Resistance Spot Research Articles

Optimizing Sample Preparation for Destructive Testing in Resistance Spot Welding

Abstract The integrity and reliability of resistance spot welding, a crucial process in various manufacturing industries, are significantly influenced by the quality of sample preparation. This study focuses on advancing the methodologies and practices in the preparation of samples for resistance spot welding destructive tests, aiming to improve the precision and repeatability of the results. We discuss comprehensive approaches encompassing material selection, surface treatment, dimensional accuracy, and alignment procedures, emphasizing the importance of meticulous handling and preparation techniques, A significant focus is placed on the utilization of sophisticated alignment and measurement tools to enhance the consistency of the welding area subjected to destructive testing. our study demonstrates a significant improvement in the reliability and accuracy of welding machine calibration, ultimately contributing to the overall quality of the welding process. By integrating these refined processes, the study highlights a significant improvement in the reliability of welding tests, contributing to enhanced welding quality and performance in practical applications. Our findings underscore the critical role of detailed and standardized sample preparation in achieving accurate and reliable resistance spot welding destructive test outcomes, providing valuable insights for both industrial applications and further research in welding technology.

A research on resistance spot welding quality judgment of stainless steel sheets based on revised quantum genetic algorithm and hidden markov model

In view of the following problems existed in the data-driven resistance spot welding (RSW) quality judgment methods: relying on expert experience, resulting in a high misjudgment rate; affected by the initial value, it is easy to fall into the local extreme point; multiple parameters needed to be modulated to increase the training time of the model. Therefore, this paper proposed a RSW quality judgment method based on revised quantum genetic algorithm (RQGA) and hidden markov model (HMM). Which used quantum rotation gate to replace the evolution process of genetic algorithm (GA), reducing the number of parameters that needed to be modulated in the model, and optimizing the initial model of HMM by RQGA to avoid falling into local extreme point. At the same time, combining expert experience with HMM to make quality judgment to ensure the accuracy of judgment.Firstly, by RSW test to obtain the main influencing factors of quality, and combining with expert experience to realize the preliminary judgment of it, on this basis, HMM was established. Next, to address the susceptibility of HMM to initial model, quantum genetic algorithm (QGA) was utilized to search for the optimal initial model. Moreover, in view of the limitations of QGA (“coding length disaster” and fixed rotation angle), a corresponding improvement was also presented. At last, the established model was applied to the RSW process of stainless steel sheets railway carriage roof. Compared with the other five models, it took the least time to complete parameter training of HMM in four quality states, less than 15s; when judging the quality, its log-likelihood probability value was −47.8418, which was close to the maximum value of this state; during the classification test, the average classification accuracy of the four quality states were 90.8 %, 92.2 %, 90.8 % and 92.0 %, respectively, which was higher than the other five models. Consequently, the model established in this paper was effective.

Microstructure and mechanical properties of similar and dissimilar resistance spot welded DC04 and HRP6222 (DD11) steels

Abstract Low carbon steels are frequently preferred in the automotive industry. The most preferred welding method in vehicle body manufacturing is resistance spot welding (RSW). In this study, RSW joints of DC04 and HRP6222 steels were carried out at two different electrode forces (2.1 kN, 2.4 kN) and three different welding currents (4 kA, 6 kA, 8 kA). The effects of different welding parameters on microstructure, tensile shear force, failure mode and microhardness were investigated. So, the focus was on optimizing the welding parameters. As a result, the RSW process caused the formation of three different regions in the microstructure (the base metal, the heat affected zone and the weld metal). It was observed that the tensile shear force increased as the welding current and electrode force increased. After the tensile shear tests, two different failure modes occurred (interface and pull-out type). Hardness values showed a linear relationship with tensile shear force results. In addition, a significant increase in hardness values was observed from the base metal to the weld metal in all welding parameters.

Using fiber optic sensors to monitor the quality of resistance spot welding joints

Using fiber optic sensors to monitor the quality of resistance spot welding joints

MICROSTRUCTURE AND PROPERTIES OF 6082/7075 MAGNETIC-FIELD-ASSISTED RESISTANCE-SPOT-WELDED JOINTS

To advance automotive lightweighting, a study was conducted on steady-state magnetic-field-assisted resistance spot welding of 6082 aluminum alloy (1.0 mm thick) and 7075 aluminum alloy (1.5 mm thick) with thermal compensation. The influence of varying magnetic induction intensity on the microstructure and tensile properties of welded joints was assessed under the same welding current, time and electrode pressure. The results revealed that the Lorentz force induced by magnetic induction intensity ranging from 0 mT to 60 mT could promote an outward circumferential movement of molten metal within the weld nugget. This movement, at the same time, led to an increase in the weld-nugget size and improved the efficiency of thermal resistance. At a magnetic induction intensity of 80 mT, no weld-nugget formation occurred in the welded joint. Microstructural observations at magnetic induction intensities of 0 mT and 60 mT revealed equiaxed grains at the nugget center and columnar dendrite grains at the nugget edge in the welded joints. The Lorentz force accelerated the weld cooling rates after the addition of magnetic field, refining the weld grain structure. Tensile properties of the welded joints gradually improved with increasing the magnetic induction intensity from 0 mT to 60 mT, driven by the weld nugget size expansion and weld grain refinement. Overall, the present study indicated that the magnetic induction intensity of 60 mT resulted in the most favorable comprehensive mechanical properties of the investigated welded joints.

Microstructure and mechanical properties of resistance spot welded dissimilar aluminum/steel joints fabricated using high entropy alloy as interlayer

To improve the welding quality of Al/steel joint during resistance spot welding (RSW) process, a CoCrFeNiMn high entropy alloy (HEA) sheet was employed to be an interlayer between aluminum alloy and high strength steel parent metal sheets. Through a series of comparative studies and analyses, the Al/steel spot welded joint obtained from the process with the HEA interlayer had a larger aluminum nugget diameter and thinner intermetallic compound (IMC) layer when compared to a conventional RSW process. When the thicknesses of two parent metal sheets were 1.0 mm or 1.5 mm, the aluminum nugget diameter of the Al/steel spot welded joint with the HEA interlayer were 4.904 mm and 5.962 mm, and respectively increases by 28.41% and 31.32% compared to a conventional RSW process. For the 1.5 mm of the thickness of the parent metal sheets, the HEA interlayer can make the layer thicknesses at the Al/steel faying interface decrease from 3.2 μm to 1.3 μm. Also, adding the HEA interlayer could induce more welding heat energy respectively by 30.74% and 30.34%, and significantly improve the lap-shear strength of the joint by 56.95% and 52.09% for two thicknesses of the parent metal sheets. Even increasing welding current of the process without HEA interlayer to make its calculated welding heat energy the same as that with HEA interlayer, the Al/steel joint obtained from the process with HEA interlayer still had a higher lap-shear strength. In addition, by seriously observing and analyzing the fracture surfaces obtained from processes with and without the HEA interlayer, it could be concluded that the HEA interlayer could improve the fracture mode of the Al/steel joint from interfacial fracture to button fracture, so the quality of the Al/steel joint could be improved. This work can supply an effective method to improve the dissimilar metals welding process.

Interfacial microstructure and mechanical property of dissimilar resistance spot welded joint of TC4 titanium alloy and 316L stainless steel with nickel interlayer

Dissimilar materials of TC4 titanium alloy and 316L stainless steel were joined by means of resistance spot welding with nickel interlayer in different thicknesses. A significant enhancement in terms of nugget morphology quality with less defects was achieved for the welded joints with nickel interlayer compared with that without interlayer. With increasing the nickel interlayer thickness from 50 μm to 300 μm, the effective nugget diameter increased gradually from ∼4.8 mm to ∼5.2 mm, which was lower than that of the interlayer-free welded joint being ∼5.9 mm. A thinner intermetallic compound layer with dual-layered structure features with thickness of ∼11 μm was formed at the nugget/titanium interface in the welded joint with nickel interlayer compared with that of the interlayer-free welded joint, meanwhile an intermetallic compound layer with thickness of ∼3 μm was formed at the nugget/stainless steel interface, which exhibited serrated structure features. The introduction of nickel interlayer in the welded joint could suppress the formation of the brittle Ti–Fe intermetallics such as Fe2Ti, and facilitate the formation of TiNi, Ti2Ni and TiNi3. A more homogeneous current density distribution and a lower peak temperature (1809 °C) during welding were achieved via employing nickel interlayer. With increasing nickel interlayer thickness from 0 μm to 300 μm, the tensile shear load of welded joints experienced an increased tendency first and then decreased, meanwhile the maximum tensile shear load of 3.7 kN was obtained with the interlayer thickness of 200 μm, which was 61% higher than that of the interlayer-free welded joint.

The Additive to Mass Manufacturing Process of Mixed Potential Electrochemical Sensors

Additive manufacturing allows for quick turn around and low cost of production of small numbers of parts. These attributes lend the technology to prototype development, where design changes are many and production numbers are low [1]. Once design parameters have been nailed down, additive manufacturing’s low throughput and poor reproducibility limit application to high volume production.Here, we discuss the implementation of direct-write extrusion of ceramic pastes and metal inks for prototype manufacturing of mixed potential electrochemical sensors and the transition to tape casting and screen printing for high volume production. Throughout the prototyping phase, direct write extrusion enabled quick and easy production of low numbers of parts, enabling various changes in sensor design and material to improve sensor performance. Sensor design evolved from a disk shape (Fig. 1 a) to a stick with integrated heater (Fig. 1 b, c). Direct write extrusion of substrate enabled quick testing of various stabilized zirconia ceramics to improve the sensitivity of the device [2]. Limitations of additive manufacturing became apparent when attempting to integrate the heater into the device, the inconsistent linewidths led to areas of high resistance and hot spots (Fig. 1 c). Tape-casting and screen printing of the devices was adopted for three reasons, first, to improve line fidelity, which is vitally important when printing small electrodes as well as heater traces (Fig. 1 d), second, to further decrease conductivity of substrate by laminating multiple layers of different ceramic materials, and finally to increase manufacturing throughput (Fig. 1 d, e).This work was supported by US Department of Energy Award DE-FE0031864References[1] T. D. Ngo, A. Kashani, G. Imbalzano, K. T. Q. Nguyen, and D. Hui, “Additive manufacturing (3D printing): A review of materials, methods, applications and challenges,” Compos. Part B Eng., vol. 143, pp. 172–196, Jun. 2018, doi: 10.1016/j.compositesb.2018.02.012.[2] S. Halley, K. Ramaiyan, F. Garzon, and L. Tsui, “Massive enhancement in sensitivity of mixed potential sensors towards methane and natural gas through magnesia stabilized zirconia low ionic conductivity substrate,” Sens. Actuators B Chem., vol. 392, p. 134031, Oct. 2023, doi: 10.1016/j.snb.2023.134031. Figure 1

Local shear fracture properties in heat-affected zone of resistance spot-welded advanced high-strength steel

In the process of resistance spot welding of advanced high-strength steel (AHSS), the development of heat-affected zones (HAZs) considerably modifies the mechanical properties of the weld region. However, the limited reporting in the study of shear behavior in the HAZ hinders the accurate prediction of joint fracture and failure behavior. This study focused on the shear fracture behavior of resistance spot-welded AHSS. Given the limited extent of the HAZ, a miniature shear test was designed and shear fracture tests were conducted on JSC590, JSC980, and JSC1180. These tests facilitated the acquisition and compilation of data regarding the shear mechanical properties of diverse steel grades and their respective HAZs. A hardness-based empirical model for the strength coefficient and the strain-hardening exponent in Hollomon's law was introduced, and this model was subsequently integrated into finite element method calculations. The accuracy of the model was validated by shear strength reproductions, exhibiting errors within the range of 5.4%–13.5% and the averaged error was less than 10%. Further analyses confirmed that stress triaxiality at critical positions varied from 0 to 0.33, indicative of shear-dominant stress conditions. Moreover, the evolution of stress states revealed a notable association between the fracture surfaces across different stress states and steel grades. These findings fill the gap regarding the shear behavior of localized HAZs and expand the understanding of their mechanical behavior under various stress states. It will contribute to accurate fracture prediction by stress triaxiality based fracture criteria, such as Modified Mohr-Coulomb (MMC) model, applied to AHSS.

Derivation of Analytical Expressions for Fast Calculation of Resistance Spot Welding System Currents

Derivation of Analytical Expressions for Fast Calculation of Resistance Spot Welding System Currents

Electrode life evaluation for varied electrode material composition and geometry in resistance spot welding of aluminum alloys

Electrode life evaluation for varied electrode material composition and geometry in resistance spot welding of aluminum alloys

Research of microstructure and properties of resistance spot welded joints of galvanized DP steel for automobile

Research of microstructure and properties of resistance spot welded joints of galvanized DP steel for automobile

Parametric Optimization of Resistance Spot Welding to Improve the Weld Strength

Parametric Optimization of Resistance Spot Welding to Improve the Weld Strength

An offset-transformer hierarchical model for point cloud-based resistance spot welding quality classification

Resistance spot welding (RSW) is a widely used welding technology in automotive manufacturing, and weld nugget quality is closely related to the quality of the vehicle body. Offline random checks are largely relied on the quality inspection of weld nuggets, but they have low efficiency and high cost. To address this issue, this paper proposes a deep learning model for RSW weld nugget classification, named the offset-transformer hierarchical model (OFTFHC), which is based on the point cloud data of its appearance shape. OFTFHC uses a hierarchical network structure to gradually expand the receptive field. A local feature module is introduced to extract local features from the point cloud, effectively enabling the recognition of the fine structural features of the resistance spot weld point cloud. A residual ratio module, which is based on MLP_MA and uses max and average functions for feature enhancement, is designed to adapt to the complex spatial structure of the point cloud. The offset-transformer structure is used to learn global context features, thereby enhancing the global feature extraction capability. Through classification experiments on RSW weld nuggets across 5 categories with a total of 1050 samples, OFTFHC achieved an average accuracy of 80.6 %, outperforming existing models. This demonstrates the effectiveness and superiority of the method, making it highly suitable for weld nugget quality control in automotive automation production lines.

Ultrasonic Non-Destructive Testing and Evaluation of Stainless-Steel Resistance Spot Welding Based on Spiral C-Scan Technique.

In order to achieve the non-destructive testing and quality evaluation of stainless-steel resistance spot welding (RSW) joints, a portable ultrasonic spiral C-scan testing instrument was developed based on the principle of ultrasonic pulse reflection. A mathematical model for the quality evaluation of RSW joints was established, and the centroid of the ultrasonic C-scan image in the nugget zone of the RSW was determined based on the principle of static moment. The longest and shortest axes passing through the centroid in the image were extracted, and the ratio of the longest axis to the shortest axis (RLS) factor and the average of axis (AOA) factor were calculated, respectively, to evaluate the quality of the joint. To study the effectiveness of the detection results, tensile tests, and stereo analysis were conducted on the solder joints after sampling. The results indicate that this detection method can realize online detection and significantly improve the detection efficiency; the detection value of internal defect size is close to the true value with an error of 0.1 mm; the combination of RLS and AOA factors can be used to evaluate the mechanical properties of RSW joints. This technology can be used to solve the NDT, evaluate problems of RSW joints, and realize engineering applications.

An adaptive multivariate functional EWMA control chart

In many modern industrial scenarios, measurements of the quality characteristics of interest are often required to be represented as functional data or profiles. This motivates the growing interest in extending traditional univariate statistical process monitoring (SPM) schemes to the functional data setting. This article proposes a new SPM scheme, which is referred to as adaptive multivariate functional EWMA (AMFEWMA), to extend the well-known exponentially weighted moving average (EWMA) control chart from the univariate scalar to the multivariate functional setting. The proposed method distinguishes itself by adaptively selecting the weighting parameter in the calculation of the EWMA statistic to enhance the sensitivity of the AMFEWMA control chart across a spectrum of potential out-of-control scenarios. Such adaptability is essential in industrial processes, where multivariate functional quality characteristics are also subject to varying degrees of change. The favorable performance of the AMFEWMA control chart over existing methods is assessed via an extensive Monte Carlo simulation. Its practical applicability is demonstrated through a case study in monitoring the quality of a resistance spot welding (RSW) process in the automotive industry through online observations of dynamic resistance curves, which are associated with multiple spot welds on the same car body and are recognized as highly representative of the RSW process quality. The proposed method is implemented in the R package funcharts, available online on CRAN.

Characterization of Microstructure–Mechanical Properties Relationship in Dissimilar Resistance Spot Welding of the Advanced High-Strength Steel DP590 Steel to the Interstitial-Free Steel DC 06: EBSD Study

Characterization of Microstructure–Mechanical Properties Relationship in Dissimilar Resistance Spot Welding of the Advanced High-Strength Steel DP590 Steel to the Interstitial-Free Steel DC 06: EBSD Study

Evaluation of Corrosion and Its Impact on the Mechanical Performance of Al-Steel Joints.

Aluminum-steel joints are increasingly used in the automotive industry to meet the requirements for energy saving and emission reduction. Among various joining technologies, self-pierce riveting (SPR) and resistance spot welding (RSW) are two well-established technologies for fabricating dissimilar joints with stable and high mechanical performance. However, corrosion will occur in these joints inevitably due to different electrochemical properties, which can degrade the surface quality and the mechanical performance, such as strength. This paper presents a method of understanding the corrosion mechanisms in joining aluminum and steel. For this understanding, a hybrid method combining experimental observations, mechanical properties identification, and analytical approaches was used to assess the evolution of the impact of corrosion on the joining performance, such as traction separation curves. The study was conducted on common combinations used in the vehicles, e.g., a 1.2 mm thickness aluminum alloy (AA 6022) and 2.0 mm thickness hot deep galvanized steel (HDG HSLA 340) joined by SPR and RSW. After the fabrication of these joints, accelerated cyclic corrosion tests of up to 104 cycles were performed, which reproduced the environmental conditions to which a vehicle was exposed. By investigating the microstructural evolution within the joints, the corrosion mechanisms of SPR and RSW joints were revealed, including the initiation and propagation. Moreover, the intrinsic impact of the corrosion on the mechanical performance, including the strength, axial stiffness, and crashworthiness, was analyzed by performing a lap-shear test. It showed that as corrosion proceeds, the fracture modes and mechanical performance are affected significantly.

Nugget and corona bond size measurement through active thermography and transfer learning model

Resistance spot welding (RSW) is considered a preferred technique for joining metal parts in various industries, mainly for its efficiency and cost-effectiveness. The mechanical properties of spot welds are pivotal in ensuring structural integrity and overall assembly performance. In this work, the quality attributes of resistance spot welding, such as both nugget and corona bond sizes, are assessed by analyzing the thermal behavior of the joint using a physical information neural network (PINN). Starting from the thermal signal phase gradient and amplitude gradient maps, a convolutional neural network (CNN) estimates the size of nuggets and corona bonds. The CNN architecture is based on the Inception V3 architecture, a state-of-the-art neural network that excels in image recognition tasks. This study suggests adopting a new methodology for automatic RSW quality control based on thermal signal analysis.

Effect of external magnetic field on microstructures and mechanical properties of Ti-2Al-1.5Mn titanium alloy resistance spot welds

The excellent specific strength and elevated-temperature mechanical properties make titanium alloys essential structural materials in aerospace. Resistance spot welding (RSW) has high efficiency and cost-effective and is widely used in titanium joining. However, the exceeded welding penetration and coarse martensite α′ limit the mechanical properties of titanium welds. This paper implemented an external magnetic field (EMF) in the RSW process of Ti-2Al-1.5Mn titanium alloy, with detailed investigations into microstructure and mechanical properties. It was found that the penetration rate was reduced, and the nugget diameter was increased under the EMF. Moreover, the coarser columnar prior β grains (PBGs) and martensite α′ formed in traditional RSW transformed into the equiaxed PBGs and widmannstatten structure with α colonies. Due to the significantly improved microstructure and larger nugget diameter, the lap-shear properties were also improved.