Mechanical performance optimization of similar thin AA 7075‐T6 sheets produced by refill friction stir spot welding

Abstract

Refill friction stir spot welding was applied to weld similar thin AA 7075-T6 aluminum alloy sheets in a spot-like joint configuration without a keyhole. The welds were produced using a small tool consisting of sleeve and probe with diameters of 6 mm and 4 mm, respectively. Design of experiment was employed to optimize the welding parameters in terms of the cross tensile strength by using Box Behnken Design. Based on analysis of variance, it can be concluded that plunge depth strongly affects the mechanical performance of the weld. Optimal welding parameters in terms of rotational speed, plunge depth and speed are identified to reach a cross tensile strength of up to 660 N.Keywords: Friction stir spot welding / similar weld / thin sheets / small tools / tensile strength Schlüsselwörter: Rühr-Reib-Schweißen / artgleiches Schweißen / dünne Bleche / kleine Werkzeuge / Zugfestigkeit Friction stir spot welding of thin AA 7075-T6 sheets Materialwiss. Werkstofftech. 2020, 51, 830-835

A Numerical Study on the Effect of Tool Speeds on Temperatures and Material Flow Behaviour in Refill Friction Stir Spot Welding of Thin AA7075-T6 Sheets

“…The refill FSSW process was modeled in DEFORM-3D using an incremental Lagrangian formulation. The simulations in the current study replicated the prior experimental work done by Yamin et al [31] for model validation. As a result, the material, tool geometry dimensions, and refill FSSW process parameters were all taken from the experimental investigation.…”

“…The increased WT allows a rise in temperature for proper phase change of the material and improves material flowability and mixing. Similar to the RS trend, in some cases, with an increase in WT, joint strength increases initially and then drops [15,28,31]. In some studies, joint strength decreases with a rise in WT [18,19,24].…”

“…where 𝜎 denotes the material flow stress, the reference plastic strain rate is represented by 𝜀 , 𝜀 denotes the equivalent plastic strain, 𝜀 denotes the plastic strain rate, and 𝑇 and 𝑇 -the melting and reference temperatures, respectively. The material constants n-coefficient of strain hardening, m-thermal softening coefficient, A-quasi-static yield strength, B-strain hardening constant, and the strain-rate dependency are described at the reference strain rate by the strengthening coefficient C. The experiment used a commercial Al-Zn-Mg-Cu alloy AA 7075-T6 with a sheet thickness of 0.6 mm [31]. The material AA7075-T6 applied to the workpiece was loaded from DEFORM-3D's library and adhered to the Johnson-Cook material law.…”

“…However, excessive heat input with a further increase in RS will weaken the joint because of the coarsening microstructure and the reduction of bonding ligament length (dispersed lap interface) because of excessive vertical material flow. PR/welding time (WT) is the parameter with the least influence on joint strength [18,22,24,31]. In most of the earlier work, it was observed that joint strength is enhanced with an increase in the WT/decrease in PR [8,10,27,32,33].…”

Simultaneous optimization of weld bead geometry and weld strength during gas tungsten arc welding of Inconel 825 strips using desirability function coupled with grey relational analysis (DF-GRA)

“…Furthermore, Desirability function analysis (DFA) and Desirability graphical analysis (DGA) are statistical optimization techniques used to optimize various welding process parameters in various welding processes for optimum welding strength and weld bead shape. Pandiyarajan et al (2019) used the DGA approach to simultaneously optimize friction stir welded (FSW) parameters in welding a hybrid ZrO2-C-AA 6061 Composites, whilst Yamin et al (2020) implemented the same method to maximise the tensile strength of FSW welded AA7075 weldments [25,26]. Senthil et al (2020) used the DFA approach for optimizing FSW process factors for the optimum mechanical properties of Al6063-T6 joints [27].…”