Welding Input Parameters Research Articles

Influence of welding conditions on resistance flash welds

The contribution gives an insight into resistance flash welding with emphasis on process dynamics. For the experiments ribbed mild steel concrete reinforcement bars were used with a range of welding parameters used in a normal welding praxis. The welded bars were tested for tensile strength and the results were used to develop a regression model. The model was designed to predict weld piece strength according to input welding parameters. The input welding parameters were: welding force, welding current and welding time.

Modeling and Optimization of Weld Zone Development in Resistance Seam Welding

Resistance Seam Welding (RSEW) is an ideal welding method to produce airtight joints where welding input parameters play a very significant role in determining the quality of weld nugget and heat affected zone (HAZ) formation. This research is aimed to study the nugget and HAZ development of 1 mm low carbon steel using RSEW. Welding parameters such as weld current, weld time, weld speed and pressure were identified and investigated to study their effect on the formation of weld nugget by using 24 factorial designs. The objective of this work is to find the optimum parameter to optimize the width of weld nugget and HAZ in order to obtain a good quality of RSEW. Furthermore the mathematical models were developed to predict the weld zone development. Experimental confirmation test was conducted at an optimal condition for observing accuracy of the developed model. Based on the confirmation test, the proposed method can be effectively used to predict the size of weld zone which can improve the welding quality and performance in RSEW.

Simulation and parameter optimization of flux cored arc welding using artificial neural network and particle swarm optimization algorithm

Flux cored arc welding (FCAW) process is a fusion welding process in which the welding electrode is a tubular wire that is continuously fed to the weld area. It is widely used in industries and shipyards for welding heavy plates. Welding input parameters play a very significant role in determining the quality of a weld joint. This paper addresses the simulation of weld bead geometry in FCAW process using artificial neural networks (ANN) and optimization of process parameters using particle swarm optimization (PSO) algorithm. The input process variables considered here include wire feed rate (F); voltage (V); welding speed (S) and torch Angle (A) each having 5 levels. The process output characteristics are weld bead width, reinforcement and depth of penetration. As per the statistical design of experiments by Taguchi L25 orthogonal array, bead on plate weldments were made. The experimental results were fed to the ANN algorithm for establishing a relationship between the input and output parameters. The results were then embedded into the PSO algorithm which optimizes the process parameters subjected to the objectives. In this study the objectives considered are maximization of depth of penetration, minimization of bead width and minimization of reinforcement.

Review on Application of Response Surface Method based Design of Experiments to Welding Processes

Abstract Design of Experiment is one of the extensively used method for experimental study of many manufacturing processes in engineering. In welding, Design of Experiments are widely used to develop a mathematical relationship between the welding input parameters and the output variables of the weld joint in order to determine the welding input parameters that lead to the desired weld quality. In the present study, a review is made on Response Surface Method based Design of Experiments that have been employed for various welding processes by other researchers. This study predominantly focuses on the usage of Response Surface Method in Welding.

Optimal design for laser beam butt welding process parameter using artificial neural networks and genetic algorithm for super austenitic stainless steel

Laser welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. Therefore, mechanical properties should be controlled to obtain good welded joints. In this study, the weld bead geometry such as depth of penetration (DP), bead width (BW) and tensile strength (TS) of the laser welded butt joints made of AISI 904L super austenitic stainless steel were investigated. Full factorial design was used to carry out the experimental design. Artificial Neural networks (ANN) program was developed in MatLab software to establish the relationships between the laser welding input parameters like beam power, travel speed and focal position and the three responses DP, BW and TS in three different shielding gases (Argon, Helium and Nitrogen). The established models were used for optimizing the process parameters using Genetic Algorithm (GA). Optimum solutions for the three different gases and their respective responses were obtained. Confirmation experiment has also been conducted to validate the optimized parameters obtained from GA.

Flux Cored Arc Welding Parameter Optimization Using Particle Swarm Optimization Algorithm

Flux cored arc welding (FCAW) process is a fusion welding process in which the welding electrode is a tubular wire that is continuously fed to the weld area. It is widely used in industries and shipyards for welding heavy plates. Welding input parameters play a very significant role in determining the quality of a weld joint. This paper addresses the modeling of welding parameters in FCAW process using a set of experimental data and regression analysis, and optimization using Particle Swarm Optimization (PSO) Algorithm. The input process variables considered here include wire feed rate (F); voltage (V); welding speed (S) and torch Angle (A) each having 5 levels. The process output characteristics are weld bead width, reinforcement and depth of penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. In the next stage, the proposed model is embedded into PSO algorithm to optimize the FCAW process parameters. In this study the objectives considered are maximization of depth of penetration, minimization of bead width and minimization of reinforcement. A comparative study on the effectiveness of the two algorithms on the optimization of the weld bead geometry is done

Optimization of laser welding process parameters for super austenitic stainless steel using artificial neural networks and genetic algorithm

The laser welding input parameters play a very significant role in determining the quality of a weld joint. The quality of the joint can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. In particular mechanical properties should be controlled to obtain good welded joints. In this study, the weld bead geometry such as depth of penetration (DP), bead width (BW) and tensile strength (TS) of the laser welded butt joints made of AISI 904L super austenitic stainless steel are investigated. Full factorial design is used to carry out the experimental design. Artificial neural networks (ANNs) program was developed in MatLab software to establish the relationship between the laser welding input parameters like beam power, travel speed and focal position and the three responses DP, BW and TS in three different shielding gases (argon, helium and nitrogen). The established models are used for optimizing the process parameters using genetic algorithm (GA). Optimum solutions for the three different gases and their respective responses are obtained. Confirmation experiment has also been conducted to validate the optimized parameters obtained from GA.

Systematic Examination of Precipitation Phenomena Associated With Hardness and Corrosion Properties in Friction Stir Welded Aluminium Alloy 2024

The mechanical and corrosion properties of friction-stir welded, precipitation hardenable, AA2024 strongly depend on the volume fraction, size and distribution of the strengthening precipitates, and thus it is necessary to precisely understand the relationship between these properties and the precipitate distribution to improve the properties of the weld. In the present study, the hardness profile and the corrosion properties were systematically correlated with the precipitate distribution in AA2024-T4 friction stir (FS) welded at different welding parameters. The hardness profile of the weld could be explained by the density of GPB zones. Two hardness reduction regions were found in the HAZ. One was characterized by overageing and the other by the absence of precipitates. Overageing could be effectively suppressed by using low heat input welding parameters. The weld had a region with lower corrosion resistance in the HAZ proximal to the stir zone, which was due to presence of many S phases. It is suggested that the corrosion was attributable to the dissolution of S (S′) phases during the corrosion tests of AA2024. Reduction of the hardness and the corrosion resistance in the HAZ could be alleviated by a decrease in heat input during FSW.

Modeling of Weld Dilution in Gas Metal Arc Welding Process Using Taguchi's Design of Experiments

Gas metal arc welding is a fusion welding process which has got wide applications in industry. In order to obtain a good quality weld, it is therefore, necessary to control the input welding parameters. In other words proper selection of input welding parameters in this process contribute to weld productivity. One of the important welding output parameters in this process is weld dilution affecting the quality and productivity of weldment. In this research paper using Taguchi method of design of experiments a mathematical model was developed using parameters such as, wire feed rate (W), welding voltage (V), nozzle-to-plate distance (N), welding speed (S) and gas flow rate (G) on weld dilution. After collecting data, signal-to-noise ratios (S/N) were calculated and used in order to obtain the optimum levels for every input parameter. Subsequently, using analysis of variance the significant coefficients for each input factor on the weld dilution were determined and validated. Finally a mathematical model based on regression analysis for predicting the weld dilution was obtained. Results show that wire feed rate (W),arc voltage (V) have increasing effect while Nozzle-to-plate distance (N) and welding speed (S) have decreasing effect on the dilution whereas gas Flow rate alone has almost no effect on dilution but its interaction with other parameters makes it quite significant in increasing the weld dilution

Microsegregation-related pitting corrosion characteristics of AL-6XN superaustenitic stainless steel laser welds

Pitting corrosion resistance of laser welds of AL-6XN superaustenitic stainless steel (SASS) was investigated in acidic chloride ion medium. It was found that the critical pitting temperature (CPT) of the laser welds increased with increasing welding speed or decreasing laser power. Pitting attack preferentially occurred at selective dendrite cores of the laser welds. Analytical electron microscope (AEM) microanalysis revealed that depletion of Mo at dendrite cores due to microsegregation is the basic cause for the pitting corrosion susceptibility. The higher partition coefficient k Mo and Mo concentration at dendrite cores of laser welds were attributed to the lower heat input welding parameters.

Some studies on the electromagnetic aspects governing the magnetically impelled arcs through experimentation, finite element simulation and statistical analysis

In this study, Magnetically Impelled Arc Butt welding (MIAB) laboratory setup for welding carbon steel tubes of small wall thickness is designed and developed. Magnetically Impelled Arc Butt welding is an efficient two phase process which is used in highly automated factory production lines in high volume industries such as automotive manufactures. In this process, an electric arc generated between aligned and properly gapped pipes are made to rotate along the peripheral butt ends. This arc swiftly rotates along the peripheral edges of the tubes to be welded due to the electromagnetic force resulting from the interaction of the arc current and the externally controlled magnetic field created by magnetic systems. The arc acts as a heating source providing the required heat to the butt ends of the pipes. Further an application of force on the pipe along the axial direction sets the weld. The electromagnetic force responsible for the arc rotation is governed by the magnetic flux density in the gap, the arc current and the arc length (gap size). To be precise the radial magnetic flux density is a critical factor in arc rotation and weld quality. Preliminary trials are conducted to understand the process parameters. Tubes with 45 mm Outer Diameter with 3 mm thickness are used for conducting the investigations. Further, for the first time an attempt is made to analyze the effects of weld input parameters such as welding current, welding voltage, magnetic coil voltage and magnetic coil current on the arc speed in MIAB welding process using software package STATA. The aim of this study also is to explore the distribution of the magnetic flux density in the tube gap region using finite element code ANSYS .The analysis emphasizes that the most significant factor that governs the arc speed is magnetic coil current (that creates magnetic flux density) and the welding current.

Estimation and optimization of depth of penetration in hybrid CO2 LASER-MIG welding using ANN-optimization hybrid model

The paper presents an artificial neural network-optimization hybrid model to predict and optimize penetration depth of CO2 LASER-MIG hybrid welding used for 5005 Al–Mg alloy. The input welding parameters are power, focal distance from the work piece surface, torch angle, and the distance between the laser and the welding torch. The model combines single hidden layer back propagation artificial neural networks (ANN) with Bayesian regularization for prediction and quasi-Newton search algorithm for optimization. In this method, training and prediction performance of different ANN architectures are initially tested, and the architecture with the best performance is further used for optimization. Finally, the best ANN architecture is found to show much better prediction capability compared to a regression model developed from the experimental data.

Prediction of weld strength and seam width for laser transmission welding of thermoplastic using response surface methodology

In the present work, a study is made to investigate the effects of process parameters, namely, laser power, welding speed, size of the laser beam and clamp pressure, on the lap-shear strength and weld-seam width for laser transmission welding of acrylic (polymethyl methacrylate), using a diode laser system. Response surface methodology (RSM) is employed to develop mathematical relationships between the welding process parameters and the output variables of the weld joint to determine the welding input parameters that lead to the desired weld quality. In addition, using response surface plots, the interaction effects of process parameters on the responses are analyzed and discussed. The statistical software Design-Expert v7 is used to establish the design matrix and to obtain the regression equations. The developed mathematical models are tested by analysis-of-variance (ANOVA) method to check their adequacy. Finally, a comparison is made between measured and calculated results, which are in good agreement. This indicates that the developed models can predict the responses adequately within the limits of welding parameters being used.

DCフラッシュ熱間溶接プロセスの加熱機構について

It hasn't been well known which heat of joule and arc discharge is dominant factor in flash welding process. The objective of this study is to clarify heating mechanism of flashing. The flashing is a cycle consisting of local contact, joule heating, melting, spattering and arc discharge. Numerical model of flashing cycles was developed by assuming initial contact conditions. It has been evaluated heat input and welding parameters of DC flash welding. As the results, arc discharge heat is higher than joule heat for a wide range of flash current. Optimum flashing of DC is large contact and low frequency compared with general continuous flashing of AC. Heat input and platen velocities are 50% higher than those of AC at the same conditions and welding quality. The calculated velocities and crater depth of DC flashing are in good agreement with hot-billets welding data. It was found that DC flash welding compares very favorably with AC for short-time welding.

Optimization of different welding processes using statistical and numerical approaches – A reference guide

Welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld-bead geometry, mechanical properties, and distortion. Generally, all welding processes are used with the aim of obtaining a welded joint with the desired weld-bead parameters, excellent mechanical properties with minimum distortion. Nowadays, application of design of experiment (DoE), evolutionary algorithms and computational network are widely used to develop a mathematical relationship between the welding process input parameters and the output variables of the weld joint in order to determine the welding input parameters that lead to the desired weld quality. A comprehensive literature review of the application of these methods in the area of welding has been introduced herein. This review was classified according to the output features of the weld, i.e. bead geometry and mechanical properties of the welds.

Residual Stresses Prediction for CO<sub>2</sub> Laser Butt-Welding of 304-Stainless Steel

Residual stresses are an integral part of the total stress acting on any component in service. It is important to determine and/or predict the magnitude, nature and direction of the residual stress to estimate the life of important engineering parts, particularly welded components. This work aims to introduce experimental models to predict residual stresses in the heat-affected zone (HAZ). These models specify the effect of laser welding input parameters on maximum residual stress and its direction. The process input variables considered in this study are laser power (1.03 - 1.368 kW), travel speed (26.48 – 68.52 cm/min) and focal point position (- 1 to 0 mm). Laser butt-welding of 304 stainless steel plates of 3 mm thick were investigated using a 1.5 kW CW CO2 Rofin laser as a welding source. Hole-drilling method was employed to measure the magnitude, and direction of the maximum principal stress in and around the HAZ, using a CEA-06- 062UM-120 strain gauge rosette, which allows measurement of the residual stresses close to the weld bead. The experiment was designed based on Response Surface Methodology (RSM). Fifteen different welding conditions plus 5 repeat tests were carried out based on the design matrix. Maximum principal residual stresses and their directions were calculated for the twenty samples. The stepwise regression method was selected using Design-expert software to fit the experimental responses to a second order polynomial. Sequential F test and other adequacy measures were then used to check the models adequacy. The experimental results indicate that the proposed mathematical models could adequately describe the residual stress within the limits of the factors being studied. Using the models developed, the main and interaction effect of the process input variables on the two responses were determined quantitatively and presented graphically. It is observed that the travel speed and laser power are the main factors affecting the behavior of the residual stress. It is recommended to use the models to find the optimal combination of welding conditions that lead to minimum distortion.

Improving reliability of modelling heat and fluid flow in complex gas metal arc fillet welds—part II: application to welding of steel

In order to improve the reliability of numerical calculations of heat and fluid flow in fusion welding, a model was proposed in part I of this paper to determine the uncertain welding input parameters from a limited volume of experimental data. The application of the model for the complex gas metal arc (GMA) fillet welding of mild steel is reported in this part of the paper. The values of the arc efficiency, effective thermal conductivity and effective viscosity were evaluated as a function of the heat input. A vorticity-based mixing-length hypothesis was also used to independently calculate the values of the effective viscosity and effective thermal conductivity. Good agreement was obtained between the values of these parameters calculated using the two techniques, indicating the effectiveness of the proposed model in improving the reliability of heat and fluid flow calculations in fusion welding. The shape and size of the fusion zone, finger penetration characteristic of the GMA welds and solidified free surface profile computed using the optimized values of the uncertain welding parameters were in fair agreement with the corresponding experimental results for various welding conditions. In particular, the computed values of the leg length, the penetration depth and the actual throat agreed well with those measured experimentally for various heat inputs.

A Software System for Determining the Preheat Temperature Required to Avoid Underbead Cracking—I

AbstractA software system for determining the preheat temperature required to avoid underbead cold cracking, given the input welding parameters (voltage, current, welding speed, thermal efficiency), base metal chemical composition, joint restraint and preparation, hydrogen level and preheat parameters, is presented. The system is based on a materials model originally proposed by Yurioka and co-workers and the heat transfer algorithm of Satoh and Matsui. Of central importance in designing the software is ease of use. For an engineer familiar with materials/welding technology but only a basic familiarity with microcomputers, the system is self evident without the necessity of written manuals or extensive help menus. To achieve this, a special user interface suitable for materials or welding engineers is presented. Furthermore, automated plotting and a simple database system are also included for the convenience of practitioners. While the software system presented in this work is focused on preheat temperat...

Effects of welding residual stresses on fatigue crack growth behaviour in butt welds of a pipeline steel: Shi, Y.W., Chen, B.Y. and Zhang, J.X. Eng. Fract. Mech. 1990 36 (6), 893–902

Welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld-bead geometry, mechanical properties, and distortion. Generally, all welding processes are used with the aim of obtaining a welded joint with the desired weld-bead parameters, excellent mechanical properties with minimum distortion.Nowadays, application of design of experiment (DoE), evolutionary algorithms and computational network are widely used to develop a mathematical relationship between the welding process input parameters and the output variables of the weld joint in order to determine the welding input parameters that lead to the desired weld quality. A comprehensive literature review of the application of these methods in the area of welding has been introduced herein. This review was classified according to the output features of the weld, i.e. bead geometry and mechanical properties of the welds.

Towards a prediction of the hardness of the heat-affected zone of steel weldments

The prediction of the level of hardness developed in the heat-affected zone (HAZ) of steel welds is discussed. It is composed of a thermal model that predicts the cooling behaviour from input welding parameters and a material model for calculating the HAZ hardness as a result of weld cooling. Experimental investigations were carried out on eight different steel welds using three different electrodes under two different welding processes. Comparisons of the experimental results as well as the experimental results reported in the open literature, against the calculated values for both HAZ hardness and cooling time, were conducted. The results presented in this paper show good agreement between calculated and measured values of both cooling rate and hardness. The calculations can be carried out readily in small pocketsized computers.