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In forming technology, the principle of stress superposition is well known for a controlled influencing of the forming zone. The aim of stress superposition is to reach an additional plastification of the material, which can be used to compensate the springback effect, e.g. of bending angles or bending radii, to extend the forming limits of the material and to reduce the forming forces. The paper deals with two new forming process variants invented by the authors, which are based on the principle of stress superposition. The first is an air bending process using an additional roll for the incremental superposition of compressive stresses along the tensile zone of a bent sheet metal. The second is the new process of incremental tube forming, which is suitable for bending tubes two-and three-dimensionally to arbitrary contours. It is based on the combination of a spinning process with the free forming of tubes.

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Important quality criteria for profile bending are an accurate profile contour and an accurate cross section. During the bending process, torsion of the profile, deformation of the cross section, and deviations at the profile contour can occur. If these undesired effects are too large, the bent profile is not usable. Critical causes of profile cross section deformation are thin wall thicknesses with hollow sections. The profile torsion is favored by asymmetrical profile cross sections. These effects can be minimized by a production-correct profile design, whereby a trade-off between a production-correct design and the boundary conditions exists. Furthermore, undesired variations in the profile material properties and the profile cross section lead to deviations in the profile contour. These deviations cannot be reduced by design but by usage of a closed-loop control during bending. In this article, a software system for three-roll bending is presented that minimizes undesirable effects during bending by structure optimization of the profile cross section and application of closed-loop control. The structure optimization is based on an evolutionary algorithm and the process control uses a neuro-fuzzy controller. The structure of the software system and results of experiments are presented and discussed. 1