Small-scale Resistance Spot Welding Research Articles

Advances in small-scale resistance spot welding of the Ni-15 %Fe-4 %Mo-1 %Mn permalloy in the production of low-noise ring cores for fluxgate magnetometers

The aim of this study was to assess the possibility of improving control of small-scale resistance spot welding (SSRSW) of the Ni-15 %Fe-4 %Mo-1 %Mn permalloy in the production of low-noise ring cores for fluxgate magnetometers. It was found that the range of the optimal current–time parameters (weld lobe) was within current amplitudes of 1–2 kA and pulse durations of 6–14 ms, which allowed to form sound nuggets with sufficient diameters but without expulsions in most cases. A preheating stage (a pulse with an amplitude of about 1 kA and a duration of 3–4 ms) had a positive effect on the stability of both dimensions and mechanical characteristics of the investigated nuggets. A decrease in the solidification rate slightly improved the stability of tensile shear strength values of the SSRSW joints despite the absence of fundamental differences in the microstructure and phase composition of the weld metals. To determine the reliability of predicting the quality of the SSRSW joints by assessing dynamic resistances measured during the formation of nuggets, a comparative statistical analysis of their diameters and the tensile shear strength values was carried out. The obtained results did not reveal any strong correlation between these parameters.

Effects of preheating and slow cooling stages in small-scale resistance spot welding of the Ti-2Al-1Mn alloy

Effects of preheating and slow cooling stages in small-scale resistance spot welding of the Ti-2Al-1Mn alloy

Contact resistance prediction of zirconium joints welded by small scale resistance spot welding using ANN and RSM models

The total electrical resistance between electrodes is a major factor in small scale resistance spot welding process uncertainty. The initial resistance between electrodes is depending on the current profile, electrode force and dome radius of hemispherical electrodes. A comparison between the experimental results of the expected resistance between electrodes and the predicted values of using ANN and RSM methods is the main goal of this study. E110 zirconium alloy with a thickness of 0.25 + 0.25 mm and 440 MPa tensile strength is used. An increase in dome radius of hemispherical electrodes reduces mean resistance values for zirconium alloy. The rate of preheating current rise has no appreciable effect on stabilization of resistance between electrodes in all cases. Stepwise current rise significantly reduces dispersion of resistance values for zirconium alloy. However, their dispersion significantly decreases after preheating in comparison with initial values. The empirical model predicted by the response surface methodology (RSM) is compared with the backpropagation algorithm model of artificial neural networks (ANN). On zirconium specimens, the absolute maximum error in RSM technique was 9.92% while 4.43%in ANN. Furthermore, in most cases the absolute maximum error in ANN is lower than RSM.

Metallurgy of a Ti–Au alloy synthesized by controlled electric resistance fusion

In this study, the first attempt was made to synthesize a Ti–Au alloy by fusing two titanium plates and a thin gold foil between them using the small-scale resistance spot welding procedure. The main goal was to study the possibility of controlling the alloy synthesis process by predefined thermal cycles (metal heating and its cooling rate). The Ti–Au alloy microstructure, chemical and phase compositions, as well as hardness distributions were studied by scanning and transmission electron microscopy, energy dispersive X-ray analysis, and nanoindentation. As a result, a weld nugget with optimal sizes for titanium alloys was formed. The average gold content in the synthesized Ti–Au alloy was about 16 at. % (42 wt %). It was distributed rather evenly throughout the nugget volume in ratios of 10–20 at. % (30–50 wt %). In addition to α-Ti and Au particles, the alloy included the Ti3Au and TiAu2 compounds corresponding to the gold content of 25 and 67 at. %, respectively. These compounds had formed in microvolumes contained high gold concentrations for a period of less than 3 ms. Hardness values were from 6 up to 7 GPa in the regions most enriched in gold, and they were about 4 GPa where the gold content was minimal. Based on the obtained results, some ways were proposed for the possible optimization of this research method.

Effects of Electrode Degradation on Properties of Small-Scale Resistance Spot Welded Joints of E110 Alloy

Effect of electrode degradation on stability of nugget formation during small-scale resistance spot welding is presented in this paper. Production of spacer grids for nuclear fuel assemblies made of E110 zirconium alloy cells of 0.25 mm thickness was studied. The following degradation processes took place in the electrodes as they wore. Roughness of the tip surface was gradually reduced to the values of the welded cells. The semispherical tips were severely deformed during the initial period of their operation (1.500...2.000 welds). The deformation dynamics slowed down significantly after that. Microhardness on the tip surface of the electrodes decreased. It was minimal in the central part of the surface layer with a thickness of 50...100 μm and increased towards the periphery. Significant coarsening of the electrode metal microstructure occurred at a depth of ~ 1 mm. Nugget area and its tensile strength decreased as the electrodes wore. An increase in welding current did not reduce deterioration of nugget quality. Measurement and processing of dynamic resistance between electrodes did not make it impossible to predict and control the properties of nuggets for the studied welding modes.

Optimization of Welding Parameters for Small-Scale Resistance Spot Welding of Zirconium Alloys

This paper presents the results of optimization of parameters for resistance spot welding of parts made of E110 zirconium alloy with a thickness of 0.25 + 0.25 mm. Its purpose was to determine the influence of welding current profiles on nugget metal structure and mechanical properties of welds. The highest tensile strength comparable with base metal (380...440 MPa) was observed when the ratio of integral heat input to current pulse duration was about two. Formation of martensitic structure and coarsening of nugget metal was observed with larger ratios. A proper fusion zone was not formed with lower ratios. Annealing of welded joints at a pressure of ~ 10–4 Pa and a temperature of 580 °C for one hour was necessary to reduce residual stresses and transformation of metastable martensitic phase to a more stable state. This reduced microhardness of nugget metal by 30...35% and increased tensile strength of welds. It was also possible to increase tensile strength and reduce dispersion of its values by increasing duration of current down slope after formation of a nugget. An increase in duration from 1 to 14 ms caused rise in tensile strength by ~ 18% and dispersion of its values by ~ 3%.

Prediction and stabilization of initial resistance between electrodes for small-scale resistance spot welding

Quality of resistance spot-welded joints depends on Joule’s heat generation and, in turn, a current profile, dynamic resistance change, and its initial value. In the present work, the impact of electrode force and dome radius of hemispherical electrodes on initial resistance between electrodes was investigated. Two combinations of workpieces of zirconium alloy thickness of 0.25 + 0.25 mm and austenitic stainless steel thickness of 0.3 + 0.3 mm were used. The experimental results obtained were compared with calculated values using published equations and data on physical properties of these materials. After that, the possibility of stabilization resistance between electrodes by preheating current pulses was studied. The pulses had different algorithms of current rise: discrete and stepwise, as well as sharp and smooth with longer upslope. The results show impossibility of reliable prediction and absolute stabilization of initial values of resistance between electrodes. No clear relationship between these values and electrode force has been found. An increase in dome radius of hemispherical electrodes reduces mean resistance values for zirconium alloy but has no effect for stainless steel. Also, it does not affect dispersion of values for both materials. The rate of preheating current rise has no appreciable effect on stabilization of resistance between electrodes in all cases. Stepwise current rise significantly reduces dispersion of resistance values for zirconium alloy but has no effect for stainless steel. However, their dispersion significantly decreases after preheating in comparison with initial values.

Quality Estimation in Small Scale Resistance Spot Welding of Titanium Alloy Based on Dynamic Electrical Signals

Quality Estimation in Small Scale Resistance Spot Welding of Titanium Alloy Based on Dynamic Electrical Signals

Using a New Electrical Contact Resistance Model for Investigating Nugget Diameter Variations in Small-Scale Resistance Spot Welding

Small-scale resistance spot welding is used frequently in various industries. The key factor that affects the welding quality is the nugget size. In this paper, the relationship between the nugget size and the input process parameters is investigated. A new practical equation is provided to calculate the electrical contact resistance that does not require the information about the contact points. To perform a simulation of the process, resistance spot welding is considered as an electrical–thermal–mechanical process in the finite element model. Thermal expansion and electromagnetic heating are considered. The film layer on the sheets is also modeled. The simulation is carried out using a three-dimensional model in COMSOL Multiphysics. Electrical contact resistance is applied using the relation that is obtained in the theoretical analysis. The results of the simulation work are validated through performing experimental validation on Hastelloy X sheets of thickness 0.4 mm. It is observed that the finite element model can efficiently and accurately determine the high-temperature contours. Also, it was concluded that increasing time and current enlarges the nugget diameter.

Investigating Mechanical Properties of Small Scale Resistance Spot Welding of a Nickel Based Superalloy through Statistical DOE

Nowadays small scale resistance spot welding is used frequently because of the requirements of miniaturization in industries. It is known that contact resistance is the most essential factor in heat generation process. In this study a new equation is provided to calculate the electrical contact resistance that does not require the number of contact points, the size, shape and distribution of them. To perform a simulation of the process, resistance spot welding is considered as an electrical-thermal-mechanical process in the finite element model. The simulation is done using a three dimensional model in COMSOL Multiphysics. The results of the simulation work are validated through performing experimental validation on Hastelloy X sheets. A new set-up is designed and constructed to study the effects of parameters in small scale resistance spot welding. Also, the relationships between mechanical properties and weld nugget dimensions and process parameters such as electrode force, welding current and welding time is evaluated. A DOE analysis is carried out to verify the significance of input factors on the nugget diameter, maximum load and nugget height. It was concluded that the nugget diameter increases with increasing time of current passing and decreases with increasing force. Also, increasing the current increases the nugget diameter. The maximum strength is obtained by applying maximum force, maximum time and minimum up to moderate currents. Optical metallography results demonstrated primary carbides (M6C) at the base metal and widmanstatten platelets at the weld area. It was found out that the maximum hardness occurs in the weld area.

A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

Optimal welding parameters for small-scale resistance spot welding with response surface methodology

In this study, Ti–1Al–1Mn thin foils with thickness of 0.05 mm were welded by small-scale resistance spot welding. Welding current, electrode force and welding time have been changed while other welding parameters remained constant. The welded joints were subjected to tensile shear tests for determining the values of shear force and absorption energy. A quadratic model of response surface methodology based on Box–Behnken design was employed in establishing regression equations between input variables (current, electrode force and time) and output variables (shear force, absorption energy, variance of shear force and variance of absorption energy). The models were satisfied in optimising the welding parameters. Besides, the microstructure analysis on the typical spot welds was also conducted.

Weld quality monitoring research in small scale resistance spot welding by dynamic resistance and neural network

Abstract Our study aims at developing an efficient quality monitoring system in small scale resistance spot welding based on dynamic resistance. The dynamic resistance variation was related to weld nugget formation process. An initial resistance peak caused by asperity heating was detected. The second peak in dynamic resistance and single peak in dynamic voltage could be attributed to bulk material heating. An obvious interrelationship could be found between end resistance and weld quality. The features extracted from dynamic resistance curve were mainly influenced by welding current. The overall resistance level was dropped as welding current enlarged. The multiple linear regression analysis and back propagation neural network were then used to estimate the weld quality in combination with extracted features. Result of the regression analysis for quality prediction was basically satisfactory. The proposed neural network model showed a better performance than regression analysis regarding the maximum estimation error and root mean square error. Accuracy of the neural network based quality estimation could be further improved combining quality level classification strategy. Combination of the dynamic resistance measurement with neural network model was supposed effective to achieve the quality monitoring purpose in small scale resistance spot welding.

Multi-performance optimization of small-scale resistance spot welding process parameters for joining of Ti-1Al-1Mn thin foils using hybrid approach

The progressive trends of product miniaturization and light-weighting necessitate the effective microjoining of ultra-thin metal foils with high reliability and performance. In this experimental investigation, Ti-1Al-1Mn foils of 0.05 mm thickness were welded by small-scale resistance spot welding (SSRSW). The experiments based on Taguchi L27 orthogonal array have been implemented to examine the effects, significances and optimal combination of welding parameters, namely welding current, electrode force, ramping time and welding time. Performance measures viz., tensile-shear force, peel force, variances of tensile-shear and peel force were optimized by a hybrid approach comprising gray relational analysis (GRA) with principal component analysis (PCA). Furthermore, two kinds of weighted gray relational grade which extracted different numbers of principal components were put into comparison for better comprehensive performance by analysis of variance (ANOVA) and confirmation tests. It indicated that the procedure of parameter optimization should only extract all the principal components that correspond to eigenvalues larger than one. The ANOVA results showed that welding current was the most significant impact on multi-performance, followed by electrode force and ramp time, while welding time showed little effect. Finally, the optimal welding parameters combination was at welding current of 800 A, electrode force of 35.6 N, ramp time of 5 ms, and welding time of 8 ms.

Quality evaluation in small-scale resistance spot welding by electrode voltage recognition

This study focuses on weld quality evaluation by electrode voltage in small-scale resistance spot welding of titanium alloy. Voltage curve could be divided into four stages based on the variation characteristic. The single voltage peak was detected as combined effects of increasing bulk material resistivity and nugget size. Variations of voltage curve shape, voltage peak and failure load were more sensitive to welding current than electrode force. A generalised regression neural network was proposed to evaluate weld quality using features extracted from voltage signal. A discrete Hopfield neural network was also applied for electrode voltage recognition. The recognised voltage patterns were found effective in identifying different quality levels. A real-time and on-line quality monitoring system could be developed.

Microstructure and tensile behavior of small scale resistance spot welded sandwich bulk metallic glasses

In this work, a small-scale resistance spot welding method was utilized to join two dissimilar Zr-based bulk metallic glasses and to fabricate the sandwich-laminated metallic glass plates. The laminates exhibit an almost fully amorphous structure without undesirable crystallization. Elemental line scanning across the joint interface shows a uniform distribution of the main elements, demonstrating favorable metallurgical bond in the laminate. The resultant tensile strength of the welded laminate is comparable to that of the parent metallic glasses. The fractured surface of the laminate exhibits extensive multiple failure planes, suggesting that the fracture instability was mediated by a crack branching mechanism over across the joint interface. Such a crack branching mechanism results in a stepwise fracture behavior which is contrastingly different from the conventional single primary shear band dominated catastrophic fracture in monolithic metallic glasses under tension. The unique stepwise fracture behavior endows the sandwiched metallic glass laminates with an excessive strain energy absorption through the joint interface than monolithic metallic glasses. Our results demonstrate that small-scale resistance spot welding is a promising approach to scaling up metallic glasses and to fabricating metallic glass laminates with desirable mechanical performance for structural applications.

Grey relational and neural network approach for multi-objective optimization in small scale resistance spot welding of titanium alloy

The prediction and optimization of weld quality characteristics in small scale resistance spot welding of TC2 titanium alloy were investigated. Grey relational analysis, neural network and genetic algorithm were applied separately. Quality characteristics were selected as nugget diameter, failure load, failure displacement and failure energy. Welding parameters to be optimized were set as electrode force, welding current and welding time. Grey relational analysis was conducted for a rough estimation of the optimum welding parameters. Results showed that welding current played a key role in weld quality improvement. Different back propagation neural network architectures were then arranged to predict multiple quality characteristics. Interaction effects of welding parameters were analyzed with the proposed neural network. Failure load was found more sensitive to the change of welding parameters than nugget diameter. Optimum welding parameters were determined by genetic algorithm. The predicted responses showed good agreement with confirmation experiments.

Multiple Quality Characteristics Prediction and Parameter Optimization in Small-Scale Resistance Spot Welding

This study focuses on prediction and optimization of multiple quality characteristics in small-scale resistance spot welding of titanium alloy. Grey relational analysis was first conducted to roughly estimate the optimum welding parameters combination. Multiple regression analysis was then implemented for a local parameter optimization. Optimum welding parameters were determined by desirability function and multi-objective genetic algorithm approach separately. A back propagation neural network model was also performed to simulate relationship between welding parameters and single output of the first principal component. Performance of the particle swarm optimization was better than genetic algorithm in obtaining optimum welding parameters. The neural network-based model was very effective in global optimization. A good agreement could be found between experimental results and predicted weld quality characteristics. Weld quality could be found significantly improved with the proposed methods.

Quality monitoring based on dynamic resistance and principal component analysis in small scale resistance spot welding process

The present study aims at solving weld quality monitoring problem in small scale resistance spot welding of titanium alloy. Typical dynamic resistance curves were divided into several stages based on the weld nugget formation process. A smaller electrode force or lower welding current was found to promote the initial resistance peak. The bulk material heating stage could not be detected under very high welding current condition. Electrode force effect on dynamic resistance and failure load was much smaller than that of welding current. Principal component analysis was made on discrete dynamic resistance values. The first principal component was selected as independent variable in regression analysis for quality estimation. A back propagation neural network model was then proposed to simultaneously predict the nugget size and failure load. The electrode force, welding current, welding time, and first five principal components were designed as network inputs. Effectiveness of the developed model was validated through data training, testing, and validation. The realtime and online quality monitoring purpose could be realized.

Multi-response optimization in small scale resistance spot welding of titanium alloy by principal component analysis and genetic algorithm

The present study aims to solve multi-response optimization problem in small scale resistance spot welding of 0.4-mm-thick TC2 titanium alloy sheets. Welding parameters of electrode force, welding current and welding time were arranged by the central composite experimental design. Principal component analysis was conducted first on quality indicators of nugget diameter, failure load, failure displacement and failure energy. Different weighted principal components selection strategies were performed to calculate the composite weld quality indexes. Multiple stepwise regression analysis was applied to develop the mathematical function for weighted principal components prediction. Welding parameters effects and sensitivity analysis on the composite weld quality index were discussed. Welding current was found the most significant factor affecting weld quality. Optimum welding parameters determined by genetic algorithm were validated through experiments. The first principal component was supposed as the most effective and simplest quality index. Weld quality was considerably improved based on the proposed model.