This paper proposes a process optimization method to improve the dimensional precision of riveted assemblies. The method representation and investigation use an assembly with 1093 rivets yielded from the double curved reflector. Firstly the static and dynamic finite element (FE) models respectively represent the global large-scale assembly and the local riveting process. The dimensional precision is denoted by the root mean square (RMS) of the deformations of the key points selected from the static FE nodes. Then the quantitation between RMS and process parameters equates to the iterative static FE analyses interpolating the dynamic FE analysis result and the possible former static FE analysis result. Finally the integration of the genetic and ant colony algorithms optimizes the process parameters, i.e. the rivet upsetting directions (UDs) and the assembly sequence (AS). Investigation indicates (1) both the rivet UDs and AS are the main RMS influence factors; (2) the proposed method can efficiently optimize the specific process parameters for the large-scale assembly with abundant rivets; and (3) the effective optimization prefers to solve rivet UDs and AS step by step.
Due to the complexities of calculations based on different representations of constituent parts in an assembly, the combined improvement of efficiency and precision for the riveting has seldom been studied by the sequence planning or dimensional engineering. This article develops an assembly sequence optimization method that simultaneously minimizes the path length and overall dimensional error for the solid riveting. The sequence is denoted by the order of classifications for the nodes around the rivet holes in the finite element model for the assembly. Ant colony algorithm is applied on the optimization by integrating two calculations, that is, the length calculation of riveting path and the calculation of the dimensional error related to rivet upsetting directions and assembly sequence. Results for three assemblies are presented which show a good degree of optimization in performance for different scales of assemblies with different numbers of rivets that share the same solid riveting process.
Reduction in the dimensional error of an assembly mostly focuses on the variation of fixtures and parts inside, in which the variation is mainly controlled by the methods relating to the fixture design and variation analysis. Recently, more researches concentrate on the dimensional analysis of the aluminum assembly where the distortion of rivet joints cannot be neglected, that is, the riveting-induced dimensional error. Hence, both the device design and the variation analysis for the riveting are drawing much attention to reduce the overall distortion. This article presents a dimensional reduction method, a rivet upsetting direction optimization based on a local-to-global dimensional calculation. The method is developed from a recent framework of assembly process optimization according to the discovered sensitivity between global dimensional error and rivet upsetting directions. A potential function that gathers the overall effect of every locating error is included. Simulations for three riveted assemblies are presented for comparison and results show that the method is efficient for the specific assignment of every rivet upsetting directions, and the effects of locating errors and rivet upsetting directions are highly coupled. The coupled effect yields the key questions in the improvement of this method. Detailed suggestions are then summarized.
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