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Excessive coil deformation can complicate normal handling of a wound or rolled coil, cause difficulties in mass production, and introduce undesirable variations in the subsequent manufacturing processes. Four critical factors for coil deformation have been identified, i.e., radial stiffness of the coil material, winding tension, stiffness of the core which supports the coil, and lubrication. In this paper, we advance the understanding of coil deformation by developing an equivalent material model based on the internal stress distribution obtained from a two-dimensional winding-analysis model. The proposed material model is then implemented in a multi-layer finite element model to study the coil deformation under gravitational loading. This proposed framework can quantify the contribution of each factor in the coil deformation and thereby provide more scientific base in the engineering design process. The approach is used to analyze the deformation of laminate sheet coils. [ABSTRACT FROM AUTHOR]

Presents an energy approach to provide a stress-based criterion for the general double-curvature sheet under compression. Effective dimensions over the region undergoing compressive hoop stress; Effects of tube thickness, tube radius and material properties on the minimum bending radius without the occurrence of wrinkling; Use of the criterion to predict the onset of wrinkling in tube bending.

Demonstrates the ability of a neural network and a stepped binder force trajectory to control springback angle and maximum principal strain in a simulated channel forming process of sheet metal parts. Determination of the high binder force and total punch displacement of the stepped binder force trajectory; Presentation of the flowchart of the proposed control system.

The forming of sheet metal into a desired and functional shape is a process, which requires an understanding of materials, mechanics, and manufacturing principles. Furthermore, producing consistent sheet metal components is challenging due to the nonlinear interactions of various material and process parameters. One of the major causes for the fabrication of inconsistent sheet metal parts is springback, the elastic strain recovery in the material after the tooling is removed. In this paper, springback of a steel channel forming process is controlled using an artificial neural network and a stepped binder force trajectory. Punch trajectory, which reflects variations in material properties, thickness and friction condition, was used as the key control parameter in the neural network. Consistent springback angles were obtained in experiments using this control scheme. [ABSTRACT FROM AUTHOR]

Studies the prediction of springback angle in the straight flanging operation of sheet metal. Use of an analytical model, finite element method and reproducing kernel particle method (RKPM); Development of contact algorithm and computation of springback angle; Material property parameters used in flanging simulation; Evidence that kinematic hardening law has a better prediction than the isotropic hardening law.