This work presents a comparison between the Remote Field Testing (RFT) and Internal Rotary Inspection System (IRIS) non-destructive testing (NDT) techniques. Such a comparison aims to assess the influence of the inspector experience on the RFT inspection process, as well as to evaluate whether the RFT technique has an inspection capability equivalent to the IRIS test. By using inspection data, a statistical analysis was conducted based on the results from three different RFT inspectors. Then, considering a third technique (3D Scanning) applied to sections extracted from tubes (destructive case) as a reference basis, the statistical equivalence of both NDT techniques was evaluated. Finally, to assess the accuracy of the analyses conducted by the RFT inspectors and the comparison between the RFT and IRIS techniques, artificial intelligence (AI) tools were employed to measure the success and error rates of corrosion detection via the RFT case. The results show equivalence between the NDT techniques and, despite the interpretation challenges with the RFT case, the subjectivity by the inspectors with its inspection process was considered low. The AI classification results indicated that the generated network was capable of classifying the corrosion effectively, hence supporting the equivalence between the RFT and IRIS techniques.
Residual stress evaluation in welded joints is of major importance, since its underestimation or lack of control can lead to deformations of welded components, to its mechanical properties' deterioration or even to failure in service. Various destructive and non-destructive techniques exist for measuring residual stress, each differing in complexity, cost, and accuracy. This study investigates the applicability of the hole-drilling method combined with Electronic Speckle Pattern Interferometry (ESPI) for residual stress evaluation specifically in welded joints, where surface conditions and material properties differ from the base metal due to reinforcement convexity, surface irregularities, and microstructural changes. The methodology involved initial equipment calibration using known strain levels, followed by residual stress measurements on bead-on-plate samples - produced with and without filler material. The analysis focused on different weld regions (fusion zone, heat-affected zone, and base metal), considering both longitudinal and transverse stress components. Calibration results showed a mean measurement error of 5.8% and a coefficient of variation around 6%. For the welded beads, the ESPI-based hole-drilling method demonstrated coherent residual stress distributions consistent with theoretical models. Higher precision was observed for the transverse stress component and in samples welded without filler material, while the longitudinal stresses in the heat-affected zone of the welds with filler addition exhibited greater variability due to local metallurgical and geometrical effects. Overall, the study confirms that the combined hole-drilling and ESPI technique is a viable and reliable approach for residual stress measurement in welded joints, provided that factors such as measurement depth, surface condition, and local stress gradients are carefully managed.
Friction stir welding (FSW) is the most widely used solid-state joining method for sheet and plate-like materials, valued for being a highly adaptable, environmentally sound, and energy-efficient process. The literature has repeatedly shown that FSW is a reliable joining technique for high-demand technological applications, particularly for high-strength aluminum and titanium alloys used in aerospace, which are difficult to join with traditional fusion welding methods. To describe the microstructural changes caused by solid-state FSW, many studies analyze mechanical parameters of FSW joints, including tensile strength, bending, torsion, elasticity, and fatigue responses. In recent years, the push to expand FSW's use, broaden the range of compatible alloy systems, and improve the resulting mechanical properties has led to significant advancements in this joining method. Accordingly, this review study provides a comprehensive investigation into the methodology and the materials relevant to this specific field.
Macrosegregations in welds are metallurgical imperfections that often form during the joining of dissimilar materials, potentially compromising the quality of the welded region. This study aimed to analyze the formation of macrosegregations during simulated welding repairs in areas degraded by cavitation, using different variants of the MIG/MAG process and involving the joining of an austenitic stainless steel to a martensitic stainless steel. Bead-on-plate deposits were carried out employing various metal transfer modes: conventional short-circuit with and without weaving, Cold Metal Transfer (CMT), globular, spray, and pulsed. Austenitic stainless steel AISI 309 was used as filler metal, and martensitic stainless steel CA-6NM was used as the base material. Microstructural characterization revealed the presence of macrosegregations in the form of islands and peninsulas at the welded interface between the materials. These imperfections were less pronounced in the CMT and conventional short-circuit without weaving processes compared to the other variants. Among the various transfer modes analyzed, the short-circuit mode, both conventional and CMT-controlled, stood out for presenting lower macrosegregation formation, with CMT being the most effective in achieving low dilution levels.
Hybrid Laser Arc Welding (HLAW) has been used globally in various sectors due to its high welding speeds and reduction in the number of passes, leading to increased productivity and reduced manufacturing costs. However, in Brazil, its industrial application has been questioned due to the high cost of equipment and the complexity of the process. Additionally, there are few studies discussing the use of the HLAW process in the welding of Thermo-Mechanical Controlled Processing (TMCP) steels. This study evaluated the hybrid welding process in different configurations and its effect on the mechanical properties, such as tensile strength and hardness, of SINCRON (R) BHS-485W steel, a high-strength material produced by Usiminas via TMCP for the manufacture of metal structures. The results indicate that the hybrid process is an excellent option for the welding of structural steels as it allows the welding of joints in a single pass and the use of high welding speeds, significantly optimizing the manufacturing of welded structures. Furthermore, the HLAW process caused minimal degradation in the properties of SINCRON (R) BHS-485W steel compared to Gas Metal Arc Welding (GMAW), making it a viable alternative for the welding of high-strength weathering TMCP steels.
Since the TOPTIG welding technique is considered highly productive, but few applications are observed with aluminum alloys, the TIG process with tangential wire feed using pulsed rectangular wave alternating current was studied. To achieve this objective, a test bench was implemented consisting of a DIGIPLUS A7 multi-process welding source, a wire feed system, a TIG torch adapted for tangential feed water-cooled, gases, a torch linear displacement system, and a data acquisition system (SAP). Four time levels were used in positive polarity with a pulse time and base time equal to 0,3 s. The test for t+ = 3 ms was selected due to its appearance and less electrode wear. A second set of tests was performed to verify the effect of current pulsation with Tp = Tb of 0,3 s; 0,6 s and 1,0 s. The weld beads were evaluated for their surface appearance and morphology. Based on these results, mechanized tangential wire feeding it is possible to perform welding with a wire speed at the base and pulse of 0,8 m/min.
AA6082 and AA6092 aluminum alloys, renowned for their high strength-to-weight ratio and excellent ductility, respectively, are widely used in the aircraft, marine, and automotive industries. Friction Stir Welding (FSW) emerges as a superior solid-state joining technique for these alloys compared to traditional fusion welding processes. To optimize the mechanical properties of dissimilar AA6082/ AA6092 joints, a comprehensive study was conducted using a Central Composite Design (CCD) with Response Surface Methodology (RSM). RSM was employed to develop mathematical models predicting UTS, TE, JE, and WNH. These models demonstrated strong predictive capability, with percentage errors typically below 2% compared to experimental values and thirty-one runs is designed to conduct experiments. The butt joints were prepared using a square tool pin made by tool steel (H13) material. Key FSW process parameters such as Tool Spindle Speed (TSS), Tool Transverse Speed (TTS), Downward Force (DF), and Tool Tilt Angle (TTA) were systematically varied to investigate their impact on Ultimate Tensile Strength (UTS), Tensile Elongation (TE), Joint Efficiency (JE) and Weld nugget Hardness (WNH). Response Surface Methodology (RSM) was employed to develop mathematical models predicting UTS, TE, PE, and WNH. ANOVA revealed that Tool Tilt Angle (TTA), Tool Transverse Speed (TTS), and Tool Spindle Speed (TSS) significantly influenced the Ultimate Tensile Strength (UTS) and Weld Nugget Hardness (WNH).The optimal FSW process parameters were determined to be a Tool Spindle Speed (TSS) of 1200 rpm, a Tool Transverse Speed (TTS) of 60 mm/min, Downward Force (DF) of 25 kN and a Tool Tilt Angle of 1.5 degrees. Under these conditions, the predicted Ultimate Tensile Strength (UTS) and Weld Nugget Hardness (WNH) were 492.31 MPa and 185.82 HRB, respectively. Microstructural analysis confirmed substantial grain refinement and dynamic recrystallization in the weld nugget, leading to improved mechanical properties. Validation experiments showed excellent agreement with model predictions.
This study evaluated the effectiveness of the Temper Bead Welding (TBW) technique in AISI 4140 steel using GMAW process and an ER4130 filler metal. The selection of welding parameters was first obtained using the Higuchi test, where welds were applied with several heat inputs. Three test coupons were welded using three different welding techniques: (1) conventional build-up in As-Welded (AW) condition, (2) conventional build-up welding with post-weld heat treatment (PW), and (3) the Temper Bead or Layer (TB) technique. The effectiveness of the TBW technique was evaluated by nondestructive examinations, carrying out a metallographic study of the microstructures, measuring the typical microhardness profiles of the weld metal and Heat-Affected Zones (HAZs). Tensile tests were also conducted with all-weld-metal specimens extracted from the coupons. Visual and radiographic examinations showed that the filler metal, ER4130, is highly susceptible to porosity. According to the results obtained, TBW has a more beneficial effect on the hardness of the cap beads than the build-up technique in the AW condition. The results also indicate that the hardness values of the HAZs in welds applied by TBW tend to be like those obtained in welds subjected to tempering heat treatment. This fact offers an economic advantage in situations where Post-Weld Heat Treatment (PWHT) cannot be performed.
In laser-arc hybrid welding, the selection of welding parameters is crucial for achieving excellent mechanical properties of weld joints. In this paper, based on the experimental data of laser-arc hybrid plate butt welding, a BP neural network was employed to establish a prediction model between the hybrid-welding process parameters, namely welding current I/A, laser power P/W, welding blunt height D/mm, welding angle alpha/degrees, welding gap d/mm, and welded joint tensile strength. Subsequently, the multi-population genetic algorithm (MPGA) was utilized to optimize the internal topology of the BP neural network, aiming to enhance the prediction accuracy. The results indicate that the prediction error of the optimized neural-network model for tensile strength is less than 6%. According to the established BP neural-network model, taking the maximum tensile strength of the welded joint as the objective function, the genetic algorithm (GA) was used to optimize the welding process parameters with the range D E [2,4]/mm, d E [0.1,0.8]/mm, a E [30,60]/degrees P E [2300,2800]/W, I E [200,280]/A. Finally, the optimal tensile strength of the weld joint was obtained as 1.441 MPa. The combination of hybrid-welding process parameters is as follows: blunt edge of 3.1 mm, welding angle of 51 degrees, welding gap of 0.37 mm, welding current of 200 A, and laser power of 2700 W. Based on the hybrid-welding process parameters optimized by the genetic algorithm, a plate-butt-welding experiment was conducted on the welding test platform. The hybrid-welding conditions were kept unchanged, and the welded sample was processed and tested for tensile strength. The test results indicated that the tensile strength of the welded sample corresponding to the optimized process parameters was 1.35 MPa. This value is higher than the maximum tensile strength of 1.309 MPa in the welded samples of the orthogonal test.
This work analyzed data from MIG/MAG welding experiments performed in short-circuit operation mode using three gases: 100% argon, argon plus 25% carbon dioxide and 100% carbon dioxide, enabling comprehensive analyses of the following parameters: short-circuit time; open arc time; short-circuit voltage; open arc voltage; current rise rate; number of shorts and reference voltage. Correlation tests (Pearson, Spearman, Kendall) were performed to analyze the quality of the models, including the application of Shapiro-Wilk tests to verify the normality of the residues, making it possible to create a correlation matrix with the parameters and gases tested. The correlation between the open arc time and the number of shorts, and between the open arc time and the current rise rate showed strong correlation for all gases. The correlations between the current rise rate and the number of shorts, the short-circuit time and the short-circuit voltage, as well as the correlation between the short-circuit voltage and the reference voltage, demonstrated lower significance for all gases. Regarding the time series analysis, the ARIMA and ETS models were adjusted and evaluated with specific metrics, indicating the need for improvements in the model to increase the accuracy of the predictions.
This work aims to simulate the spot welding process using the finite element method, obtain dimensions of the welding point and analyze the heat affected zone (HAZ), observing the different regions of the HAZ and comparing with the literature. The material of the plates is low carbon steel with a thickness of 2 mm, the current used is 15 kA over a period of 20 cycles. The geometry and parameters for carrying out welding are specified by literature and standards. For the computational analysis, the ANSYS (R) Workbench 23.2 software, in the student version, was used, together with the Moving Heat Flux extension, in which the mathematical model was solved by the Transient Thermal tool and thermal losses due to conduction, convection and radiation were considered. At the end of the work, the simulation results converged with the results predicted in the literature.
In this study, it was proposed to evaluate different flux compositions for submerged arc welding that are feasible for use as root backing flux in root pass welding performed by the MIG/MAG welding process. The aim was to identify the effect of these fluxes on the geometric quality of the root pass. For comparison purposes, a method was developed to use the flux as root support. Non-acceptance criteria, based on bead geometry, were proposed to analyze performance. Five different types of fluxes were evaluated under a single welding current condition (aiming at high productivity), root gap range, and welding speed. Statistical analyses to differentiate means and reduce uncertainty were applied as tools. The effects of each flux on the root geometry were analyzed. As a conclusion, it was observed that the characteristics of the fluxes act in a competing manner as root support. Basicity appears to be a determining factor in reinforcement height, while grain size seems to govern root convexity. The regularity of the root depends on both grain size and basicity. The effect of melting point remains uncertain, not prevailing over the others in any of the three criteria.
The advancements in Metal Additive Manufacturing (MAM) technologies have expanded opportunities for research and the development of components across aerospace, automotive, medical, and other industrial sectors. Friction Stir Engineering Metal Additive Manufacturing (FSE-MAM), including processes such as Additive Friction Stir (AFS) and Friction Surfacing Additive Manufacturing (FSAM), offers an alternative for fabricating complex parts using environmentally friendly methods that reduce environmental impacts compared to conventional techniques. These processes eliminate fume emissions and minimize noise generation. In AFS, a hollow rotary tool is fed with additive material, while FSAM employs a rotating tool with a pin projection to generate frictional heat for material deposition. Both methods utilize pressure and heat without reaching the material's melting point, resulting in forged joints with enhanced mechanical properties, such as superior hardness and tensile strength, compared to fusion-based deposition processes. This study aims to present a comprehensive literature review on FSE-MAM processes, focusing on mechanical properties, utilized materials, tools, and potential hybrid methods. Significant improvements are highlighted, including higher hardness, allowable stresses, and macrostructural quality compared to conventional additive manufacturing techniques.
This work dealt with the determination of parameters and execution of joints welded by the Friction Stir Welding process of commercial EN AW 1200 aluminum alloy sheets with 3 mm thickness, using a milling machine with computer numerical control. To identify the influence of tool geometry on the process, tests were carried out with tools with conical pins and square pins manufactured using AISI H13 steel with heat treatment. The samples were characterized by the uniaxial tensile test, face and root bending tests, microhardness tests, and microstructure analyses. It was verified through uniaxial tensile tests that the samples manufactured with a conical pin showed greater efficiency, which also reduces the costs of the welding process due to its simplicity in execution. The face and root bending results demonstrate that the welded joint presented behavior-highlighted ductility, corroborating the microhardness tests. Based on the process parameters and tool geometry obtained from this investigation, commercial EN AW 1200 aluminum alloy sheets can be manufactured with lower production costs and excellent mechanical and metallographic properties.
Duplex stainless steels have superior mechanical and corrosion properties with better toughness and ductility compared to austenitic and ferritic stainless steels due to their dual phase microstructure i.e. austenite and ferrite, which attractive for gas pipelines. In this study, effects of different heat inputs and interpass temperatures were investigated on the mechanical and microstructural properties of UNS-S31803-(2205) duplex stainless steel welds using two different welding methods i.e. Gas Tungsten Arc Welding and Shielded Metal Arc Welding in place of conventionally used Submerged Arc Welding. UNS-S31803-(2205) duplex stainless steel pipe was joined using ER2209 (GTAW) filler wire and ESAB OK67.55 (SMAW) electrode. Pure argon was used as shielding gas and for back-root protection. Microstructural examinations and mechanical tests were carried out in accordance with PTS and ASME standards. Results showed that, two different welding methods generated a weld joint with higher strength and hardness than base metal at certain heat inputs and interpass temperatures. Weld metal properties were within the defined limits of standards and the critically selected interpass temperature and heat input which induced different cooling conditions with multiple passes produced a welded joint without the formation of deleterious sigma phase in weld metal and the heat affected zone.
The mechanical properties of the weld metals are dependent on the alloying elements and the microstructure of the weld metal. Neural network analysis is widely applicable in various fields, aiming to enhance efficiency thorough analysis. The application of artificial intelligence techniques for the rapid and accurate determination of physical properties offers a significant time, cost and labor advantage in industrial production processes due to the time consuming and costly nature of traditional methods. This study was aimed to investigate the relationships between structural and microstructural properties against alloying elements in SMAW weld metal using neural networks and to analyze them through this innovative methodology. In this study, the Levenberg-Marquardt algorithm is utilized to predict the physical properties of weld metal through artificial neural networks approach using 94 sets of weld metal composition and microstructural properties. The success rates of the modelling were found to be 93.14% for acicular ferrite, 95.92% for hardness, 94.17% for yield strength, and 96.32% for ultimate tensile strength. It is also feasible to make reverse predictions of weld metal composition in order to predict weld metal properties such as hardness, yield strength, acicular ferrite percentage and ultimate tensile strength within a range of alloying elements percentages, with a reasonable degree of accuracy.
In certain sectors, such as shipbuilding and offshore, corrosion causes considerable costs by material loss and rework, making material protection by shop primer necessary to create a protective barrier. FCAW is widely used in these situations but its attributes are compromised when carried out over the protective layer. The comprehension of shop primer influence during welding and its relationship with the obtained results are not completely understood. This work aimed to verify the influence of ethyl zinc silicate shop primer thickness layers applied to steel plates during welding and on the weld metal and slag characteristics produced by class E71T1-C1A2-CS2 wire. The current and voltage monitoring was carried out during welding, the weld bead dimensions and microstructure were evaluated, and the slag generated was analyzed. Primer layer thickness increased weld bead width and penetration. The electrical parameters did not indicate changes in the arc. Dilution changes resulting from increased penetration did not impact the microstructure of the weld metal. Measurements of the bead contact angle and analysis of the slag together with the analysis of electrical signals indicated, by elimination, that the thickness of the shop primer layer was responsible for the change in the fluidity of the liquid metal.
The identification of relevant information in vibration signals has been a subject of study for decades, leading to significant advancements. This field is increasingly recognized as essential for diagnosis, prognosis, and failure prediction, ensuring safety, estimating quality conditions, and monitoring processes across various domains. Researchers have developed numerous approaches to extract and classify features within vibration signals, aiming to identify patterns and useful process information. Many of these approaches have proven effective with vibration signals from various manufacturing processes, including welding, and mechanical, civil, and electrical engineering systems. However, few studies have focused on vibration signals in the Friction Welding process, specifically Rotary Friction Welding (RFW). During RFW, simultaneous application of rotation and compressive forces joins two surfaces, generating complex vibration waves that carry unique information about deformations between the parts' surfaces. The main challenge in diagnosing vibrations in RFW is that the vibration signal is often contaminated with noise due to uneven heating, causing fluctuations in roughness, friction coefficient, and variable ripples over time. This study aims to develop a hybrid signal analysis methodology to investigate the potential for quality diagnosis using vibration signals from the continuous drive friction welding (CDFW) process. The proposed method combines the Dickey-Fuller test (DF) for stationarity identification, Empirical Mode Decomposition (EMD) for frequency recognition, Principal Component Analysis (PCA) for compression, visualization, and data classification, and Short-Time Fourier Transform (STFT) for graphical frequency representation over time. Analyses confirmed that vibration signals are significantly affected by corresponding changes in process evolution. It was demonstrated that vibration signals can characterize CDFW quality. Experimental results also showed that applying EMD, PCA, and STFT to vibration signals successfully identified relevant characteristics of process evolution in the time-frequency domain.
Resistance spot welding is a widely used welding process for thin plates in industries such as aerospace and automotive. This process involves the combination of heat, force, and electricity, and the development of numerical simulation technology for welding processes has enabled the simulation of complex welding phenomena. Numerical simulation can reduce the need for extensive experimental work and improves welding production efficiency. In this article, the focus is on studying the temperature field and process parameters of resistance spot welding of (0.2+0.2 mm) 304 stainless steel. Initially, a three-dimensional symmetric model was created using Solid Works, and then Abaqus is used to perform a numerical analysis of the thermal-electric three-field coupling. The impact of welding parameters (welding current and welding time) on the temperature field and nugget diameter are analyzed. Next, welding experiments are conducted on the workpiece using different welding times and welding currents. The morphology and diameter changes of the molten material nucleus are observed using a high-magnification digital microscope. The results of the numerical simulation analysis and spot welding experiment analysis for resistance spot welding of 304 stainless steel with an equal thickness of 0.2+0.2 mm show a high level of consistency. Finally, tensile testing is carried out on the solder joints, combining this with the diameter to evaluate their strength and quality for the determination of the optimal welding process parameters.
This study presents an effective method for laser welding, using welding energy as a reference to increase productivity without compromising quality. The research examines the influence of laser power and welding speed on ASTM A36 steel, testing eight combinations of these variables while keeping welding energy constant. Unlike conventional methods that optimize individual variables, this approach establishes a relationship between welding energy, power density, and interaction time, creating a model for consistent results. Through visual, mechanical, and microstructural analyses, the study identifies different laser welding modes: conduction, penetration, and excessive penetration, contributing to a better understanding of their effects on material behavior. In this context, welding energy alone is not sufficient, as different combinations of power and speed generate distinct results. This occurs due to the relationship between welding efficiency and power density, which directly influences keyhole formation, plasma plume behavior, and weld bead morphology. These variations affect energy distribution and the occurrence of defects, such as underfill and irregularities in the weld profile. The findings provide valuable insights for optimizing laser welding in low-carbon steels, helping to refine process parameters and improve weld quality.
