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Abstract: With the development of the technology, miniature and portability become the trends in manufacturing business. It is more and more important to miniaturize blank size in micro-forming process as well. Therefore, the researchers of micro-forming focus on this trend and try their best to study the problems and find the best solution. This paper presents an effective and practical mathematical modeling to describe the material behavior of any thickness and any grain size in micro-forming. Using this modeling, the cylindrical micro-cup deep drawing is analyzed by explicit dynamic finite element method. The simulation results show that thickness variety and stress distribution are reasonable. This investigation proves that the new mathematical modeling of material behavior will supply a useful modeling which takes into account the thickness and grain size effects in micro-forming. [Copyright &y& Elsevier]

Abstract: A methodology for formulating an elasto-plastic finite element model was developed to analyze the direct penetration and re-penetration in the hole-flanging process. The model was based on the updated lagrangian formulation, Prandtl-Reuss flow rule, and Hill''s yield criterion. Simulation results included the relationship between punch load and punch stroke, the variation of the workpiece thickness, and the forming limit. Two sets of tools with different dimensions were designed for experiments to verify the reliability of the program. By using the designed tools for re-penetration process, this paper studied the effect of the direct penetration and re-penetration on the workpiece. Besides, this paper also discussed the comparison of experiments and numerical analysis between penetration and re-penetration processes. According to the comparison between simulation and experiment, the punch load of re-penetration was less than the punch load of direct penetration. The maximum punch load increased remarkably upon decreasing the profile radius of cylindrical punch and the initial diameter of the inner hole of blank. Moreover, the re-penetration had better formability than the direct penetration in the same condition. The forming limit ratio of the re-penetration process was improved from 2.70 to 2.97. The simulation results showed good agreement with the experiments. [Copyright &y& Elsevier]

Abstract: This paper presents a forward–inverse prediction scheme that combines explicit dynamic finite element method (FEM), true strain method (TSM), and adaptive-network-based fuzzy inference system (ANFIS) to determine the anisotropic optimum blank in stretch flange process. It is not easy to guess the blank shape in stretch flange process using traditional trials. The forward–inverse prediction scheme can efficiently determine the optimum blank and improve the shrink phenomenon of the flange target. In the present study, the initial shape of the nearby optimum blank could be predicted quickly by the forward scheme of TSM at first. Then, several blanks with parallel curves to this shape are created and analyzed by explicit dynamic FEM to establish the training database for the inverse scheme of ANFIS. From the hybrid-learning algorithm, ANFIS can be efficiently trained for the optimum blank shape, and the prediction knowledge rule database can be accomplished. Using the trained ANFIS, the exact optimum blank shape of stretch flange can be inversely predicted more correctly and efficiently. Moreover, the stretch flange experiments are performed using non-optimum and optimum blanks. It also shows that a good agreement is achieved from comparison between simulated and experimental results, such as punch load, punch stroke and deform shape. From this investigation, the forward–inverse scheme is proved to be able to supply a useful optimum preform in the metal forming category. [Copyright &y& Elsevier]