Performance of weld bead profile during A-TIG welding on nitrogen alloyed stainless steel

Austenitic stainless steel (ASS) is widely fabricated by tungsten inert gas (TIG) welding for aesthetic look and superior mechanical properties while compared to other arc welding process. Hitherto, the limitation of this process is low depth of penetration and less productivity. To overcome this problem activated tungsten inert gas (A-TIG) welding process is employed as an alternative. In this investigation the welding performance of conventional TIG welding is compared with A-TIG process using TiO2 and SiO2 flux with respect to weld bead geometry. The experimental investigation on A-TIG welding of ASS-201 grade shows TiO2 flux helps in achieve higher penetration as compared to SiO2 flux. While welding with SiO2 the hardness in HAZ and weld region higher than that of TIG welding process.

Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies

The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness.

Influence of Activated Fluxes on the Bead Shape of A-TIG Welds on Carbon and Low-Alloy Steels in Comparison with Stainless Steel AISI 304L

The article presents results of comparative A-TIG welding tests involving selected unalloyed and fine-grained steels, as well as high-strength steel WELDOX 1300 and austenitic stainless steel AISI 304L. The tests involved the use of single ingredient activated fluxes (Cr2O3, TiO2, SiO2, Fe2O3, NaF, and AlF3). In cases of carbon and low-alloy steels, the tests revealed that the greatest increase in penetration depth was observed in the steels which had been well deoxidized and purified during their production in steelworks. The tests revealed that among the activated fluxes, the TiO2 and SiO2 oxides always led to an increase in penetration depth during A-TIG welding, regardless of the type and grade of steel. The degree of the aforesaid increase was restricted within the range of 30% to more than 200%.

Productivity improvement in butt joining of thick stainless steel plates through the usage of activated TIG welding

Activated tungsten inert gas (A-TIG) welding is one variant of conventional TIG welding where a thin layer of suitable activating flux is deposited on the parent components prior to constituting the arc in order to harness enhanced penetration. Despite several benefits, industries are still reluctant in overwhelmingly using this new variant. This article attempts to highlight the productivity benefits in employing A-TIG welding either together with or superseding TIG welding during butt joining of 10-mm-thick AISI-316L austenitic stainless steel components. Initially, three single-component fluxes (Cr2O3, Fe2O3, and SiO2) are tested in forehand welding technique under varying currents but with straight polarity. Filler rod having similar metallurgical composition is also delivered during homogeneous welding. The extent of capability of each of the three fluxes is analysed by comparing the weld bead geometrical parameters (penetration, puddle width, and reinforcement) with the same obtained in conventional TIG welding under similar set of parameters. While Fe2O3 and SiO2 fluxes are found capable in enhancing penetration and reducing puddle width and heat affected zone, Cr2O3 flux failed to exhibit better performance. The article further demonstrates the time saving that can be obtained by adopting flux-assisted TIG for joining 10-mm-thick plates. When joining from both the faces is allowed, about 70% less time is desired if a combination of A-TIG and TIG is employed rather than using only TIG welding. If joining from only one face is allowed, then also usage of flux can reduce welding time by 33%.

Optimization of A-TIG Welding Process Using Simulated Annealing Algorithm

Flux-assisted tungsten inert gas welding process, also known as activated tungsten inert gas (A-TIG) welding, is extensively used in order to improve the performance of the conventional TIG welding process. In this study, the orthogonal array Taguchi (OA-Taguchi) method, regression modeling, analysis of variance (ANOVA) and simulated annealing (SA) algorithm have been used to model and optimize the process responses in A-TIG welding process. Welding current (I), welding speed (S) and welding gap (G) have been considered as process input variables for fabricating AISI316L austenitic stainless steel specimens. Depth of penetration (DOP) and weld bead width (WBW) have been taken into account as the process responses. In this study, SiO2, nano-particle has been considered as an activating flux. To gather required data for modeling, statistical analysis and optimization purposes, OA-Taguchi based on the design of experiments (DOE) has been employed. Then the process responses have been measured and their corresponding signal-to-noise (S/N) ratio values have been calculated. Different regression equations have been applied to model the responses. Based on the ANOVA results, the most fitted models have been selected as an authentic representative of the process responses. Furthermore, the welding current has been determined as the most important variable affecting DOP and WBW with 68% and 88% contributions, respectively. Next, the SA algorithm has been used to optimize the developed models in such a way that WBW is minimized and DOP is maximized. Finally, experimental performance evaluation tests have been carried out, based on which it can be concluded that the proposed procedure is quite efficient (with less than 4% error) in modeling and optimization of the A-TIG welding process.