Abstract
In this study, an artificial neural network (ANN) model was constructed to investigate the relationship between the roller path parameters to form a cylindrical cup in multi-pass conventional spinning and the thickness distribution throughout the height of a workpiece. Furthermore, the path parameters that simultaneously realize multiple target values of the workpiece dimensions were calculated instantly by the iterative solution based on the constructed model. A systematic design of the path parameters for a constant thickness distribution was established as follows. First, the roller path was expressed using 12 parameters. Second, the workpieces were spun under various experimental conditions, which were determined by partial randomization of the orthogonal array based on the Taguchi method. Third, an ANN model was trained by considering seven path parameters as inputs and five forming result values as outputs (cup height, wall thickness at 25%, 50%, and 75% of the cup height, and residual path length). Finally, the path parameters required for realizing a constant thickness were determined using an ANN model with an iterative solution. Although several samples of the training dataset exhibited non-uniform thickness distributions, the workpieces that were spun under the parameters obtained via iteration exhibited a constant thickness distribution. The parameters responsible for stretching the material in the radial direction significantly affected the thickness distribution. The most influential parameter was the increment in the axial start position for each curved pass.Graphical abstract
Highlights
Deformation mechanism in metal spinningMetal spinning enables the formation of three-dimensional shapes, such as cups, from a rotating sheet metal material using a roller
This study investigates the relationship between the parameterized roller path and the results to realize workpieces with a constant thickness by employing machine-learning techniques
Similar to the results reported by Essa and Hartley (2009), the thickness increased with increasing pfeed
Summary
Metal spinning enables the formation of three-dimensional shapes, such as cups, from a rotating sheet metal material using a roller. Quigley and Monaghan (2000) presented the strain state at the corner of the mandrel, under the roller, and at the flange in spherical conventional spinning They observed that tensile strain in the radial direction, compressive strain in the thickness direction, and an extremely small circumferential strain occurred in all regions. The objectives of this study are to investigate (1) the applicability of ANN in metal spinning, (2) the effectiveness of an iterative solution to determine the path parameters under which the workpiece is formed to achieve the desired configuration, and (3) the effects of the path parameters on the thickness distribution
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