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Shielded metal arc welding (SMAW) is a typical manual process with many important but dangerous applications for the welder. The purpose of this paper is to present a methodology developed for execution time trajectory generation for robotic SMAW which offers greater safety and improved weld quality and repeatability.

The study presents a methodology developed for execution time trajectory generation for the robotic SMAW. In this methodology, while the electrode is melted the robot makes the diving movement, keeping the electric arc length constant. The trajectory is generated during execution time as a function of melting rate and independent of the welding speed, given by the welding parameters. The proposed methodology uses a variable tool center point (TCP) model where the covered electrode is considered a prismatic joint, whose displacement is determined by the melting rate.

The proposed methodology was implemented in a KUKA robot. The electrode melting rate was determined by measuring the arc voltage and the electrode holder trajectory was determined during the weld, keeping the arc length and the welding speed constant. All the obtained weld beads have the same aspect, showing the process repeatability.

Owing to its low productivity, robotic SMAW is only suitable to certain applications.

With this methodology, the TCP will always be located at the tip of the electrode (melting front), allowing one to program the welding speed independently of the electrode diving speed. The diving movement is automatically performed by the robot during the welding.

Robotic SMAW allows dangerous applications such as underwater welding and hot tapping of pipes without human intervention during the weld.

The purpose of this paper is to develop multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process has been improved with respect to its predictive capabilities regarding the spatial distribution of the mechanical properties (strength, in particular) within the weld.

The improved GMAW process model is next applied to the case of butt-welding of MIL A46100 (a prototypical high-hardness armor-grade martensitic steel) workpieces using filler-metal electrodes made of the same material. A critical assessment is conducted of the basic foundation of the model, including its five modules, each dedicated to handling a specific aspect of the GMAW process, i.e.: first, electro-dynamics of the welding-gun; second, radiation/convection controlled heat transfer from the electric arc to the workpiece and mass transfer from the filler-metal consumable electrode to the weld; third, prediction of the temporal evolution and the spatial distribution of thermal and mechanical fields within the weld region during the GMAW joining process; fourth, the resulting temporal evolution and spatial distribution of the material microstructure throughout the weld region; and fifth, spatial distribution of the as-welded material mechanical properties.

The predictions of the improved GMAW process model pertaining to the spatial distribution of the material microstructure and properties within the MIL A46100 butt-weld are found to be consistent with general expectations and prior observations.

To explain microstructure/property relationships within different portions of the weld, advanced physical-metallurgy concepts and principles are identified, and their governing equations parameterized and applied within a post-processing data-reduction procedure.

This paper aims to study the effect of number of welding passes on microstructure, mechanical and corrosion properties of 409 M ferritic stainless steel. Shielded metal arc welding (SMAW) process is used to weld two metal sheets of 409 M having 3 mm thickness as bead-on-plate with single, double and triple passes. Microstructures were observed at transverse section with the help of optical microscope and with increasing number of passes grain growth, and the width of heat-affected zone (HAZ) increases. The results of tensile tests revealed that as number of passes increases, there is reduction in tensile strength and ductility. Double loop electrochemical potentiokinetic reactivation (DL-EPR) test revealed that as number of passes increases, the degree of sensitization increases. This is due to the deposition of chromium carbides at the grain boundaries and the associated depletion of chromium.

Three welded plates of single, double and triple pass were welded by SMAW process. From three welded plates (single, double and triple passes), samples for microstructural examination were cut in transverse direction (perpendicular to welding direction) with the help of wire-cut electrical discharge machine (EDM). The welded plates were sliced using wire-cut EDM along transverse direction for preparing optical microscopy, tensile testing, microhardness and DL-EPR testing specimens.

From the microstructure, it was observed that the large grain growth, which is dendritic, and the structure become finer to increase in number of welding passes. As number of passes increases, the width of HAZ increases because of the higher temperature at the welded zone. The tensile strength decreases to increase the number of welding passes because of grain coarsening and chromium carbide precipitation in sensitized zone and wider HAZ. The maximum microhardness value was observed for single-pass weld as compared to double- and triple-pass welds because of the fast cooling rate. The degree of sensitization increases to increase the number of passes because of chromium carbide deposition at the grain boundaries.

The authors declare that the manuscript is original and not published elsewhere, and there is no conflict of interest to publish this manuscript.

The purpose of this paper was to propose a method based on an Artificial Neural Network and a real-time vision algorithm, to learn welding skills in industrial robotics.

By using an optic camera to measure the bead geometry (width and height), the authors propose a real-time computer vision algorithm to extract training patterns and to enable an industrial robot to acquire and learn autonomously the welding skill. To test the approach, an industrial KUKA robot and a welding gas metal arc welding machine were used in a manufacturing cell.

Several data analyses are described, showing empirically that industrial robots can acquire the skill even if the specific welding parameters are unknown.

The approach considers only stringer beads. Weave bead and bead penetration are not considered.

With the proposed approach, it is possible to learn specific welding parameters despite of the material, type of robot or welding machine. This is due to the fact that the feedback system produces automatic measurements that are labelled prior to the learning process.

The main contribution is that the complex learning process is reduced into an input-process-output system, where the process part is learnt automatically without human supervision, by registering the patterns with an automatically calibrated vision system.

In common with many engaged in engineering manufacture, the welding fabricator is under continuing pressure to increase productivity in order to remain competitive in home and international markets.

The essence of a successful weld is that the joint should possess similar properties to the parent material. In the welding of stainless materials it is essential that the corrosion resistance be preserved in the weld metal and adjacent areas. In this article the author discusses the difficulties involved and the means whereby corrosion resistance is maintained.

Discusses some aspects of welding of FERRALIUM alloy SD40 and considers differences from the penultimate alloy refinement FERRALIUM alloy 255–3SF. Gives details relating to the metallurgy of FERRALIUM SD 40, noting that it has approximately equal amounts of ferrite and austenite. Reports on methods of achieving the optimum composition after hot working. Also notes methods of accomplishing welding of FERRALIUM alloy and parameters that must be adhered to.

Stainless steel is one of the most important elements in structural design and application, and due to its excellent properties, it is widely used in industries for conventional structural engineering applications, such as thermal power plants, nuclear power plants, civil constructions, etc. (Mishra et al., 2014). A traditional tensile testing machine cannot determine the transversal stress–strain curves (Olden, 2002, 2013).

In the present study, identical mild steel specimen parts are welded at different intervals and then subjected to tensile loading. Welding is carried along the length of the specimen. Induced stresses are determined at the welded intervals and the stress–strain curve is obtained.

By considering the temperature of the weld at the interface, thermal stresses are determined. Brinell hardness number is determined at the interface and the base metal. Also, the change in the hardness at the heat-affected zone (HAZ) is found. Validation is carried out by comparing the results with the original stress–strain curve.

In the HAZ, there is a drop in the hardness number, which means that there is a change in the material property due to welding. The thermal stresses which develop at the interface can also play a very important role for property change. Results show that the stress developed due to the rise in temperature is lesser than that of normal stresses.

The gas tungsten arc welding (GTAW) process is a widely used process that produces quality weldments. But the high heat generation from the GTAW arc can cause extreme temperatures as high as 20,000°C. The residual stresses and deformations are high accordingly. One of the methods for decreasing residual stresses and deformations is to change the welding pattern. In the literature, there are not so many examples of modeling dealing with welding patterns. This paper aims to investigate the influence of welding patterns on the deformations.

In this work, back-stepping patterns and partitioning of the weld line were investigated and the distortions and residual stresses were calculated. By doing this, temperature-dependent thermophysical and thermo-mechanical material properties were used. The temperature distribution and deformation from experiments with the same welding conditions were used for validation purposes.

Seven different welding patterns were analyzed. There is only one pattern with a single partition. There are three patterns investigated for both two and three partitioned weldings. The minimum deformation and the optimum residual stress combination is obtained for the last pattern, which is a three partitioned and diverging pattern.

The most important aspect of this paper is that it deals with welding patterns, which is not much studied beforehand. The other important thing is that the structural part and the thermal part of the simulation were coupled mutually and validated according to experiments.

Online spiral pipe manufacturing is one of the most common processes for producing water and gas transmission pipes. Weld quality and pipe circumstances are the most important qualitative characteristics of these pipes determining the overall cost of production. The purpose of this paper is describing how to implement Six Sigma on the production of spiral welded pipes with a real case study.

First, the capability of the pipe production process has been performed by using the defects per million opportunities to allow for comparison and analysis of the project effectiveness. Then, the variation pattern of this index, after an improvement project, has been investigated. Finally, Taguchi's loss functions are used to evaluate the effectiveness of these projects.

The results represent a significant improvement in the production process and a reduction in production costs regarding both weld quality and pipe circumstances. Due to the successful implementation of Six Sigma project in welding and pipe quality improvement, the Define, Measure, Analyze, Improve and Control (DMAIC) method can be used effectively in defining weld and pipe quality.

In this proposed work, for the first time, research on the implementation of Six Sigma in the pipeline and welding industries on two online spiral production machines has been investigated. The DMAIC method has been used for the first time to improve the dimensional quality and weld quality of spiral pipes.