strength steel (Inconel 625 plate) and nickel-based alloys (GL E36 steel) and their influence on the mechanical properties to eliminate the risk associated with failure and reliability of materials during their service life. Hence, the joining of these dissimilar steels finds a lot of http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 915 applications in fabrication industries (Madhavadas et al., 2022; Arunkumar et al., 2022; Ren et al., 2022). The present study uses an optimization application approach technique to investigate the influence of welding parameters on tensile strength and hardness, enhancing the quality of the weld joints of dissimilar metals, comprising Inconel 625 and Gl E36 steels, as a driver to guide the stakeholders in the manufacturing industry. 2. Materials and Methods The materials used for carrying out the study and their specifications are: 3 mm thick Inconel 625 plate, 3 mm thick GL E36 steel plate, 5mm electrode, and a gas metal arc welding machine. The choice of the materials was made due to variations in the condition of service and specifications of the materials available, such as the size of the samples, weight, cost, availability, durability, and strength of the materials. It has good toughness properties, higher strength, strong corrosion resistance, processing properties, and welding properties. 2.1 Experimental setup The GMAW power voltage 230 V single-phase flux wire welding machine was used for making buttweld joints. The mechanized torch movement ensured precise control over the weld speed, while voltage and wire feed rate were set at the GMAW power source to one decimal place precision. Flux-cored wire electrodes of diameter 3 mm suitable for this dissimilar welding were used as filler material. The 3 mm Inconel 625 plate was welded to 3mm GL E36 steel using GMAW. Table 1 presents the chemical composition of the Inconel 625 and GL E36 steel plates. Figure 4 shows the two- and three-dimensional sectional views and lap joint configuration with plate dimensions overlapped for FSLW. The horizontal dashed and vertical dotted lines in the two-dimensional sectional view are the locations for the hardness measurement. Figures 5 and 6 are the sample microstructures. The welded specimens were transversely cut using a diamond-plated blade, ground, and polished for microstructure evaluation. The hardness distributions were measured with a load of 500 g and at a regular gap of 0.3 mm along the dashed lines in the Y-direction. The hardness measurements were determined along the dotted line in the Z-direction at a regular gap of 0.15 mm. Figures 7 and 8 show the longitudinal and transverse welded specimens for evaluation of the joint tensile strength. Six lap-shear specimens were tested for each process condition, with the steel plate being pulled for three cases and the Inconel 625 plate being pulled for the other three samples. Separate engagement of the steel and Inconel 625 plates during the lap- shear tensile testing was conducted to evaluate the effect of stir zone asymmetry on the final weld joint strength. Figure 9 shows the longitudinal micro-tensile testing specimen and its dimensions. The Response Surface Methodology experimental design was used to vary the selection of three different process input parameters, such as welding speed, wire feed rate, and voltage, and three levels, as shown in Table 2. Table1: Chemical composition (%) of Inconel 625 and GL E36 steel Elements Ni Cr Fe Mo Nb Co Mn Al Ti Si C INCONEL625 58 21.70 4.70 8.60 3.38 0.03 0.09 0.13 0.18 0.18 0.02 GL E36 - 0.06 - 0.01 0.03 - 1.40 0.03 0.01 0.39 0.17 Table 2: Process Parameters and levels Process Parameters Level 1 Level 2 Level 3 Welding speed (s) 52.0 58.0 64.0 Wire Feed rate (F) 4.7 5.1 5.6 Voltage (volts) 22.0 24.0 26.0 http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 916 Figure 4: 2-3 Dimension Sectional View Fig. 5: Horizontal micro structure Fig. 6: Vertical Micro structure Fig. 7: Longitudinal Specimen Fig. 8: Transverse Specimen Figure 9: longitudinal micro-tensile A steady-state three-dimensional heat conduction analysis was carried out considering the governing equation in equation 1 (Benlamnover et al., 2021). 𝜕 𝜕𝑥 (𝑘 𝜕𝑇 𝜕𝑥 ) + 𝜕 𝜕𝑦 (𝑘 𝜕𝑇 𝜕𝑦 ) + 𝜕 𝜕𝑧 (𝑘 𝜕𝑇 𝜕𝑧 ) + 𝑄 = 𝜌𝐶𝑝𝑉 𝜕𝑇 𝜕𝑥 (1) Where v is the tool travel speed, T is the temperature variable, x, y, and z are spatial variables, and ρ, k, and Cp refer to the density, thermal conductivity, and specific heat of the workpiece materials, respectively. The FSLW process was simulated, considering the Inconel 625 plate lapped onto the steel plate from the bottom until a depth of 0.5 mm. The tensile strength of a weld joint was measured by subjecting the standard http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 917 specimens drawn from the test coupons to tensile tests as per ISO 4136:2001 using a universal testing machine. The hardness of different regions in the weld joint is measured by a Rockwell hardness test (ISO 9015-1 and 9015-2 standards) following the preparation of the preparation of a weld pad of size 80mm wide, 300mm long, and 3mm thick with run-on and run-off plates. 2.2 Weld Geometry and Defect Test The bead width, such as welding current, welding speed, and gap distance, was determined by measuring the width of each welded sample with 0.01 mm least-count Vernier callipers for the mechanical qualities of the weld. 2.3 Mechanical Property Testing For various mechanical tests, GMAW-welded experimental specimens were created from SS316 metals and machined using ASTM in order to determine the necessary dimensions for studying their properties. 2.4 Tensile Strength A tensile test was conducted using a universal testing machine, a 600 servo-hydraulic with a piston speed of 8 mm/min and a maximum force of 600 KN. 2.5 Hardness Testing The Rockwell hardness test was used because it was quick, inexpensive, and largely non-destructive, leaving a tiny indentation on the specimen. The hardness strength of the welded samples was examined using BROOKS Rockwell hardness testing equipment with a ball-shaped indenter at a force of 100 kg for a duration of 10 s. 2.6 Design Expert The design matrix of three welding parameters via speed (S), wire feed rate (F), and voltage (V) at three levels was selected as the quality characteristic for the performance measure for 20 experimental runs, optimized, and tabulated. 2.7 Response surface methodology (RSM) RSM was used to investigate the response of welding process parameters to the physical properties of INCONEL 625 and GL E36 steel based on design expert software. The welding speed, wire feed rate, and voltage were chosen as the independent variables, while the dependent variables (responses) were tensile strength and hardness values. The quadratic response surface model built up all the linear terms, square terms, and linear by-linear interactions described in equation 2 (Tumer et al., 2022). Y=𝛽𝑜 + 𝜀 ∑ 𝛽𝑖𝑥𝑖 + ∑ 𝛽𝑖𝑗 𝑘 𝑖−1 𝑘 𝑖=1 𝑥𝑖𝑥𝑗 + ∑ 𝛽𝑖𝑖 𝑘 𝑖=1 𝑥𝑖 2+ 𝜀 (2) Where Y is the predicted response; 𝛽𝑜 is the overall mean,𝛽𝑖 is the linear effect of the input factors 𝑥𝑖; 𝛽𝑖𝑗 is the linear-by-linear interaction effect; 𝛽𝑖𝑖 is the quadratic effect of the input factor, 𝑥𝑖𝜀 is the random error term. 2.8 Empirical Model The second-order polynomial model was used to describe the behaviour of the response to the inputs following the form presented in equation 3 (Wang et al., 2020; Zhao et al., 2021; Yang et al., 2022) 𝑌 = 𝑋0 + 𝑋1(𝐴) + 𝑋2(𝐵) + 𝑋3(𝐶) + 𝑋11(𝐴2) + 𝑋22(𝐵2) + 𝑋33(𝐶2) + 𝑋12(𝐴𝐵) + 𝑋13(𝐴𝐶) + 𝑋23(𝐵𝐶) (3) Where all X are constants and Y is the response. http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 918 The developed empirical formulas in terms of the coded factors are given as equations 4 and 5 for tensile strength and hardness, respectively. 𝑌1 = {435.34 − 37.82𝐴 + 1.76𝐵 + 12.18𝐶 − 0.3750𝐴𝐵 + 1.87𝐴𝐶 + 0.1250𝐵𝐶 − 2.62𝐴2 + 5.69𝐵2 + 5.51𝐶2} (4) 𝑌2 = {83.00 − 7.12𝐴 + 0.3661𝐵 + 2.35𝐶 − 0.1250𝐴𝐵 + 0.3750𝐴𝐶 − 0.1250𝐵𝐶 − 0.6781𝐴2 + 1.09𝐵2 + 0.9129𝐶2} (5) Y1 is the tensile strength response, Y2 is the hardness response, and A, B, and C represent the welding speed, wire feed rate, and voltage, respectively. 3. Results and Discussion The results of the liquid penetrant and visual defect testing on the specimens were visually inspected and showed a few welding faults, such as a bit of undercut at the end, excessive reinforcement height, lack of fusion, porosity, root crack, and lack of penetration in some of the welded samples. There was a lack of fusion in one sample (20) due to minimum current input, arc length, electrode angle, electrode manipulation, and improper welding parameter settings, which contributed to the fusion failure. There was a porosity defect observed in a sample (14). This defect was created by air entrapped in the shielding gas, which resulted in dispersed porosity and gross surface pore breaking. An undercut defect was observed in samples 2 and 10. At the weld, undercut discontinuities formed a mechanical notch interface. Apart from the aforementioned, others were defect-free samples (1-20) used for the tensile strength and hardness tests in consonance with Mou et al. (2021) study. Table 3 displays the tensile strength and hardness values of the welded samples based on the 20 experimental runs used for this study. The tensile strength and hardness values gotten from the experiment range between 380 and 500 MPa and 72 and 95 HRB, respectively. The large variance shows that process factors have an impact on the mechanical behavior of welded samples. The impact of welding input parameters such as welding speed, welding feed rate, and voltage is significant to the mechanical property responses. For instance, welding input parameters in the experimental run 7 with welding speed 52, welding feed rate 5.6, and voltage of 26 produced the highest value of tensile strength and hardness, i.e., 500 MPa and 95 HB, whereas the experimental run 10 with welding speed 68, welding feed rate of 5.1, and voltage of 24 v had the least tensile strength and hardness, i.e., 380 MPa and 72 HB. Increasing the welding feed rate from 5.1 to 5.6 increases the tensile strength from 380 to 500 MPa and the hardness value from 72 to 95 HB. There were 3 runs with the same input welding parameters given by the design expert, as seen in experimental runs 4, 16, and 17, with the same values of 58, 5.1, and 24 for welding speed, welding feed rate, and voltage, respectively, as shown in Table 3. There was no significant difference in their response values for both tensile strength and hardness. However, when the welding feed rate and voltage have the same values but different welding speeds, as seen in experimental runs 1, 4, 5, 8, and 17, there was significant variation in tensile strength and hardness. This is proof that the welding speed input parameter is the most significant factor that influences the tensile strength and hardness responses as contained in Satputaley et al., (2021) and Patel et al., (2020) works. http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 919 Table 3: Experimental responses of tensile strength and hardness at different levels S/N Original Value Responses Welding, S(m/s) Welding Feed Rate(m/min) Voltage(v) TS (MPa) Hardness (HRD) 1 52 5.1 24 476 90 2 64 5.6 22 385 73 3 64 4.7 26 482 92 4 58 5.1 24 388 74 5 64 5.1 24 495 94 6 64 5.6 26 410 78 7 52 5.6 26 500 95 8 58 5.6 24 415 79 9 50 4.7 24 476 90 10 68 5.1 24 380 72 11 58 4.4 26 450 86 12 58 5.9 24 453 86 13 58 5.1 21 428 81 14 52 4.7 27 474 90 15 58 5.1 22 435 83 16 58 5.1 24 435 83 17 58 5.1 24 436 83 18 64 4.7 22 436 83 19 64 4.7 22 435 83 20 52 5.6 22 435 83 In reliability Table 4, the factors are considered significant when the adequacy of this model is analysed using ANOVA (and p ≤ 0.05) and insignificant if otherwise. Accordingly, the developed models are significant. Welding speed (A) and voltage (C) are more significant than welding feed rate. http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 920 Table 4: Determination of model significance using ANOVA Source Tensile Strength Hardness F Value p- value F Value p-value Model 29.18 < 0.0001 29.42 < 0.0001 A-Welding Speed 223.53 < 0.0001 211.37 < 0.0001 B-Welding feed rate 0.4911 0.4994 0.5585 0.4721 C- Voltage 23.51 0.0007 23.07 0.0007 AB 0.013 0.9113 0.0381 0.8491 AC 0.3262 0.5805 0.3432 0.5710 BC 0.0014 0.9704 0.0381 0.8491 A2 1.05 0.3096 2.02 0.1855 B2 5.41 0.0423 5.22 0.0454 C2 5.08 0.0478 3.66 0.0846 *Note that the p-value of less than 0.0500 is an indication of model term significance. Figure 10 (a-c) shows the effect of the input factors on the first response tensile strength. The three plots clearly show the level of significance of the selected welding speed and voltage on the tensile strength. It was discovered in Figure 10a that the welding speed has a better influence on hardness than the welding feed rate because the hardness deviates more from the welding speed than the welding feed rate. Figure 10b depicts a better response of welding speed compared to the voltage, and Figure 10c shows that hardness has a better response to the voltage compared to the welding feed rate. The hardness responses obtained from all the input parameters follow the same trend when compared to the tensile strength response, while the welding feed rate showed the least significant effect on hardness. Figure 10: 3D plots of tensile strength against (a) welding speed and welding feed rate (b) welding speed and voltage (c) voltage and welding feed rate Y 1 ( M P a) A B C http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 921 Figure 11: 3D plots of hardness against (a) welding speed and welding feed rate (b) welding speed and voltage (c) voltage and number of passes As indicated in Table 5, R2 of 0.9633 and 0.9611 for both tensile strength and hardness and adequate precisions of 19.7960 and 19.284 for both tensile strength and hardness imply a good fit. Other variables also support the fact that the model is adequate and reliable, and can be used to navigate the design space. Table 5: Second Order Model Fitting Results in the Form of ANOVA Model Summary Characteristics Tensile strength Hardness Standard Deviation 9.29 1.81 Mean 441.20 83.9 R2 0.9633 0.9611 Adjusted R2 0.9303 0.9260 Predicted R2 0.7216 0.7040 Adequate Precision 19.7960 19.284 The value of the output factors at optimum for the given input parameters with a maximum desirability of 1 and for the combined results that are derived from the software. The tensile strength and hardness generated from the empirical model developed have been validated with the use of experimental results and were compared as presented in Table 6.Three confirmation experiments were conducted at the optimum process welding parameters of 53 welding speed, 5 welding feed rate, and 23 voltage that were predicted by the software. The details of the experimental designs were reported in Figure 12 (Zhang et al., 2020). Figure 12: Tensile strength Response ANOVA A B C http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 922 Table 6: Predicted and experimental results for tensile strength and Hardness Standard Input Tensile S Hardness W S WFR Voltage Actual Predicted Actual Predicted 1 52 5.1 24 435.00 435.34 83.00 83.00 2 64 5.6 22 415.00 421.67 79.00 80.04 3 64 4.7 26 476.00 491.53 90.00 93.06 4 58 5.1 24 453.00 454.39 86.33 86.69 5 64 5.1 24 453.00 435.34 83.00 83.00 6 64 5.6 26 428.00 430.45 81.00 81.62 7 52 5.6 26 495.00 489.79 94.00 93.05 8 58 5.6 24 482.00 473.44 92.00 90.08 9 48 4.7 24 390.00 364.33 72.00 69.10 10 68 5.1 24 435.00 435.34 83.00 83.00 11 58 4.4 26 388.00 393.31 74.00 74.84 12 58 5.9 24 476.00 469.42 90.00 88.85 13 58 5.1 21 410.00 418.65 78.00 79.81 14 52 4.7 27 385.00 390.79 73.00 74.10 15 58 5.1 22 435.00 435.34 83.00 83.00 16 58 5.1 24 474.00 471.42 90.00 89.54 17 58 5.1 24 500.00 494.31 95.00 93.79 18 64 4.7 22 450.00 448.47 86.00 85.46 19 64 4.7 22 436.00 435.34 83.00 83.00 20 52 5.6 22 436.00 435.34 83.00 83.00 Note: WS = Welding speed and WFR = welding feed rate 4. Conclusion The right selection of welding process and responses of tensile strength and hardness by optimizing the welding parameters during the welding of INCONEL 625 and GL E360 steels in the operation have been investigated and established. The parameters have a significant impact in relation to the input independent variables (such as welding speed, welding feed rate, and voltage) and the response variables (such as tensile strength and hardness). Various defects in welding technologies have been eliminated by using the correct combination of welding process parameters, technical know-how, response surface methodology, and optimization tools. The tensile strength falls between 380 and 500 MPa, and the hardness is between 72 and 95 HRD. The variation in the responses shows that the combination of the selection of welding process parameters has a significant impact on the machining operations. The impact of a welding speed of 52, a welding feed rate of 5.6, and a http://www.azojete.com.ng/ mailto:oginni.olarewaju@bouesti.edu.ng Arid Zone Journal of Engineering, Technology and Environment, December 2024; Vol.20(4): 913-925. ISSN 1596-2490; e-ISSN2545-5818; www.azojete.com.ng Corresponding author’s email address: oginni.olarewaju@bouesti.edu.ng 923 voltage of 26 (run 7) proved to be the most noticeable effect, with the highest tensile strength of 500 MPa and a hardness of 95 HRD.The welding process parameters have the highest significant factor in tensile strength, followed by the voltage. The welding feed rate parameter is the least significant in both tensile strength and harness responses. The value of the output factors at optimum for the welding parameters at maximum desirability of 1 and for the combined results that are derived from the software was obtained. 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