Application of Taguchi philosophy for parametric optimization of bead geometry and HAZ width in submerged arc welding using a mixture of fresh flux and fused flux

Taguchi philosophy has been applied for obtaining optimal parametric combinations to achieve desired weld bead geometry and dimensions related to the heat-affected zone (HAZ), such as HAZ width in the present case, in submerged arc welding. The philosophy and methodology proposed by Dr. Genichi Taguchi can be used for continuous improvement in products that are produced by submerged arc welding. This approach highlights the causes of poor quality, which can be eliminated by self-adjustment among the values of the process variables if they tend to change during the process. Depending on functional requirements of the welded joint, an acceptable weldment should confirm maximum penetration, minimum reinforcement, minimum bead width, minimum HAZ width, minimum bead volume, etc. to suit its area of application. Hence, there exists an increasing demand to evaluate an optimal parameter setting that would fetch the desired yield. This could be achieved by optimization of welding variables. Based on Taguchi’s approach, the present study has been aimed at integrating statistical techniques into the engineering process. Taguchi’s L9 (3**3) orthogonal array design has been adopted and experiments have been accordingly conducted with three different levels of conventional process parameters using welding current and flux basicity index to obtain bead-on-plate weld on mild steel plates. Features of bead geometry and HAZ in terms of bead width, reinforcement, depth of penetration and HAZ width have been measured for each experimental run. The slag, generated during welding, has been consumed in further runs by mixing it with fresh unmelted flux. The percentage of slag in the mixture of fused flux (slag) and fresh flux has been defined as slag-mix%. Welding has been performed by using varying slag-mix%, treated as another process variable, in order to obtain the optimum amount of slag-mix that can be used without any alarming adverse effect on features of bead geometry and HAZ. This would lead to ‘waste to wealth’.     

Solving multi-criteria optimization problem in submerged arc welding consuming a mixture of fresh flux and fused slag

In the present work, application of the Taguchi method in combination with grey relational analysis has been applied for solving multiple criteria (objective) optimization problem in submerged arc welding (SAW). A grey relational grade evaluated with grey relational analysis has been adopted to reveal an optimal parameter combination in order to obtain acceptable features of weld quality characteristics in submerged arc bead-on-plate welding. The idea of slag utilization, in subsequent runs, after mixing it with fresh unmelted flux, has been introduced. The parentage of slag in the mixture of fresh flux and fused flux (slag) has been denoted as slag-mix%. Apart from two conventional process parameters: welding current and flux basicity index, the study aimed at using varying percentages of slag-mix, treated as another process variable, to show the extent of acceptability of using slag-mix in conventional SAW processes, without sacrificing any characteristic features of weld bead geometry and HAZ, within the experimental domain. The quality characteristics associated with bead geometry and HAZ were bead width, reinforcement, depth of penetration and HAZ width. Using grey relational grade as performance index, we have performed parametric optimization yielding the desired features of bead geometry and HAZ. Predicted results have been verified with confirmatory experiments, showing good agreement. This proves the utility of the proposed method for quality improvement in SAW process and provides the maximum (optimum) amount of slag-mix that can be consumed in the SAW process without any negative effect on characteristic features of the quality of the weldment in terms of bead geometry.     

Development of mathematical model with a genetic algorithm for automatic GMA welding process

Gas metal arc (GMA) welding process has widely been employed due to the wide range of applications, cheap consumables, and easy handling. In order to achieve a high level of welding performance and quality, a suitable model is required to investigate the characteristics of the effects of process parameters on the bead geometry in the GMA welding process. This paper is to represent new algorithms to predict process parameters on top-bead width in robotic GMA welding process. The models have been developed, linear, curvilinear, and intelligent model, based on full factorial design with two replications. Regression analysis was employed for optimization of the coefficients of linear and curvilinear models, while genetic algorithm (GA) was utilized to estimate the coefficients of an intelligent model. Not only the fitting of these models was checked and compared by using a variance test (analysis of variance (ANOVA)) but also the prediction on top-bead width using the developed models was carried out based on the additional experiments. The developed models were employed to investigate the characteristic between process parameters and top-bead width. Resulting solutions and graphical representation showed that the intelligent model developed can be employed for prediction of bead geometry in GMA welding process.     

Slag recycling in submerged arc welding and its influence on weld quality leading to parametric optimization

Slag generated during conventional submerged arc welding (SAW) has been recycled by mixing varying percentages of crushed slag with fresh flux to use in subsequent runs. The influence of using flux-slag mixture on various aspects of SAW weld parameters of bead geometry have been investigated in a quantitative basis. Slag has been reprocessed and reused in submerged arc welding to produce bead-on-plate weld on mild steel plates. Apart from conventional process parameters: voltage (OCV), wire feed rate, nozzle to plate distance (stick-out) and traverse speed, welding has been carried out using various percentages of flux-slag mixture; the % of fused flux in the mixture has been treated as a process parameter. Various bead geometry parameters viz. bead width; reinforcement, depth of penetration and depth of HAZ have been measured for each of weld prepared in the study. Using experimental data, a grey-based Taguchi approach has been applied for parametric optimization of this non-conventional SAW process. The aim was to reveal the optimal amount of slag-mix%, which could be applied in SAW process without imposing any adverse effect on features of bead geometry and HAZ. Optimal result has been checked through confirmatory test.     

An application of genetic algorithm for edge detection of molten pool in fixed pipe welding

This paper presents a study on an application of genetic algorithm (GA) for edge detection of molten pool in fixed pipe welding. As circumferential butt-welded pipes are frequently used in power stations, offshore structures, and process industries, it is important to investigate the characteristic of the welding process. In pipe welding using constant arc current and welding speed, the bead width becomes wider as the circumferential welding of small-diameter pipes progresses. In order to avoid the errors and to maintain the uniform weld bead over the entire circumference of the pipe, the welding conditions should be controlled as the welding proceeds. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position using the AC welding machine. The monitoring system used an omnidirectional camera to monitor backside image of molten pool. A method of optimization for image processing algorithm using GA was proposed and has been implemented into a process to recognize the edge of molten pool. The result of detection, which is back bead width, was delivered into a fuzzy inference system to control welding speed. The experimental results show the effectiveness of the control system that is confirmed by a sound weld of the experimental results.     

Genetic algorithm based optimization of the process parameters for gas metal arc welding of AISI 904 L stainless steel

The present study is focused on welding of super austenitic stainless steel sheet using gas metal arc welding process with AISI 904 L super austenitic stainless steel with solid wire of 1.2 mm diameter. Based on the Box — Behnken design technique, the experiments are carried out. The input parameters (gas flow rate, voltage, travel speed and wire feed rate) ranges are selected based on the filler wire thickness and base material thickness and the corresponding output variables such as bead width (BW), bead height (BH) and depth of penetration (DP) are measured using optical microscopy. Based on the experimental data, the mathematical models are developed as per regression analysis using Design Expert 7.1 software. An attempt is made to minimize the bead width and bead height and maximize the depth of penetration using genetic algorithm.     

Optimization of pulsed GTA welding process parameters for the welding of AISI 304L stainless steel sheets

Optimization of pulsed gas tungsten arc welding (pulsed GTAW) process parameters was carried out to obtain optimum weld bead geometry with full penetration in welding of stainless steel (304L) sheets of 3 mm thickness. Autogenuous welding with square butt joint was employed. Design of experiments based on central composite rotatable design was employed for the development of a mathematical model correlating the important controllable pulsed GTAW process parameters like pulse current (I _p), pulse current duration (T _p), and welding speed (S) with weld bead parameters such as penetration, bead width (W), aspect ratio (AR), and weld bead area of the weld. The developed models were checked for adequacy based on ANOVA analysis and accuracy of prediction by conducting a confirmation test. Weld bead parameters predicted by the models were found to confirm observed values with high accuracy. Using these models, the main and interaction effects of pulsed GTAW process parameters on weld bead parameters were studied and discussed. Optimization of pulsed GTAW process parameters was carried out to obtain optimum bead geometry using the developed models. A quasi-Newton numerical optimization technique was used to solve the optimization problem and the results of the optimization are presented.     

Study on arc characteristics and their influences on weld bead geometry in narrow gap GMAW of 5083 Al-alloy

As an efficient process, narrow gap gas metal arc welding (NG-GMAW) was employed to join thick plates of 5083 Al-alloy. In this paper, arc characteristics in NG-GMAW of 5083 Al-alloy and their influence on the weld bead geometry were studied with synchronous acquisition system for various groove types, welding modes, welding current levels, and swing frequencies. The arc profiles were measured and appear to be entirely different compared with that in bead-on-plate GMAW process, meanwhile the arc size changes with varied welding mode, welding current, and arc swing frequency. Arc characteristics highly affect the weld bead geometrical parameters such as bead width, welding penetration, sidewall penetration, and weld surface concavity. Linear regressions were made between the arc characteristics and the weld bead geometrical parameters both in swing and non-swing arc process. It showed that a negative linear correlation exists between welding penetration and arc length, sidewall penetration, and arc warpage, while a positive linear correlation exists between weld surface concavity and arc warpage in non-swing arc process. In contrast, a non-linear correlation exists among them and the variation tendency remains the same in swing arc process.     

Joining different metallic sheets without protrusion by flat hole clinching process

In this paper, we propose an architecture based on an artificial neural network (ANN), to learn welding skills automatically in industrial robots. With the aid of an optic camera and a laser-based sensor, the bead geometry (width and height) is measured. We propose a real-time computer vision algorithm to extract training patterns in order to acquire knowledge to later predict specific geometries. The proposal is implemented and tested in an industrial KUKA KR16 robot and a GMAW type machine within a manufacturing cell. Several data analysis are described as well as off-line and on-line training, learning strategies, and testing experimentation. It is demonstrated during our experiments that, after learning the skill, the robot is able to produce the requested bead geometry even without any knowledge about the welding parameters such as arc voltage and current. We implemented an on-line learning test, where the whole experiments and learning process take only about 4 min. Using this knowledge later, we obtained up to 95 % accuracy in prediction.     

Modeling and optimization of features of bead geometry including percentage dilution in submerged arc welding using mixture of fresh flux and fused slag

Quality has now become an important issue in today’s manufacturing world. Whenever a product is capable of conforming to desirable characteristics that suit its area of application, it is termed as high quality. Therefore, every manufacturing process has to be designed in such a way that the outcome would result in a high quality product. The selection of the manufacturing conditions to yield the highest desirability can be determined through process optimization. Therefore, there exists an increasing need to search for the optimal conditions that would fetch the desired yield. In the present work, we aim to evaluate an optimal parameter combination to obtain acceptable quality characteristics of bead geometry in submerged arc bead-on-plate weldment on mild steel plates. The SAW process has been designed to consume fused flux/slag, in the mixture of fresh flux. Thus, the work tries to utilize the concept of ‘waste to wealth’. Apart from process optimization, the work has been initiated to develop mathematical models to show different bead geometry parameters, as a function of process variables. Hence, optimization has been performed to determine the maximum amount of slag--flux mixture that can be used without sacrificing any negative effect on bead geometry, compared to the conventional SAW process, which consumes fresh flux only. Experiments have been conducted using welding current, slag-mix percentage and flux basicity index as process parameters, varied at four different levels. Using four³ full factorial designs, without replication, we have carried out welding on mild steel plates to obtain bead-on-plate welds. After measuring bead width, depth of penetration and reinforcement; based on simple assumptions on the shape of bead geometry, we calculated other relevant bead geometry parameters: percentage dilution, weld penetration shape factor, weld reinforcement form factor, area of penetration, area of reinforcement and total bead cross sectional area. All these data have been utilized to develop mathematical models between predictors and responses. Response surface methodology (RSM), followed by the multiple linear regression method, has been applied to develop these models. The effects of selected process parameters on different responses have been represented graphically. Finally grey relational analysis coupled with the Taguchi method (with Taguchi’s orthogonal array) has been applied for parametric optimization of this welding technique. Confirmatory experiments have been conducted to verify optimal results.     

Development of an Intelligent System for Selection of the Process Variables in Gas Metal Arc Welding Processes

Gas metal arc (GMA) welding is extensively employed in the metal industries for a variety of ferrous and non-ferrous metals because of its potential for increasing the productivity and quality of welding which is controlled by the process parameters. The objective of this paper is to develop an algorithm that enables the determination of process variables for optimised bead geometry for robotic GMA welding. It depends on the inversion of empirical Eq. derived from multiple regression analysis of the relationships between the process variables and the bead dimensions using the least-squares method. The method determines directly those variables which will give the desired set of bead geometry. This avoids the need to iterate by a succession of guesses which are employed in the finite element method (FEM). These results suggest that process variables from experimental equations for robotic GMA welding may be employed to monitor and control the bead geometry in real-time.     

Autonomous seam acquisition and tracking system for multi-pass welding based on vision sensor

Automatic welding technology is a solution to increase welding productivity and improve welding quality, especially in thick plate welding. In order to obtain high-quality multi-pass welds, it is necessary to maintain a stable welding bead in each pass. In the multi-pass welding, it is difficult to obtain a stable weld bead by using a traditional teaching and playback arc welding robot. To overcome these traditional limitations, an automatic welding tracking system of arc welding robot is proposed for multi-pass welding. The developed system includes an image acquisition module, an image processing module, a tracking control unit, and their software interfaces. The vision sensor, which includes a CCD camera, is mounted on the welding torch. In order to minimize the inevitable misalignment between the center line of welding seam and the welding torch for each welding pass, a robust algorithm of welding image processing is proposed, which was proved to be suitable for the root pass, filling passes, and the cap passes. In order to accurately track the welding seam, a Fuzzy-P controller is designed to control the arc welding robot to adjust the torch. The Microsoft Visual C++6.0 software is used to develop the application programs and user interface. The welding experiments are carried out to verify the validity of the multi-pass welding tracking system.     

Optimization of Inconel 718 alloy welds in an activated GTA welding via Taguchi method, gray relational analysis, and a neural network

The purpose of this work is to optimize the weld bead geometry of Inconel 718 alloy gas tungsten arc (GTA) welds that are coated with activating flux before welding. In order to obtain the optimal welding parameters with multiple quality characteristics (QCs) such as penetration and depth-to-width ratio (DWR) of weld bead, the Taguchi method (TM), gray relational analysis (GRA), and a neural network (NN) are employed in this work. The TM is first used to construct a database for the NN. The GRA is adopted to solve the problem of multiple QCs. The gray relational grade (GRG) obtained from the GRA is used as the output of the backpropagation (BP) NN. Then, a NN with the Levenberg–Marquardt BP (LMBP) algorithm is used to provide the nonlinear relationship between welding parameters and GRG of each specimen. The optimal parameters of the activated GTA welding process are determined by simulating parameters using a well-trained BPNN model. The experimental procedure of the proposed approach not only improves the DWR of weld bead but also increases the penetration of Inconel 718 alloy welds.     

Processing parameter optimization of fiber laser beam welding using an ensemble of metamodels and MOABC

In fiber laser beam welding (LBW), the selection of optimal processing parameters is challenging and plays a key role in improving the bead geometry and welding quality. This study proposes a multi-objective optimization framework by combining an ensemble of metamodels (EMs) with the multi-objective artificial bee colony algorithm (MOABC) to identify the optimal welding parameters. An inverse proportional weighting method that considers the leave-one-out prediction error is presented to construct EM, which incorporates the competitive strengths of three metamodels. EM constructs the correlation between processing parameters (laser power, welding speed, and distance defocus) and bead geometries (bead width, depth of penetration, neck width, and neck depth) with average errors of 10.95%, 7.04%, 7.63%, and 8.62%, respectively. On the basis of EM, MOABC is employed to approximate the Pareto front, and verification experiments show that the relative errors are less than 14.67%. Furthermore, the main effect and the interaction effect of processing parameters on bead geometries are studied. Results demonstrate that the proposed EM-MOABC is effective in guiding actual fiber LBW applications.     

Effect of process parameters and mathematical model for the prediction of bead geometry in pulsed GMA welding

Pulsed gas metal arc welding is one of the most widely used processes in the industry. It offers spray metal transfer at low average currents, high metal deposition rate, versatility, less distortion, and the ability to be used in automated robotic welding systems. The weld bead plays an important role in determining the mechanical properties of the weld. Its geometric parameters, viz., width, reinforcement height, and penetration, are decided according to the welding process parameters, such as wire feed rate, welding speed, pulse current magnitude, frequency (cycle time), etc. Therefore, to produce good weld bead geometry, it is important to set the proper welding process parameters. In the present paper, mathematical models that correlate welding process parameters to weld bead geometry are developed with experimental investigation. Taguchi methods are applied to plan the experiments. Five process parameters, viz., wire feed rate, plate thickness, pulse frequency, pulse current magnitude, and travel speed, are selected to develop the models using multiple regression analysis. The models developed were checked for their adequacy. Results of confirmation experiments show that the models can predict the bead geometry with reasonable accuracy.     

Optimization of flux-cored arc welding process parameters by using genetic algorithm

The effect of flux-cored arc welding (FCAW) process parameters on the quality of the super duplex stainless steel (SDSS) claddings can be studied using Taguchi L9 design of experiments. In this experimental investigation, deposits were made with 30 % bead overlap. Establishing the optimum combination of process parameters is required to ensure better bead geometry and desired properties. The above objectives can be achieved by identifying the significant input process parameters as input to the mathematical models like welding voltage (X ₁), wire feed rate (X ₂), welding speed (X ₃), and nozzle-to-plate distance (X ₄). The identified responses governing the bead geometry are bead width (W) and height of the reinforcement (H). The mathematical models were constructed using the data collected from the experiments based on Taguchi L9 orthogonal array. Then, the responses were optimized using non-traditional nature-inspired technique like genetic algorithm (GA).     

Modeling of transport phenomena and solidification cracking in laser spot bead-on-plate welding of AA6063-T6 alloy. Part I—the mathematical model

In this work, the oscillating arc narrow gap all-position gas metal arc (GMA) welding process was developed to improve efficiency and quality in the welding of thick-walled pipes. The statistical models of narrow gap all-position GMA weld bead geometry were developed using response surface methodology (RSM) based on central composite design (CCD). The developed models were checked for their adequacy and significance by ANOVA, and the effects of wire feed rate, travel speed, dwell time, oscillating amplitude and welding position on weld bead dimension were studied. Finally, the optimal welding parameters at welding positions of 0° to 180° were obtained by numerical optimization using RSM.     

全数字大功率交流脉冲埋弧焊接电源

为改善埋弧焊的焊接质量,结合脉冲焊接和交流焊接两者优势,提出一种交流脉冲埋弧焊焊接方法,并研制了一台大功率交流脉冲埋弧焊接电源。功率变换电路采用双主电路并联设计,可实现1 250 A交流脉冲电流输出;主电路次级采用耦合电感结构,加快交流过零点速度并提高极性切换时的电弧稳定性;搭建了以STM32F405RGT6芯片为核心的数字化控制系统,通过多特性数字均流策略实现了双主电路的可靠均流和多种电流波形的平稳输出,采用分离式增量PID算法进一步提升动态响应性能。工艺试验结果表明,在同等的焊接条件和交流参数下,交流脉冲埋弧焊比交流方波埋弧焊可获得更深的熔深、更宽的熔宽以及更细化的焊缝晶粒。     

Welding polarity effects on weld spatters and bead geometry of hyperbaric dry GMAW

Welding polarity has influence on welding stability to some extent, but the specific relationship between welding polarity and weld quality has not been found, especially under the hyperbaric environment. Based on a hyperbaric dry welding experiment system, gas metal arc welding(GMAW) experiments with direct current electrode positive(DCEP) and direct current electrode negative(DCEN) operations are carried out under the ambient pressures of 0.1 MPa, 0.4 MPa, 0.7 MPa and 1.0 MPa to find the influence rule of different welding polarities on welding spatters and weld bead geometry. The effects of welding polarities on the weld bead geometry such as the reinforcement, the weld width and the penetration are discussed. The experimental results show that the welding spatters gradually grow in quantity and size for GMAW with DCEP, while GMAW with DCEN can produce fewer spatters comparatively with the increase of the ambient pressure. Compared with DCEP, the welding current and arc voltage waveforms for DCEN is more stable and the distribution of welding current probability density for DCEN is more concentrated under the hyperbaric environment. When the ambient pressure is increased from 0.1 MPa to 1.0 MPa, the effects of welding polarities on the reinforcement, the weld width and the penetration are as follows: an increase of 0.8 mm for the weld reinforcement is produced by GMAW with DCEN and 1.3 mm by GMAW with DCEP, a decrease of 7.2 mm for the weld width is produced by DCEN and 6.1 mm by DCEP; and an increase of 3.9 mm for the penetration is produced by DCEN and 1.9 mm by DCEP. The proposed research indicates that the desirable stability in the welding procedure can be achieved by GMAW with DCEN operation under the hyperbaric environment.     

Gas Pool Coupled Activating TIG Welding Method with Coupling Arc Electrode

Gas pool coupled activating TIG(GPCA?TIG) welding put forward in?house can dramatically enhance weld penetration of TIG welding through introducing active element oxygen to reverse the Marangoni convection flow in the molten pool. In order to further improve the welding productivity, the normal solid tungsten electrode is replaced by a kind of coupling arc electrode. The changes of arc pressure distribution along anode surface and the weld appearance were evaluated. On this basis, the dependences of weld shape characterized with weld depth, width and undercut on the main welding parameters were discussed. The results indicate, the substitution of coupling arc electrode can lead to an obvious decrease of arc pressure. Compared to hollow tungsten electrode and twin tungsten electrodes, the coupling arc electrode is much easier to manufacture and has more compacter structure. Combined with the symmetric distribution of arc pressure in di erent directions, this electrode has extensive adaptability. In the GPCA?TIG welding with coupling arc electrode, both the substitution of coupling arc electrode and the introduction of outer active gas oxygen can reduce the possibilities of producing humping bead and undercut. Their joint action makes this welding method have the capability of realizing high travel speed and deep penetration welding.