Gas Metal Arc Welding Parameters Research Articles

Optimization of welding parameters on weld deposits area in pulsed gas metal arc welding

This paper presents a methodology for optimising pulsed gas metal arc welding parameters on Stainless Steel GRADE 410. Most sectors favour the economic welding technique for its favourable outcomes, such as enhanced strength and reduced corrosion. Compared to conventional welding methods, pulsed gas metal arc welding has the advantage of reducing current consumption and increasing the rate at which metal is deposited. An optimisation technique is employed to forecast the weld bead's accurate geometry, penetration depth, and reinforcement height, considering the welding input parameters such as welding speed, current rate, and frequency level. The Taguchi technique uses experimental analysis by considering input and output parameters. A multiple regression analysis model has been developed for SS Grade 410 Stainless steel to determine the bead geometry's correctness.

Specification of the optimal gas metal arc welding (GMAW) parameters to enhance the mild steel strength (MS1018)

Arc fusion processes, such as high-efficiency gas metal arc welding (GMAW), have become increasingly prevalent in various industries. To optimize the GMAW parameters and enhance the strength of MS 1018, Monika and Chauhan conducted experiments using the low carbon steel filler wire (ER 70 S6). They used a Taguchi L9 OA (orthogonal array) to generate test data focusing on 3 GMAW parameters such as gas flow rate, arc voltage, and welding current. The performance characteristics considered were tensile strength (TS), weld zone hardness (WZH), and heat-affected zone hardness (HAZH). The effect of GMAW parameters investigated using the S/N (signal-to-noise ratio) transformation of individual test data, which is valid to account for variations observed in repeated tests. By conducting a thorough analysis of variance (ANOVA) on this transformed data, they were able to identify the optimal GMAW parameters for achieving high TS, WZH, and HAZH. Given that HAZH exhibited higher values than WZH, it was evident that TS had the most significant impact on the GMAW process. Consequently, the researchers established empirical relationships for TS, WZH, and HAZH in terms of the GMAW parameters. Their test data aligned reasonably well with the expected range of performance indicators, supporting the validity of their findings. Overall, Monika and Chauhan’s modified Taguchi approach, based on the L9 OA, allowed them to efficiently conduct a limited number of tests while obtaining comprehensive information on the optimal GMAW parameters for enhancing the strength of MS 1018.

Numerical and experimental investigation for the cladding of AISI 304 stainless steel on mild steel substrate using Gas Metal Arc Welding

In the present study, Gas Metal Arc Welding (GMAW) is used to deposit AISI 304 stainless steel layer on the mild steel substrate. The cladding parameters like welding voltage and feed rate have been varied to identify the deposited AISI 304 stainless steel bead profile and factors affecting the bead deposition on the mild steel substrate. Microscopic and EDS analysis confirms the successful deposition of the stainless steel layer on the mild steel substrate. The GMAW parameters like welding voltage and wire feed rate (WFR) govern the AISI 304 clad bead quality like clad profile, heat affected zone (HAZ), and clad penetration. A numerical model has also been developed using a double ellipsoidal heat source to identify the effect of welding parameters on the clad bead. The developed numerical model identifies the temperature distribution along with the clad bead profile and the model is identical with the experimental results. The experimental results showed that a non-uniform weld bead formation has been observed at lower voltage (14 V) and low WFR (3 m/min). The clad bead quality has improved with an increase in the welding voltage (16 V & 18 V) and wire feed rate (5 m/min & 7 m/min). However, cladding at a high wire feed rate (7 m/min) results in low dilution of the clad material with the substrate.

Hybrid Taguchi Based Grey Algorithm for Multi Objective Optimization of Gas Metal Arc Welded DP1000 Steel

Euro-6 norms for reduction of CO2 emissions and ECE-R66-01 regulation for safer passenger transportation became legislative obligations for bus builders. These two adaptations increase the weight of a bus as nearly 600kg which also increases the fuel consumption nearly 1.5-3%. Dual phase (DP) steels can compensate these increases by decreasing the thickness of the components. Because, ferrite provides the steel with good formability and martensite increases the hardness and ultimate tensile strength in DP steels. This study focused on the multi response hybrid optimization of gas metal arc welding (GMAW) of DP1000 steel to determine the optimal parametric combination which gives the maximum ultimate tensile strength (UTS, MPa) and joint efficiency (JE) under minimum heat input (Q, kj/mm). Nine experimental trials which is based on the orthogonal array suggested by Taguchi method was carried out to investigate objective functions for optimization in the experimental range of GMAW parameters such as voltage (U, volt), welding speed (V, mm/min) and wire feed rate (f, m/min). The Taguchi method continued with Grey Relational Analysis (GRA) to overcome the multi-objective optimization model. Finally, Analysis of variance (ANOVA) method has been used to determine the significance of the welding parameters on the responses of UTS, JE and Q. This shows flexible applicability of Taguchi based GRA to find out the effect of each GMAW process parameters onto individual responses.

Correlation between GMAW Parameters and Mechanical Properties of Hot-Rolled, High-Strength Low-Alloy (HSLA) Steel Butt Joints

In all industrial fields, the product requirements are more and more demanding. HSLA steels are designed to provide higher atmospheric corrosion resistance and improved mechanical properties than structural steels. The paper presents the results of an experimental program based on factorial design, applied to predict the mechanical properties of butt-welded joints of S420MC and S460MC hot-rolled, high-strength low-alloy (HSLA) steel plates with 2mm, 4mm and 8mm thickness. Gas Metal Arc Welding (GMAW) was used and correlations between the main process parameters and the related mechanical properties of the welded joints were found. Obtained mathematical correlations can be exploited to provide optimal combination of welding parameters to fit the quality requirements of the end-users for envisaged welded product.

The Coatings Breakdown Products Influence on the Gas Metal Arc Welding Parameters

The installation and renovation works of steel structures are often performed using gas metal arc welding. Thereby, the welded elements of these structures are frequently protected by a variety of primers and coatings, especially in shipbuilding. Complex nonequilibrium physical and chemical processes occurring under the influence of high temperatures and electric arc discharge, as well as the presence of the products that affect the welding parameters, have a significant impact on the joints’ quality. Experimental studies on the coatings’ breakdown products influence on the gas metal arc welding parameters were performed with epoxy, alkyd, polyacrylate, polyvinyl butyral primers, epoxy zinc filled, vinyl chloride, vinyl isobutyl, and organosilicate coatings. The peculiarity of welding current waveform parameters was studied using oscillograms processing. It was found that the main coatings breakdown products that influence the current waveform are oxygen and carbon monoxide.

Ductility of Welded Joints in CK45 Carbon Steel

The procedure of gas-metal arc welding (GMAW) has received much attention in recent years and has numerous beneficial applications in the industry, including car industry and ship building. It is expected that the GMAW parameters, such as arc voltage, welding current and welding speed, strongly affect the mechanical properties of welded joints. As one of the most important mechanical properties that should be taken into account by designers, we can mention the ductility of welded joint, which can be found as a result of bending tests. Thus, we perform the experimental investigation with an aim to determine the effect of the parameters of robotic GMAW on the ductility of welded joints in CK45 carbon steel. The accumulated results clearly illustrate that the ductility of welded joints is a monotonic function of the welding parameters.

Optimization of Gas Metal Arc Welding (GMAW) Parameters for Minimum Distortion of T Welded Joints of A36 Mild Steel by Taguchi Method

In this study, the GMAW parameters for welding of A36 mild steel have been investigated to get the minimum of distortion. The type of welded joint used was square groove T-joint fillet weld with filler wire ER70S-6. The welding current and the welding speed were selected as input parameters while the response used was distortion (longitudinal bending distortion and angular distortion). Taguchi method was used to determine optimal welding parameters which the minimum distortion. Design of experiment was set two factors with three level in each factor and three replication, so the L9 Taguchi’s orthogonal array was applied. The minimum conditions were determined using S/N ratio with a quality character of smaller is better (SB). In addition, to determine the significance of the welding parameters used ANOVA. The results show that the welding current of 170 A and the welding speed of 4.0 mm/s were obtained as the minimum of longitudinal bending distortion and angular distortion. Based on analysis of variance, the welding current was a parameter that greatly affects the longitudinal bending distortion with the percentage contribution of 64.36% while angular distortion was strongly influenced by welding speed parameter with the percentage contribution of 53.38%.

Gas Metal Arc Welding Parameters Effect on Properties of Tailored Orbital Weld of SS304 and BS1387

Dissimilar material pipes in a power plant boiler water piping system are used to transmit water at various temperatures, either in extremely high temperature water or room temperature water. In this study, tailored orbital welding of dissimilar material of Stainless Steel (SS) 304 and British Steel (BS) 1387 were performed by Gas Metal Arc Welding (GMAW) with automated fixed nozzle-rotational jig. This study focused on GMAW parameters variation effects on mechanical properties of SS304 and BS1387 dissimilar material tailored orbital welding. The weldment quality was tested by performing non-destructive dye penetrant test. The tensile strength and microhardness were studied to verify the influence of welding parameters variations. Design of Experiment (DOE) was employed to generate process parameter using Response Surface Methodology (RSM) method. Welding parameters that were arc current, arc voltage and travel speed as input response, whilst, tensile strength and microhardness as output response. Results from non-destructive test showed no major defect occurred. The tensile strength and microhardness increased when arc current and voltage increased and travel speed decreased. Microhardness at weldment was higher than base material.

Multi-objective optimization of gas metal arc welding parameters and sequences for low-carbon steel (Q345D) T-joints

Q345D high-quality low-carbon steel has been extensively employed in structures with stringent welding quality requirements. A multi-objective optimization of welding stress and deformation was presented to design reasonable values of gas metal arc welding parameters and sequences of Q345D T-joints. The optimized factors included continuous variables (welding current (I), welding voltage (U) and welding speed (v)) and discrete variables (welding sequence (S) and welding direction (D)). The concepts of the pointer and stack in Visual Basic (VB) and the interpolation method were introduced to optimize the variables. The optimization objectives included the different combinations of the angular distortion and transverse welding stress along the transverse and longitudinal distributions. Based on the design of experiments (DOE) and the polynomial regression (PR) model, the finite element (FE) results of the T-joint were used to establish the mathematical models. The Pareto front and the compromise solutions were obtained by using a multi-objective particle swarm optimization (MOPSO) algorithm. The optimal results were validated by the corresponding results of the FE method, and the error between the FE results and the two-objective results as well as that between the FE results and the three-objective optimization results were less than 17.2% and 21.5%, respectively. The influence and setting regularity of different factors were discussed according to the compromise solutions.

Multi-variable measurements and optimization of GMAW parameters for API-X42 steel alloy using a hybrid BPNN–PSO approach

This research addresses multi criteria modeling and optimization procedure for Gas Metal Arc Welding (GMAW) process of API-X42 alloy. Experimental data needed for modeling are gathered as per L36 Taguchi matrix. Model inputs include work piece groove angle as well as the five main GMAW process parameters. The proposed back propagation neural network (BPNN) simultaneously predicts weld bead geometry (WBG) and heat affected zone (HAZ). Image processing technique along with Bridge Cam and AWS gauges are used to take accurate measurements of WBGs and HAZs. The adequacy of the developed BPNN is established through comparisons against measured process outputs. Measurements indicate that the BPNN model simulates GMAW process with average errors of 0.33 to 0.82%. Next, the BPNN model is implanted into a particle swarm optimization (PSO) algorithm to simultaneously optimize HAZ and WBG characteristics. The hybrid BPNN–PSO determines process parameters values and groove angle so as a desired WBG is achieved while HAZ is minimized. Verification tests demonstrate that the proposed BPNN–PSO is quite efficient for in multi-criteria modeling and optimization of GMAW.

The Effects of GMAW Parameters on Penetration, Hardness and Microstructure of AS3678-A350 High Strength Steel

Abstract This research aims to study the effects of various welding parameters in gas metal arc welding (GMAW) process on welding penetration, microstructure and hardness of AS3578-A350 high strength steel with the thickness of 10 mm. The welding process parameters were a welding current of 100-200A, an arc voltage of 20-30V, a welding speed of 20-60 cm/min and a gas shielding type of Ar and Ar+CO 2 . The summarized experimental results are as follows. An increase of the welding current and voltage affected to increase the penetration depth of the joint. However, when the welding speed was decreased, it increased the penetration depth of the joint. Using the Ar gas for shielding the weld area, produced the higher penetration depth and the less narrow weld bead than the joint that was shielded by the mix gas of Ar+CO 2 . The variation of the welding process parameters affected to produce the various microstructures of weld metal and heat affected zone and also showed the various kind of hardness along the weld joint.

Parametric Optimization of Gas Metal Arc Welding Processes by Using Factorial Design Approach

Gas Metal Arc Welding is a process in which the source of heat is an arc format between consumable metal electrode and the work piece with an externally supplied gaseous shield of gas either inert such as argon, helium. This experimental study aims at optimizing various Gas Metal Arc welding parameters including welding voltage, welding current, welding speed and nozzle to plate distance (NPD) by developing a mathematical model for sound weld deposit area of a mild steel specimen. Factorial design approach has been applied for finding the relationship between the various process parameters and weld deposit area. The study revealed that the welding voltage and NPD varies directly with weld deposit area and inverse relationship is found between welding current and speed with weld deposit area.

Prediction of gas metal arc welding parameters based on artificial neural networks

This paper presents a novel technique based on artificial neural networks (ANNs) for prediction of gas metal arc welding parameters. Input parameters of the model consist of gas mixtures, whereas, outputs of the ANN model include mechanical properties such as tensile strength, impact strength, elongation and weld metal hardness, respectively. ANN controller was trained with the extended delta-bar-delta learning algorithm. The measured and calculated data were simulated by a computer program. The results showed that the outcomes of the calculation were in good agreement with the measured data, indicating that the novel technique presented in this work shows the good performance of the ANN model.