Spot welding

About: Spot welding is a research topic. Over the lifetime, 12491 publications have been published within this topic receiving 89845 citations. The topic is also known as: Spot_welding.

Predicting the hardness profile across resistance spot welds in martensitic steels

Abstract: Much work has been done in the area of modelling resistance spot welding Most of this work predicts the weld geometry resulting from particular process parameters This is well known and can be easily predicted using low-cost tools Predicting post-weld properties is much more difficult though Most of this work needs large computing power and complex modelling techniques such as neural networks This is made more complex when welds exhibit heat-affected zone softening This study proposes a simple three-step method to model the hardness profile of resistance spot welds First, the temperature history throughout the weld zone is calculated Second, known models describing the local phase transformations that occur during welding are applied Finally, the results across the weld are assembled into the hardness profile prediction The validity range of this model is wide in terms of martensite chemical content, sheet thickness and process parameters Predictions were validated against welds in three martensitic steels with varying amounts of carbon and alloying additions

Development of weld lobe for resistance spot-welded TRIP800 steel and evaluation of fracture mode of its weldment

Abstract: The weld lobe in spot welding provides an indication of good quality joining and the tolerance of the weld schedule in production stage. In this study, TRIP800 steel was used for the experiments, and welding times of 5, 10, 15, 20, and 25 cycles were selected with welding currents ranging from 1 to 7 kA with an interval of 2 kA and from 7 to 10 kA with an interval of 1 kA. The effect of heat input associated with welding current and welding time on nugget geometry, such as diameter, height, nugget size ratio, and electrode indentation, was determined by optical microscope. The welded specimens were exposed to tensile shear tests. Tensile shear strength and failure mode associated with nugget geometry and electrode indentations were also evaluated and weld lobe was drawn accordingly. It was found that the nugget diameter and nugget size ratio of TRIP800 steel spot welds should be at least 4.5√t and 0.15–0.30, respectively, for pullout failure mode, acceptable shear strength, and surface quality.

An ANFIS based approach for predicting the weld strength of resistance spot welding in artificial intelligence development

Abstract: Artificial intelligence (AI) is a modern approach which has the ability to capture nonlinear relationships and interaction effects. Frequently, AI methods have been used by researchers to predict output responses of the Resistance spot welding (RSW) due to the complex- ity during the welding process and numerous interferential factors, especially the short-time property of the process. The present study is to investigate the weld strength of spot weld for high strength steel sheets of CR780 using the Adaptive neuro fuzzy inference system (ANFIS). These results were compared with those obtained by conventional Artificial neural network (ANN). The input parameters were extracted through the dynamic resistance signal which was obtained from the primary circuit of the welding machine. Both the ANN and ANFIS models were utilized for the formulation of mathematical model with an off-line dynamic resistance response of the RSW at a particular parameters setting. The performances of both models were compared in terms of correlation coefficient value (R), Root mean squared error (RMSE), and Mean absolute percentage error (MAPE). While both methods were capable of predicting the weld strength, it was found that ANFIS model could predict more precisely than ANN.

Optimization of the cycle time of robotics resistance spot welding for automotive applications

Abstract: In the automobile manufacturing industry, resistance spot welding (RSW) is widely used, especially to build the car's body. The RSW is a standard and wide‐ranging joining technique in several assembling ventures, showing a wide range of possibilities for a competent procedure. Robots are commonly used for spot welding in various industrial applications. After completing assembling design, interest increases to improve the designed processes, cost‐reduction, environmental impact, and increase time productivity when all is said to be done. In this paper, the robot movement between two welding points, a path followed while spotting, gripping and payload‐carrying activities, numbers of holds, moves, and a possibility to enhance interaction between four Robots were analyzed using an offline Robot simulation software 'DELMIA‐V5'. The body shop assembly line of the SML ISUZU plant has four robots that perform about 209 welding spots in 532 sec. The optimal model reduced the whole welding cycle time by 68 sec, and after modification and proper sequencing, a12.7% reduction in cycle time was achieved. The offline Robot simulation software 'DELMIA‐V5' has good potential to produce optimal algorithms while saving precious time. It enables an organization to promote higher quality and to encourage meaningful creativity by reducing design flaws.