The modern concept of lightweight design (LW) requires the application of different materials in one structure (multi-material structures). The structure of different materials has a good perspective for application in the automotive and aerospace industries but only if it is possible to achieve a quality joint between different materials. The most used technology for joining different materials in the automotive industry is Resistance spot welding (RSW). Due to different mechanical, physical, and chemical properties, the joining of different materials by RSW technology does not provide a quality joint, and accordingly, alternative technologies for joining different materials have emerged. Resistance element welding (REW) was developed to enable joint of different materials. This paper presents the welding of AW 5754 H22 Al alloy (1.0 mm-thick) and DP500 steel (1.5 mm-thick) using novel REW. The peak load, absorption energy, microstructure, microhardness and fatigue strength of the REW joint has been investigated. The joint of the same materials has been done also using conventional RSW to compare some results. The results that will be presented in this paper show that that REW can achieve reliable joining of the two materials at relatively low welding currents compared to RSW. Using REW process with a significantly lower welding current, satisfactory mechanical characteristics of the weld joint can be achieved, so peak load is between 2300–2500 N, displacement is between 2.5–3 mm and the absorption energy is between 3.3–5.7 J. REW joints showed fatigue strength with the fatigue limit of 882 N.
In order to ensure a quality welded joint, and thus safe operation and high reliability of the welded part or structure achieved by friction stir welding, it is necessary to select the optimal welding parameters. The parameters of friction stir welding significantly affect the structure of the welded joint, and thus the mechanical properties of the welded joint. Investigation of the influence of friction stir welding parameters was performed on 6-mm thick plates of aluminum alloy AA2024 T351. The quality of the welded joint is predominantly influenced by the tool rotation speed n and the welding speed v. In this research, constant tool rotation speed was adopted n = 750 rpm, and the welding speed was varied (v = 73, 116 and 150 mm/min). By the visual method and radiographic examination, imperfections of the face and roots of the welded specimens were not found. This paper presents the performed experimental tests of the macro and microstructure of welded joints, followed by tests of micro hardness and fracture behavior of Friction Stir Welded AA2024-T351 joints. It can be concluded that the welding speed of v = 116 mm/min is favorable with regard to the fracture behavior of the analysed FSW-joint.
Resistance spot welding (RSW) is still the most used form of welding in the automotive industry, primarily for welding steel. One of the advanced steels used in the automotive industry is dual-phase steel, so it is important to properly select the welding parameter for these steels. Therefore, this paper presents multi-objective optimization in the RSW welding process of DP 500 steel. The paper considers three different mechanical characteristics i.e., the failure load (F), failure displacement (l) and weld nugget diameter (D), as all these welding characteristics play significant roles in evaluating the quality of spot welding. The results show that the welding current is the most influential parameter with respect to the mechanical characteristics. The effect of welding time on the weld quality is the least significant. The optimal parameters for welding DP 500 steel obtained in this paper are weld current 8 kA, electrode force 4.91 kN and weld time 400 ms.
This paper will also present single objective optimization and Failure load prediction of Resistance spot welding of Aluminium alloy 57547. The experimental studies were conducted under varying welding currents I, electrode forces F, welding times T, pred preheating currents IA. The settings of welding parameters were determined by using the Taguchi experimental design of L9 Orthogonal array method. For optimization and prediction will be used analysis of Signal-to-Noise (S/N) ratio and Response surface modelling RSM.
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