Material–Structure–Process–Performance Integration Multi-Objective Optimization Design for Solid Rivet Joint

A material–structure–process–performance integration multi-objective optimization design of a magnesium/aluminum alloy punch-forming solid rivet joint based on Taguchi, grey relational analysis (GRA), and fuzzy rough set theory (FRST) weighting method was proposed. First, the material constitutive models of the rivet and riveted sheets were established through experiments. Second, simulation models of the rivet forming process and the pull-out and shear tests of the riveted joint were established, and corresponding experiments verified accuracy. Finally, the FRST weighting method was proposed. The integration multi-objective optimization of a rivet joint was conducted based on Taguchi, GRA, and FRST methods with optimization objectives (the rivet forming head’s dimensions and the riveted joint’s maximum pull-out and shear forces) and design variables (the material, structure, and riveting process parameters of the rivet joint). The optimal combination of design variable levels was obtained. Optimization results show that the rivet forming head’s dimensions were quite close to the recommended values after optimization, and the pull-out and shear mechanical strengths of the riveted joint were increased by 10.7% and 12.8%, respectively. Furthermore, a comparison was presented among FRST, principal component analysis, and entropy weighting methods. The FRST weighting method was concluded to be highly effective.