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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.


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Journal ArticleDOI
TL;DR: In this paper, the authors show that the strength of friction stir spot welds increased as bond width increased, which depended on tool speed and dwell time, and that an optimal combination of tool speeds and dwell times can maximize the strength and fracture behavior of joints.

43 citations

Journal ArticleDOI
TL;DR: In this paper, the material flow in friction stir spot welding of aluminium to both aluminium and steel has been investigated, using pinless tools in a lap joint geometry, and the flow behaviour was revealed experimentally using dissimilar Al alloys of similar strength.

43 citations

Journal ArticleDOI
Won Seok Chang, Suck-Joo Na1
TL;DR: In this paper, the authors applied the finite element method (FEM) and neural network for predicting the bead shape in laser spot welding of type 304 thin stainless steel sheets and compared the results with the calculated penetration depth and nugget size of specimens without gap.
Abstract: The finite element method (FEM) and neural network were applied for predicting the bead shape in laser spot welding of type 304 thin stainless steel sheets. The parameters of pulsed Nd:YAG laser spot welding such as pulse energy, pulse duration, sheet metal thickness, and gap between sheets were varied for various experiments and numerical simulations. The penetration depth and nugget size of spot welds measured for specimens without gap were compared with the calculated results to verify the proposed finite element model. Sheet metal thickness, gap size, and bead shape of the workpiece without gap were selected as the input variables for the back-propagation learning algorithm of the neural network, while the bead shape of the workpiece with and without gap was considered as its output variable. Various combinations of stainless steel sheet metal thickness were considered to calculate the laser-spot-weld bead shape of the workpiece without gap, which was then used as the input variable of neural network to predict the bead shape for various gap sizes. This combined model of finite element analysis and neural network could be effectively applied for the prediction of bead shapes of laser spot welds, because the numerical analysis of laser spot welding for the workpiece with gap between two sheets is highly limited.

43 citations

Journal ArticleDOI
P.S. James1, H.W. Chandler1, J.T. Evans1, J. Wen1, D.J. Browne, C.J. Newton 
TL;DR: In this paper, the effect of sliding in breaking down contact resistance of sheet with an insulating surface film has been investigated using pre-treated (coated) and abraded aluminium alloy strip.
Abstract: Measurements of contact resistance, related to resistance spot welding, were made using pre-treated (coated) and abraded aluminium alloy strip. With conventional domed electrodes, the contact resistance was much larger at the sheet-to-sheet (faying) contact than at the electrode-sheet contact. The effect is believed to be associated with the role of sliding in breaking down contact resistance of sheet with an insulating surface film. When the coating was removed the difference between faying surface and electrode-sheet contact was much smaller. Macroscopic shear stresses are developed by electrode-sheet contact whereas no shear stresses are present at the faying surface. The hypothesis is supported by experiments made with asymmetrical electrode pairs which give rise to varying shear stresses in faying surface contact. Some implications for the control of spot welding of different aluminium surfaces are discussed.

43 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of weld time and the influence of different weld atmospheres in the resistance spot weldability of AISI304 grade stainless steel deformed in tension by 5, 10, or 20 was analyzed.

43 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023208
2022415
2021355
2020620
2019739
2018744