Aluminum alloy sheets are widely applied as structure components in automotive, aircraft and other industries to realize lightweight. Nowadays, many high strain rate forming techniques have been developed to improve their formability and widen their application. To ensure the reliability of the aluminum alloy structure components under high strain rate conditions, it is imperative to develop a thorough understanding of the alloy’s mechanical properties. In this paper, taking high-strength 6XXX aluminum alloy sheet as an example, the anisotropic deformation characterization and corresponding material models at various strain-rate conditions are investigated systematically. The material hardening curves and anisotropic plastic yielding stresses were achieved based on the quasi-static uniaxial tensile test and the split Hopkinson tensile bar tests. In this study, the Johnson–Cook hardening model and two anisotropic yield functions are applied to well describe the strain-rate-dependent anisotropic plastic deformation behavior. In addition, the fractographic characterization of the fractured samples at various strain-rate conditions are measured and compared. The study systematically investigates the influence of strain rate on the anisotropic deformation behavior of the high-strength aluminum alloy sheets and gives the basic experimental data for their application in engineering fields in the future.

Problems such as unreasonable processability or model defects generated in the design stage will lead to continuous rework during the manufacturing process, which greatly increases the manufacturing cost of the product. Through manufacturability analysis, the process designer can find design defects that are difficult to manufacture, impossible to manufacture, or have high manufacturing costs as early as possible, so as to reduce the number of round trips between design and process, and shorten the product development cycle. However, it is difficult for the current rule-based manufacturability analysis method to obtain professional knowledge and construct a complete manufacturability analysis rule repository. Therefore, a manufacturability analysis method based on a graph neural network is proposed. First, the attribute adjacency graph and UV gridding are combined to characterize the part model data, which can effectively represent the topological information and geometric information on the part model. At the same time, parameter information on the spherical coordinate system is used to ensure rotation and translation invariance; then, based on the graph representation of the part model, a hierarchical graph neural network is constructed, which is divided into three levels, edge, node, and graph, for encoding, information transmission and updating, and expanding the receptive field for better node classification to support manufacturability analysis. Finally, graph contrastive learning is used as a regularization technique in the pre-training stage to maximize the similarity of graph representations between different views to improve prediction performance. Manufacturability analysis tests were carried out on the constructed part model dataset, and the experimental results showed that the method has good performance.

Process reuse technology has been widely studied and applied in manufacturing industry. However, the current NC process reuse generally assumes that the micro process is compatible with the macro process, but in fact, the reusable processes from the similar local structures of multiple parts are usually difficult to be compatible with each other under the overall manufacturing requirements of the query parts, which leads to the fact that a large amount of user interactions are still required for modification and adjustment in practical engineering applications, so it is not significant to improve the design efficiency. Therefore, an efficient NC process scheme generation method based on reusable macro and micro process fusion is proposed in this paper. Firstly, according to the calculation of semantic distance of process design intention, the micro processes are mapped to the macro process to realize the fusion of the macro process and the micro process, and a compatibility credibility evaluation model is established to evaluate the compatibility of fusion results. Then, when the fusion result is credible, the machining areas corresponding to the process scheme are adjusted and optimized from the geometric level. The adjustment and optimization of machining areas mainly realize the integration of machining areas and the optimization of machining sequence. Finally, the effectiveness and feasibility of the proposed method are verified by the test of actual parts.