Interaction Effects Of Parameters Research Articles

Response Surface Optimization for Compliant Joint of Humanoid Robot Using ANSYS - Design of Experiment

Objective: A Compliant Joint of humanoid robot is a spring-loaded assembly, which is used to interact safely with the environment, and it helps to stabilized sudden shock and vibration in the robotic system. At the moment, compliant joints are required to optimize their size and dimensions which result into optimized weight and factor of safety of humanoid robot. Methods: Analysis is carried out using Response Surface Methodology (RSM) and Multi-Objective Genetic Algorithm (MOGA) using ANSYS. The current study employed goal-driven optimisation using ANSYS Workbench to minimise weight and achieve the required factor of safety range for the compliant joint. To find out range of variables such as rim thickness, shaft diameter, base thickness, module thickness and spoke thickness affecting on responses such as factor of safety and geometrical mass of compliant joint single factor single response parametric analysis is carried out. Findings: Based on trend of preliminary analysis variable range and combinations are selected to study interaction effect of parameters to obtain favorable factor of safety and low geometrical mass. The optimized compliant joint is compared with various design and validated through the developed actual module. Novelty: Eventually, the geometry mass of the compliant joint was reduced from 0.8604 kg to 0.6449 kg, resulting in a lighter weight (24.06% reduction) with a 1.7533 factor of safety and more compact in size (outer diameter is shrink from 142 to 126 mm). Keywords: Compliant joint, Goal driven optimization, Response surface optimization, Design of experiment, Humanoid robot

An Experimental Study on Hard Turning Performance of DIN 17350 Tool Steel

The main objective is to investigate the effects of cutting speed, feed rate and depth of cut on surface roughness Rz in hard turning process of DIN 17350-tool steel (60÷62HRC) under dry condition. The full factorial experimental planning design with the help of Minitab 19 software was applied to evaluate the main effects and interaction effects of input machining parameters. The experimental results indicate that feed rate and depth of cut cause the stronger impact on the objective function Rz than cutting speed. In addition, the interaction effects of cutting speed and feed rate as well as the cutting speed and depth of cut have significant influences on the output, but the interaction effect between the feed rate and depth of cut has little impact. Furthermore, cutting speed of 1400 rpm, feed rate of 0.05 mm/rev, and cutting depth of 0.1 mm should be recommended for the smaller surface roughness Rz values.

Evaluation of sugar content and bioethanol production of Ethiopian local varieties “Nech Tinkish” and “Hawaye” sweet sorghum (Sorghum bicolor (L.))

Diversifying the use of climate-smart crops such as sweet sorghum has the potential to solve integrated food, bioenergy, feed, and land management problems. The study’s purpose is to quantify the sugar content of Nech Tinkish (v1) and Hawaye (v2) Ethiopian sweet sorghum varieties and investigate the interaction effect of fermentation parameters to determine their capacity for ethanol production. Sweet sorghum varieties were analyzed to determine their difference in °Brix content by extracting their juices. The juice was clarified using milk lime. Its total soluble sugars, total carbohydrates, and reducing sugars were determined using a digital refractometer, phenol sulfuric acid, and 3,5-dinitrosalicylic acid, respectively. A completely randomized factorial was employed to evaluate ethanol production capacity, and the ethanol content was estimated using a potassium dichromate solution. The °Brix results revealed that v2 had a higher sugar concentration than v1. Additionally, the estimated carbohydrate content of the juice ranged from 37.402 to 157.641 g/L. The estimated reducing sugar also varied from 4.644 to 33.412 g/L. Therefore, the estimated reducing sugar showed the hydrolysis of sweet sorghum juice by invertase and sulfuric acid produced more fermentable sugars. Fermentation at 30 °C with pH 4.5 incubated for 4 days yields the highest ethanol, and v2 yields higher (15.31%) ethanol, compared to v1 produced 14.85%. This study showed a basis for the existence of two sugar-rich climate smart sweet sorghum varieties with an extraordinary amount of sugar used as a source of biofuel and food simultaneously in a single plot of land.

Size effects of voids on the mechanical properties of 3D printed parts

Although the effects of additive manufacturing process parameters on the mechanical properties of 3D printed parts have been numerically investigated in the literature, less attention has been paid on the size effects of voids between deposited filaments. This study fills this gap by developing a methodology based on a combined finite element (FE) and design of experiment (DoE) technique. The development of FE methodology is based on micro-mechanical analysis of representative volume element (RVE) of 3D printed parts to predict the effective orthotropic properties. To account for the size effects of inter-bead voids, the RVE includes contribution of the multiple parameters of layer heights, layer widths and overlapping regions. To study the main and interaction effects of the above input parameters on the stiffness properties of 3D printed parts, a structured approach based on full factorial design is used. Although the size effects of voids on the constituents of elastic moduli of RVE were investigated, the main focus in the present work is to develop a regression model to predict the stiffness properties. The FE stress analysis of the RVE conducted in this study provides an insight about the potential failure modes such as delamination and filament debonding that may occur in load bearing 3D printed parts. For a case study, the results of FE-based homogenization technique in terms of stiffness properties are validated against the experimental data via three-point bending and Iosipescu shear tests which were conducted in conjunction with digital image correlation technique. The combined numerical and statistical approach proposed in this study provides a swift iterative design of 3D printed parts prior to the time-consuming computation modelling, contributing to reduce the number of tests and manufacturing costs.

Synergistic interaction effects of process parameters on surface finish in two-way AFM of SS446

Synergistic interaction effects of process parameters on surface finish in two-way AFM of SS446

Sensitivity Analysis and Optimization of Energy-Saving Measures for Office Building in Hot Summer and Cold Winter Regions

To effectively reduce building energy consumption and enhance indoor thermal comfort, this study developed a sensitivity analysis and multi-objective optimization method for an office building in Hangzhou considering the effects of parameter interactions. We utilized Latin hypercube sampling (LHS) to sample the parameters and subsequently simulated the energy consumption and discomfort hours for the building’s four orientations. Following this, Gaussian process regression models were established, and the feature importance ranking method (FIRM) alongside an interaction effects method were employed to quantify the sensitivity of 10 parameters. Lastly, a multi-objective optimization was performed for total energy consumption and discomfort hours, yielding a set of Pareto-optimal solutions. Through the VIKOR method, the optimal solution within the Pareto set was identified, resulting in three sets of optimal solutions.

Optimization of Mechanical Properties Of Electrospun Epoxidized Natural Rubber/ Acrylonitrile-Butadiene-Styrene (ENR/ABS) Fibre For Membrane Application

This study created membrane nanofibres using the electrospinning method and newly studied a mixture of ENR and ABS. The two-level complete factorial designs with centre points were used to characterise the functionality of the constructed membrane. The variables considered for experimental design were the polymer concentration, materials ratio (ENR concentration), applied voltage and distance between the needle tip and collector. According to the analysis of variance (ANOVA), the concentration of solution and distance were statistically significant parameters that affected the tensile properties of the ENR/ABS electrospun membrane. A mathematical model of the tensile property of polymer fibres was created using Response Surface Methodology (RSM). This model was built based on essential process factors. The mechanical properties of the electrospun ENR/ABS membrane compromised with 25wt% of solution concentration, 30% ratio of ENR, the voltage at 22.5kV and 15 cm of distance create an excellent tensile strength with desirability of 0.94. The influence of ENR on the morphology of ENR/ABS fibres was characterised by Scanning Electron Microscopy (SEM). The result showed beaded fibre and decreased fibres due to the low concentration of the solution and high ratio of ENR (50%). The contact angle measurements indicated that the electrospun fibre membrane was hydrophobic with a water contact angle of 136°. The addition of ENR showed a reduction in contact angle to 119°. The existence of ENR will change the features of the membrane, and investigations have demonstrated that RSM has been efficiently developed to acquire the interaction effects of processing parameters.

Optimization of Ziziphora clinopodioides L. essential oil nanoencapsulation in chitosan nanocomplex by response surface methodology

Nano-encapsulation of essential oils, a specific area of interest, can help overcome challenges associated with their commercial use. This study aimed to evaluate the effect of different concentrations of chitosan, Ziziphora clinopodioides L. essential oil (ZcEO), and Sodium-Tri Polyphosphate (TPP), both individually and in interaction, on several properties of EO-loaded chitosan nanoparticles. These properties include particle size (PS), zeta potential (ZP), and encapsulation efficiency (EE) using a two-stage emulsion-ionic gelation approach. The optimization of the parameters was done by response surface methodology using Box-Behnken design. The chemical composition of ZcEO was analyzed as well. The primary compounds in ZcEO were found to be pulegone (29.24 %), 1,3-dimethyl-2-(2-methylpropylidene) imidazolidine (9.05 %), piperitenone (6.65 %), thymol (5.38 %), and carvacrol (5.27 %). The PS ranged from 117.33 to 4934.1 nm, the ZP varied from −1.1 to −30.83 mV, and the EE spanned from 31.74 to 87.04 %. The results showed that an increase in the initial EO content led to a decrease in PS and ZP, but an increase in EE. Moreover, increasing the TPP concentration resulted in an enhancement in PS, ZP, and EE, whereas increasing the Chs concentration led to a slight increase in PS, ZP, and EE. Furthermore, the results of this study proved the interaction effect of different parameters on the responses investigated. Under optimized conditions, the optimal concentrations of chitosan, ZcEO and TPP were attained at 6.768, 6.078, and 7.595 mg/mL respectively. This resulted in a PS of 117.331 nm, a ZP of −20.949 mV, and an EE of 75.385 %. In conclusion, the results suggest that adjusting the concentrations of Chs, EO, and TPP is an effective approach to controlling the properties of NPs and optimizing their performance.

Experimental and statistical study on the effect of process parameters on the quality of continuous fiber composites made via additive manufacturing

Ongoing research in additive manufacturing towards structural and industrial application has led to the use of commingled roving as a manufacturing feedstock for printing high fiber volume fraction composites. The prospects of using this technology for high performance applications necessitates the need for a comprehensive experimental investigation into the effects of processing parameters on the quality of an additively manufactured composite printed from commingled roving feedstock. In this work, transverse flexure and void fraction matrix pyrolysis testing are both performed to evaluate composite quality. The transverse flexure test is a testing approach that evaluates the quality of the interfacial fiber-matrix bond while the void fraction test estimates the void content in the printed composite. A full observational study consisting of 27 different test combinations is done to investigate the effects of three different process parameters namely, temperature, pressure, and print speed across three different levels. Composite samples were made from commingled roving of E-glass and amorphous PET using an in-house built continuous fiber composite digital manufacturing system. Least squares regression analysis is performed to study the main, interaction and quadratic effects of process parameters. A statistical regression model having an R2 adjusted value of 80.1% is generated from the transverse flexure study, which is used to explain main and interaction effects and also predict performance. Response surface plots are also generated and are used to optimize process parameters which can subsequently be of help in scaling up composite manufacturing. Results show that all three process parameters are highly statistically significant at the 0.01 level of significance. Pressure * Temperature and Pressure * Printspeed are significant interaction terms. Pressure plays a weightier role when print speed is increased or temperature is decreased as it closes more voids that would ordinarily have been introduced because of drop in polymer melt viscosity. Micrographic analysis is also performed.

Removal of major nutrients by sono-direct and sono-alternate current electrocoagulation process from domestic wastewater

Background: Electrocoagulation is becoming a promising eco-friendly wastewater treatment technique. It is a low-cost wastewater treatment method suitably applied for various wastewater effluent characteristics. Nevertheless, there are different kinds of electrocoagulation; comparison among them in terms of nutrient removal is investigated in the present research. This study analyzed nitrate (NO3 - ) and phosphate (PO4 3-) removal potential of the sono-alternative and direct-current electrocoagulation process. Methods: Batch reactor and sono-direct current (SDC)/sono-alternative current (SAC) electrocoagulation cell were employed to investigate NO3 - and PO4 3- removal efficiency from domestic effluents. The data gathered from laboratory experiments were analyzed using response surface methodology (RSM). ANOVA was used to examine the interaction effects of diverse parameters in terms of NO3 _ and PO4 3- removal from domestic wastewater effluents. Results: At extreme experimental conditions, the percentage of NO3 - and PO4 3- removal attained with sono-direct current electrocoagulation (SDCE) and sono-alternative current electrocoagulation (SACE) were 96.5%, 96.2% and 96.8%, 96.5, respectively. The SACE was more successful in eliminating NO3 - and PO4 3- than the SDCE process. The appearance of resistant oxide coating on the cathode and the appearance of corrosion on the anode due to oxidation processes in the case of SDCE were identified as principal factors highly affecting NO3 - and PO4 3- removal efficiency. Conclusion: With optimum process efficiency, experimental findings show that the SACE process is more capable of NO3 - and PO4 3- removal than the SDCE process.

Proposal and optimization of a novel biomass-based tri-generation system using energy, exergy and exergoeconomic analyses and design of experiments method

A novel trigeneration system of cooling, heating and power based on biomass is designed in current study. This system consists of five parts: biomass gasification subsystem, steam turbine subsystem (Rankin cycle), gas turbine subsystem (Brayton cycle), Kalina subsystem and ejector refrigeration subsystem. Energy, exergy and exergy-economic analysis were performed on the whole system and the effects of different key parameters on energy efficiency and exergy and economic factors are investigated. The designed cycle has been qualitatively optimized using DOE method and the interaction effects of parameters on cycle performance has been investigated. The results show that the highest exergy destruction is related to the combustion chamber with 56.14 %. Also, the lowest exergy destruction is assigned to the separator of the Kalina cycle with a nearly zero value. The highest investment, operating and maintenance costs are related to air compressor, gas turbine and steam generator, respectively. The results of parametric analysis showed that with increasing the mixing ratio of natural gas to syngas the thermal and exergy efficiencies, the rate of total system cost and the unit cost of power generation increase. Also, with increasing gasification temperature, the thermal and exergy efficiencies of this system vary slightly and can be considered constant, but the total cost of system increases. The results of DOE analysis showed that among the main effects of the parameters, the isentropic efficiency of the gas turbine and the temperature of the air entering the combustion chamber have the greatest effect on the system efficiency, and the GMR has the greatest effect on the LCOE of the system, and among the interaction effects of the parameters, the interaction between the temperature of the air entering the combustion chamber has the greatest effect on the system efficiency and LCOE.

Optimization Research on the Space-V-Type Biomimetic Surface Grooves of a Marine Centrifugal Pump

The biomimetic surface with Space-V grooves can effectively reduce flow resistance and noise. Our investigation was in order to further enhance the drag reduction and noise reduction performance of a marine centrifugal pump with Space-V-groove-shaped biomimetic surfaces. A regression equation was established with response surface methodology between the total sound pressure level and the height (h), width (s), and spacing (b) of the biomimetic groove structure. The interaction effects of various parameters on the total sound pressure level were analyzed, and the parameter range was determined at the lowest total sound pressure level. The hydraulic performance and interior noise of the model before and after optimization were compared. The results showed that the total sound pressure level initially decreased and then increased with increasing groove height. Similarly, with an increase in groove width, the total sound pressure level decreased at first, then increased. When the height of the bionic groove is 0.5–0.7 mm, the groove width is 0.4–0.7 mm, the groove spacing is 0.7–1.3 mm, and the total sound pressure level of the centrifugal pump is the smallest, which is 180–182 dB. On the other hand, the total sound pressure level increased as groove spacing increased. Through the use of an optimized Space-V groove model, under rated working conditions, the model head is increased by 0.27 m and the efficiency is increased by 1.21%. In addition, the optimized model has excellent drag and noise reduction performance, with the drag reduction rate of 3.73% and noise reduction rate of 1.81%, which are, respectively, increased by 0.87% and 0.45% compared with before optimization. The performance of centrifugal pumps for ships can be greatly improved.

Uncertainty Quantification for the Noah‐MP Land Surface Model: A Case Study in a Grassland and Sandy Soil Region

AbstractLand surface models rely on a multitude of parameters to simulate land‐atmosphere interactions, but the parameter uncertainty can limit the reliability of model predictions. This study utilizes a parameter uncertainty quantification (UQ) framework to quantify and reduce the parameter uncertainty of the Noah‐MP land surface model in a grassland and sandy soil region in the Midwest of the USA. First, the sparse polynomial chaos expansion method which can quantify the interaction effect of parameters, is employed. A relatively small parameter sample size (i.e., 20 times of the number of parameters) was sufficient to identify the sensitive parameters; an additional sensitive parameter, the saturated soil hydraulic conductivity, was screened out compared to previous study. Then, based on the selected sensitive parameters, the weighted multi‐objective adaptive surrogate modeling‐based optimization algorithm is used as the parameter optimization method. The optimization results showed that the root mean square error of flux of latent heat (FLH) on about 82% of the total grids was reduced, and the number was about 57% for gross primary production (GPP) compared to the results using the original parameter settings, indicating that the Pareto parameter set by the UQ framework improved the Noah‐MP model in simulating FLH and GPP in a grassland and sandy soil region in the Midwest of the USA.

Process Parameter Optimization of Aerospace-Grade Dissimilar Aluminium Alloy 7075 and 2014 by Friction Stir Welding

In friction stir welding process, the selection of optimum process parameter is an important step. To make a welding with high quality in all aspects such as defect free and reduced HAZ region, it becomes necessary to choose the parameter in such a way the temperature developed due to heat generation is in optimum level. A study on the effect of process parameters on temperature distribution and HAZ region is performed for dissimilar combination of AA7075 and AA2014. A statistical model based on Box-Behnken RSM is built to study the interaction effect of parameters on temperature distribution and optimization of process parameter is obtained as is Tool Rotational Speed (TRS) – 1400 rpm, Tool Traverse Speed (TTS) – 1.21mm/s and Tool Size Ratio (TSR) – 4. An experiment of FSW is made with K-type thermocouples for optimized parameter of AA7075+AA2014 and temperature reading is then compared with simulation for validation of model. The prediction accuracy is in the range of maximum 98.69% and minimum 92.45%. It was observed that optimum depth location of thermocouples is beyond the half of thickness because of less error attained as 1.31%.

Laser cutting of basalt fibre reinforced polymers by QCW fiber laser: Interaction mechanisms and effect of laser parameters

In the paper, laser cutting of basalt fibre reinforced polymer laminate using a 450 W QCW fiber laser, working in a pulsed regime is presented. Preliminary tests were performed on a basalt laminate, 1.3 mm in thickness, changing the pulse power (Pp) and pulse duration (D) to find the maximum cutting speed. Then a 33 experimental plan was carried out changing the pulse power, the pulse duration, and the cutting speed. The kerf width and the heat-affected zone were measured in the section and on the external surfaces. ANOVA analysis was adopted to assess the process parameters’ influence. The interaction mechanisms were found and discussed. From the results, the BFRP laminate appears easy to cut at maximum cutting speeds up to 3500 mm/min. However, thermal damages occur. Kerf geometry and HAZ are mainly affected by the cutting speed, while the Pp and D seem to have a minor role.

Revealing interactions between the operating parameters of protonic ceramic electrolysis cell: A modelling study

Protonic ceramic electrolysis cell (PCEC) is a clean and sustainable technology for hydrogen production. To provide a comprehensive understanding of the effects of various parameters on the performance of PCEC, a framework is proposed to combine the 2D numerical model with One-Factor-At-a-Time (OFAT) and Design of Experiments (DOE) methods. DOE is a simple but effective method to gain deep insight into the effect of different factors on the response variable using a small number of cases. In the OFAT result, a peak optimal Faradaic efficiency (FE) of 82% is found at 600 °C and a current density of 0.4 A cm−2. The FE increases with the increasing inlet flow rate, while the temperature gradient reduces continuously. It is also found that if the inlet steam mole fraction increases by 5%, the FE can be increased by at least 0.25%. DOE results demonstrate the most important factors are the anodic inlet steam molar fraction and anodic inlet flow rate. Additionally, the interaction effects between them are also found to be significant. Noteworthy, regression models derived from DOE results also demonstrate potential capabilities as surrogate models for 2D numerical model. Therefore, DOE is a powerful tool that can draw rigorous conclusions while saving a lot of computational resources. Overall, this study provides deep insights into the interaction effects of different parameters. The framework proposed in this study can be applied to guide future PCEC design optimization.

The rest-activity rhythm, genetic susceptibility and risk of type 2 diabetes: A prospective study in UK Biobank.

This study aims to examine the association between the rest-activity rhythm (RAR) and the incidence of type 2 diabetes (T2D). In total, 97 503 participants without diabetes in the UK Biobank cohort were recruited. Wearable accelerometry was used to monitor circadian behaviour. The parameters of RAR including inter-daily stability, intra-daily variability, relative amplitude (RA), most active continuous 10 h period (M10), and least active continuous 5 h period (L5) were calculated to evaluate the robustness and regularity of the RAR. The weighted polygenic risk score for T2D (T2D-PRS) was calculated. Cox proportion hazards models were used to evaluate the survival relationship and the joint and interaction effects of RAR parameters and T2D-PRS on the occurrence of T2D. During 692 257 person-years follow-ups, a total of 2434 participants were documented. After adjustment for potential confounders, compared with participants in the highest quartile of RA and M10, the participants in the lowest quartile had a greater risk of T2D (HRRA = 2.06, 95% CI: 1.76-2.41; HRM10 = 1.33, 95% CI: 1.19-1.49). Meanwhile, the highest quartile of L5 was related to a higher risk of T2D (HR = 1.78, 95% CI: 1.55-2.24). The joint analysis showed that the high T2D-PRS with the lowest quartile of RA and M10, or highest quartile of L5 jointly increased the risk of T2D (HRRA = 4.46, 95% CI: 3.36-6.42; HRM10 = 3.15, 95% CI: 2.29-4.32; HRL5 = 3.09, 95% CI: 2.40-3.99). No modification effects of T2D-PRS on the association between the RAR parameters and risk of T2D were observed (p > .05). The unbalanced RAR are associated with a greater risk of T2D, which are independent of known risk factors of T2D.

Chloride removal from sewage using bismuth trioxide: Characterization and optimization by response surface methodology (RSM)

Chloride ions, omnipresent environmental pollutants, can have devastating and irreversible effects on sustainable water ecosystems worldwide. Herein, bismuth oxide (Bi2O3) was employed as an antichlor to effectively dislodge chloride, and systematic investigations were conducted to assess the effect of various factors on dechlorination. Response surface methodology with Box-Behnken designs was used to optimise the dechlorination process, and the control parameters were determined by fitting high quality predictive model incorporating saliency variables and interactions. Furthermore, X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS) were performed to determine the phase composition, micromorphology and binding energy of the dechlorinated products. The optimum parameters for dechlorination, as determined by response surface methodology (RSM), were found to be pH 0.53, bismuth trioxide multiple of 1.48, and initial chloride concentration of 3.62 g/L, giving a theoretical removal rate of 90.0563 %. The data analysis presented provides evidence that response surface methodology is a reliable approach for optimizing the interaction effects of dechlorination process parameters, resulting in improved performance in the removal of almost non-removable chloride.

Investigations of performance characteristics on direct metal laser sintered MONEL K-500 superalloy

MONEL K-500 superalloy is difficult to manufacture precisely in traditional manufacturing processes like casting, forming and machining. The direct metal laser sintering (DMLS) process is one of the best metal additive manufacturing processes used in this work. In this work, Laser Power (LP), Scan Speed (SS), Hatch Distance (HD) and Layer Thickness (LT) are used as DMLS process parameters. L09 Orthogonal array is used for printing the MONEL K-500 metal parts. The performance characteristics like ultimate tensile strength (UTS) and surface toughness (Ra ) are improved by 2% and 17% for the Taguchi optimum parameter levels. Contour plots explained the interaction effects of DMLS process parameters on performance characteristics. The better microstructural characteristics obtained the higher optimum parameter level.

Optimization of gas tungsten arc welding parameters for welding of super duplex stainless steel using factorial design

This study investigates the relationship between four welding input parameters (voltage, current, heat input, and welding speed) and the ultimate tensile strength (UTS) and yield strength (YS) of a welded joint. The work joined two super-duplex stainless-steel pipes of outside diameter 0.630 inches (16.002 mm) and a thickness of 0.065 (1.651 mm), using Gas Tungsten Arc Welding. Factorial design was used to ascertain the main and interaction effects of the welding input parameters on the UTS and YS of the welded joint. Results revealed a significant interaction between voltage, current, welding speed and heat input for UTS, and a significant interaction between the welding speed and heat input for YS. Results further revealed that as voltage increases from 9.3 V to 11.6 V, the UTS decreases by 2.69 MPa, while YS increases significantly by 24.25 MPa. When the current increases from 30 A to 38 A, the UTS increases by 10.81 MPa, while the YS increases by 4.25 MPa. In the case of the welding speed, an increase from 0.46 to 0.71 mm/s results in a decrease of the UTS by 7.94 MPa and a significant increase of the YS by 33.25 MPa. When the heat input increases from 0.54 to 0.70 kJ/mm, the UTS decreases by 15.06 MPa, whereas the YS decreases significantly by 35.25 MPa. Also, the optimum voltage, current, welding speed and heat input for UTS are 11.60 V, 30.0 A, 0.71 mm/s, and 0.70 kJ/mm, respectively, and those of YS are 9.30 V, 30.0 A, 0.46 mm/s, and 0.70 kJ/mm, respectively.