Experimental and numerical study on warm single-point incremental sheet forming (WSPIF) of titanium alloy Ti–6Al–4V, using cartridge heaters

The single-point incremental forming process is an emerging process, which presents an alternative to the conventional sheet metal forming processes like hydroforming and drawing. It is known to be perfectly suited for prototyping and small series. For example, the incremental forming process offers the possibility of manufacturing medical prosthesis or implants specific to each patient, which are more comfortable and guarantee better performance. The customization of this type of product brings better efficiency and better comfort. However, the manufacture of customized titanium prosthesis is not yet industrialized, mainly due to the geometrical inaccuracy of the parts and inability to form parts with a high wall angle. In fact, considerable forces and damage occur during the process limiting the formability. Several studies have already shown that increasing the working temperature allows improving the formability. A reverse engineering approach associated with warm single-point incremental forming process, in order to produce a customized titanium prosthesis, can make the ability to be exploited in the industry to manufacture titanium alloys medical shapes. In this paper, an experimental and numerical study of the warm incremental process based on the use of heat cartridges is performed. The objective is to demonstrate that our low-cost heating system can be used in forming limit angle similar to that obtained with expensive laser heating. The effects of the wall angle at 450 °C on the forming force, thickness distribution and displacement are investigated by producing a truncated cone with Ti–6Al–4V thin sheets. Results show that the formability is significantly improved with the heating. In addition, a thermo-viscoplastic constitutive model is used to simulate the warm incremental forming process. A comparison of the numerical and experimental results shows that the finite element model gives accurate predictions.