Modelling of arc welding : the importance of including the arc plasma in the computational domain

We present results of computational simulations of tungsten-inert-gas and metal-inert-gas welding. The arc plasma and the electrodes (including the molten weld pool when necessary) are included self-consistently in the computational domain. It is shown, using three examples, that it would be impossible to accurately estimate the boundary conditions on the weld-pool surface without including the arc plasma in the computational domain. First, we show that the shielding gas composition strongly affects the properties of the arc that influence the weld pool: heat flux density, current density, shear stress and arc pressure at the weld-pool surface. Demixing is found to be important in some cases. Second, the vaporization of the weld-pool metal and the diffusion of the metal vapour into the arc plasma are found to decrease the heat flux density and current density to the weld pool. Finally, we show that the shape of the wire electrode in metal-inert-gas welding has a strong influence on flow velocities in the arc and the pressure and shear stress at the weld-pool surface. In each case, we present evidence that the geometry and depth of the weld pool depend strongly on the properties of the arc.

Understanding welding practices on shipyards : an ethnographic study for designing an interactive robot welder

The aim of this ethnographic study was to understand welding practices in shipyard environments with the purpose of designing an interactive welding robot that can help workers with their daily job. The robot is meant to be deployed for automatic welding on jack-up rig structures. The design of the robot turns out to be a challenging task due to several problematic working conditions on the shipyard, such as dust, irregular floor, high temperature, wind variations, elevated working platforms, narrow spaces, and circular welding paths requiring a robotic arm with more than 6 degrees of freedom. Additionally, the environment is very noisy and the workers – mostly foreigners – have a very basic level of English. These two issues need to be taken into account when designing the interactive user interface for the robot. Ideally, the communication flow between the two parties involved should be as frictionless as possible. The paper presents the results of our field observations and welders’ interviews, as well as our robot design recommendation for the next project stage.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

An Investigation of Friction During Friction Stir Welding of Metallic Materials

The technique of friction stir welding (FSW) puts effective use frictional heat for the purpose of joining metallic materials. In this research article, we present and discuss an experimental method to determine the coefficient of friction during FSW. The experiments were conducted to study the interaction between the FSW tool (a die steel) and the base metal (a high strength aluminum alloy) at various contact pressures (13MPa, 26MPa, and 39MPa) and rotation speeds (200rpm, 600rpm, 1000rpm, and 1400rpm). The experimental results, the microstructure, and the process temperature reveal the experimental setup to be capable of simulating the conditions during FSW. The coefficient of friction was found to vary from 0.15 to 1.4, and the temperature increased to as high as 450C. The coefficient of friction was found to increase with temperature. There exists a critical temperature at which point a steep increase in the coefficient of friction was observed. The critical temperature decreases from 250C at a contact pressure of 26MPa to 200C at contact pressure of 34MPa. Below the critical temperature at a specific contact pressure the maximum coefficient of friction is 0.6, and above the critical temperature it reaches a value as high as 1.4. The steep increase in the coefficient of friction is found to be due to the seizure phenomenon and the contact condition during FSW between the tool and the workpiece (base metal) is found to be sticking.

Optimization of friction stir welding parameters for dissimilar aluminum alloys

Assembly consisting of cast and wrought aluminum alloys has wide spread application in defense and aero space industries. For the efficacious use of the transition joints, the weld should have adequate strength and formability. In the present investigation, A356 and 6061 aluminum alloys were friction stir welded under tool rotational speed of 1000-1400 rpm and traversing speed of 80-240 mm/min, keeping other parameters same. The variable process window is responsible for the change in total heat input and cooling rate during welding. Structural characterization of the bonded assemblies exhibits recovery-recrystallization in the stirring zone and breaking of coarse eutectic network of Al-Si. Dispersion of fine Si rich particles, refinement of 6061 grain size, low residual stress level and high defect density within weld nugget contribute towards the improvement in bond strength. Lower will be the tool rotational and traversing speed, more dominant will be the above phenomena. Therefore, the joint fabricated using lowest tool traversing and rotational speed, exhibits substantial improvement in bond strength (similar to 98% of that of 6061 alloy), which is also maximum with respect to others. (C) 2010 Elsevier Ltd. All rights reserved.

Positional dependence of material flow in friction stir welding: analysis of joint line remnant and its relevance to dissimilar metal welding

Understanding material flow in friction stir welding is important for production of sound dissimilar metal welding that control the intermixing of two alloys being welded and consequent formation of new constituents which influences the weld properties. In the present experimental investigation material flow patterns are visualised using dissimilar and similar aluminium alloys using a simple innovative ,experiment. The experimental results reveal that only a portion of material transported from the leading edge undergoes chaotic flow and the remaining is deposited systematically in the trailing edge of the weld. Using this information it is shown that the formation of a friction stir welding defect, joint line remnant, does not occur only when the weld interface is on the advancing side. The material flow visualisation study has been utilised to analyse the mechanism of weld formation and its usefulness in improving fatigue properties and for dissimilar metal welds.