Capability of iterative learning control and influence of the material properties on the improvement of the geometrical accuracy in incremental sheet forming process

Incremental Sheet Forming (ISF) is a flexible technology that allows the deformation of blank sheets without the need of complex and high cost tools or equipments. One of the main lacks of ISF is the geometrical accuracy which is not comparable with the one achieved by using traditional sheet stamping processes. There are several approaches proposed to enhance this aspect and among them the Authors have developed a method based on an Iterative Learning Control (ILC). ILC consists of a cyclic and progressive error compensation method that improves the quality of the manufactured parts. ILC has been proved to be capable for optimising the production of parts with tight tolerances when dealing with ductile materials (aluminium and steel alloys) and small deformations. In this paper, the method was tested to investigate its capability in a virtual environment. The suggested compensations were checked with Finite Element Method (FEM) so to reduce the number of parts to be manufactured saving time and costs. Moreover, the algorithm was tested considering both a difficult to form material (titanium alloy) and high deformation conditions. The results demonstrated how the precision of ISF processes depends on the blank material properties. Moreover, the capabilities of ILC are shown and discussed.