Analysis of gas metal arc welding process using GA tuned fuzzy rule based system

An investigation into an intelligent system for predicting bead geometry in GMA welding process

Generally welding is one of the most important processes to have a strong influence on the quality and productivity from a manufacture-based industry such as shipbuilding, automotive and machinery. The GMA(Gas Metal Arc) welding process involves large number of interdependent welding parameters which may affect product quality, productivity and cost effectiveness. To solve such problems, mathematical models are required to select the welding parameters for GMA welding process. In this study, the GMA welding process was studied using the information generated during the welding. The statistical analysis of a generalized regression approach was conducted by the following three methods: Firstly using the mathematical model (linear regression, 2nd regression); Secondly GA(Genetic Algorithm) with intelligent models; And finally using response surface analysis of models to develop the relationships between welding parameters and bead width as welding quality.

Effect of controlled atmosphere on the mig-mag arc weldment properties

A study on MOORA-based taguchi method for optimization in automated GMA welding process

Efficient control of a gas metal arc welding (GMAW) process enables one to obtain high quality products as a consequence of achieving a high quality weld. Although control of the droplet detachment frequency in the welding process would play a great role in improving the welding quality, measuring this variable is difficult and expensive. In this paper, we attempt to control the frequency of droplet detachments without directly measuring it. To this end, we utilize the hybrid property of the GMAW process to indirectly control the frequency. Specifically, a mixed logical dynamical (MLD) model is obtained by considering the hybrid act of the process during droplet detachment. Then, a nonlinear model predictive controller with variable control and prediction horizons is designed incorporating the hybrid behavior of the process. The controller regulates the droplet detachment frequency without measuring this variable directly. Computer simulation results show that the proposed controller leads to a higher quality weld compared to the present approaches.

PurposeThe purpose of this paper is to optimize the gas metal arc welding (GMAW) process input parameters simultaneously considering the multiple output variables (bead width (BW), bead height (BH) and depth of penetration (DP)).Design/methodology/approachGrey‐based Taguchi approach was used for designing the experiment, L27 orthogonal array was used which composed of three levels and 27 rows, which means that 27 experiments were carried out. Design of experiments was selected based on a four welding parameters with three levels each. The selected welding parameters for this paper are gas flow rate, voltage, travel speed and wire feed rate. The bead‐on‐plate welding trials are carried out on AISI 904L super austenitic stainless steel (SASS) sheets and evaluate the shape of the fusion zone depends upon a number of input parameters.FindingsBead‐on‐plate welding of 904L SASS sheet is successfully performed (without any cracks and discontinuity) by GMAW process and the bead profiles are measured. The predicted bead profiles have the better DP and lower BH and BW. It is found that the optimized setting values are improving the response values by 10 per cent.Originality/valueThe optimal welding conditions are identified in order to increase the productivity and minimize the total operating cost. The process input parameters effect is determined under the optimal welding combinations.

The weld quality is generally controlled by the welding parameters. In gas metal arc welding process, the welding parameters are inter related and the adjustment of one parameter may affect another...

In this paper a modified continuous energy law was explored to investigate transport behavior in a gas metal arc welding (GMAW) system. The energy law equality at a discrete level for the GMAW system was derived by using the finite element scheme. The mass conservation and current density continuous equation with the penalty scheme was applied to improve the stability. According to the phase-field model coupled with the energy law preserving method, the GMAW model was discretized and a metal transfer process with a pulse current was simulated. It was found that the numerical solution agrees well with the data of the metal transfer process obtained by high-speed photography. Compared with the numerical solution of the volume of fluid model, which was widely studied in the GMAW system based on the finite element method Euler scheme, the energy law preserving method can provide better accuracy in predicting the shape evolution of the droplet and with a greater computing efficiency.

The present work reports results obtained by applying pseudorandom noise injection to the gas metal arc welding process to determine the impulse response of the system (the response to a short pulse of energy). The phenomena having the longest time constants are investigated and it is found that there is a damped oscillation associated with delayed heating of the anode wire stickout. Properties of the oscillation are measured and found to agree with previous research. It is demonstrated that the pseudorandom noise injection technique has advantages in investigating welding processes in which it is desired to determine operating characteristics without significantly perturbing welding.

Mathematical models of the gas metal arc (GMA) welding process may be used to study the influence of various welding parameters on weld dimensions, to assist in the development of welding procedures, and to aid in the generation of process control algorithms for automated applications. In this work, a three-dimensional (3-D), steady-state thermal model of the GMA welding process has been formulated for a moving coordinate framework and solved using the finite-element method. The model includes temperature-dependent material properties, a new finite-element formulation for the inclusion of latent heat of fusion, a Gaussian distribution of heat flux from the arc, plus the effects of mass convection into the weld pool from the melted filler wire. The influence of weld pool convection on the pool shape was approximated using anisotropically enhanced thermal conductivity for the liquid phase. Weld bead width and reinforcement height were predicted using a unique iterative technique developed for this purpose. In this paper, the numerical model is shown to be capable of predicting GMA weld dimensions for individual welds, including those with finger penetration. Also, good agreement is demonstrated between predicted weld dimensions and experimentally derived relations that describe the effects of process variables and their influence on average weld dimensions for bead-onplate GMA welds on steel plate.

The gas metal arc welding (GMAW) process combines aspects of arc plasma, droplet transfer, and weld pool phenomena. In the GMAW process, an electrode wire is melted by heat from an arc plasma, and molten metal at the wire tip is deformed by various driving forces such as electromagnetic force, surface tension, and arc pressure. Subsequently, the molten droplet detaches from the tip of the wire and is transferred to the base metal. The arc plasma shape changes together with the metal transfer behavior, so the interaction between the arc plasma and the metal droplet changes from moment to moment. In this paper, we describe a unified arc model for GMAW, including metal transfer. In the model, we do not account for heat transfer in the metal, but the wire melting rate is determined by the arc current. The developed model can show transition from globular transfer at low currents to spray transfer at higher currents. It was found that electromagnetic force is the most important factor at high currents, but surface tension is more important than electromagnetic force at low currents in determining the transfer mode.

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

Gas Metal Arc Welding (GMAW) is a popular method of material joining, widely used for a variety of critical industrial structures. Assuring high quality of joints is than a vital task. Welding is a highly dynamic and non-linear process, thus an application of time-domain or frequency-domain methods is often not suitable for evaluation of welded joints quality. To fully describe the correspondence between the geometry of welding arc, parameters that express the quality of joint, and the welding arc current, being the most important steerable parameter of a GMAW, time-frequency methods (TFM) of signal analysis should be applied. In the paper application of ensemble of STFT and EMD (Empirical Mode Decomposition)-based estimators to evaluate the stability of a GMAW process, that results in the quality of joint. Proposed method of feature extraction was applied on the real data taken during several GMAW realizations with different conditions (changes in welding current, arc voltage, shield gas flow, wire feed speed, etc.). In the active experiment process parameters were acquired. Performed investigations revealed that in comparison to traditional as well as separately used TFM, ensemble of TF estimators gave better performance in a GMAW condition assessment.

A three-dimensional model has been developed to study turbulent fluid flow and heat transfer in a gas metal arc weld pool. The phase change process during melting and solidification is modelled using the enthalpy–porosity technique. Mass and energy transports by droplet transfer are considered through a thermal analysis of the electrode. The droplet heat addition into the molten pool is considered to be in the form of a volumetric heat source distributed in an imaginary cylindrical cavity within the weld pool ('cavity' model). A two-equation k-ε model capable of addressing turbulent weld pool convection, taking into account the morphology of the phase change, is presented. The weld pool dynamics and geometry (shape and size) in a moving gas metal arc welding (GMAW) process are studied and the effects of enhanced diffusivities on the turbulent weld pool are discussed. The predicted weld pool geometry using laminar and turbulent models is also compared with corresponding experimental post-weld sections.

Welding process parameters and the interaction between them show a major effect on the clad bead shape. This work focuses on an experimental study of clad bead shapes and analyzes the interaction between the welding process parameters by depositing ERNiCrMo-10 cladding on AISI 4140 steel by gas metal arc welding (GMAW) process. The experiment is performed with three factors and three levels, and mathematical models are developed using the response surface methodology (RSM), and the adequacy is checked using ANOVA. The model developed using RSM is analyzed using interaction surface plots.