The Influence of Tool Wear on the Mechanical Performance of AA6061-T6 Refill Friction Stir Spot Welds

The Refill Friction Stir Spot Welding (RFSSW) process—an alternative solid-state joining technology—has gained momentum in the last decade for the welding of aluminum and magnesium alloys. Previous studies have addressed the influence of the RFSSW process on the microstructural and mechanical properties of the AA6061-T6 alloy. However, there is a lack of knowledge on how the tool wear influences the welding mechanical behavior for this alloy. The present work intended to evaluate and understand the influence of RFSSW tool wear on the mechanical performance of AA6061-T6 welds. Firstly, the welding parameters were optimized through the Designing of Experiments (DoE), to maximize the obtained ultimate lap shear force (ULSF) response. Following the statistical analysis, an optimized condition was found that reached a ULSF of 8.45 ± 0.08 kN. Secondly, the optimized set of welding parameters were applied to evaluate the wear undergone by the tool. The loss of worn-out material was systematically investigated by digital microscopy and the assessment of tool weight loss. Tool-wear-related microstructural and local mechanical property changes were assessed and compared with the yielded ULSF, and showed a correlation. Further investigations demonstrated the influence of tool wear on the height of the hook, which was located at the interface between the welded plates and, consequently, its effects on the observed fracture mechanisms and ULSF. These results support the understanding of tool wear mechanisms and helped to evaluate the tool lifespan for the selected commercial RFSSW tool which is used for aluminum alloys.

Nanoindentation in multi-modal map combinations: a correlative approach to local mechanical property assessment

A method is presented for the registration and correlation of property maps of materials, including data from nanoindentation hardness, Electron Back-Scattered Diffraction (EBSD), and Electron Micro-Probe Analysis (EPMA). This highly spatially resolved method allows for the study of micron-scale microstructural features, and has the capability to rapidly extract correlations between multiple features of interest from datasets containing thousands of data points. Two case studies are presented in commercially pure (CP) titanium: in the first instance, the effect of crystal anisotropy on measured hardness and, in the second instance, the effect of an oxygen diffusion layer on hardness. The independently collected property maps are registered using affine geometric transformations and are interpolated to allow for direct correlation. The results show strong agreement with trends observed in the literature, as well as providing a large dataset to facilitate future statistical analysis of microstructure-dependent mechanisms. Graphical abstract