Diagnosis of Sheet Metal Stamping Processes Based on 3-D Thermal Energy Distribution

Abstract

In this paper, a new approach is proposed using the 3-D thermal energy distribution of the workpiece. The new approach is based on the fact that during the stamping process, the workpiece absorbs energy to deform. This mechanical energy is converted into thermal energy. Therefore, it is possible to diagnose the stamping by analyzing the 3-D thermal energy distribution. In practice, the thermal energy distribution can be acquired using an infrared camera. However, it is often necessary to reconstruct the 3-D thermal energy distribution, which can be accomplished by using the Octree algorithm. On the other hand, one can compute the thermal energy distribution through finite-element modeling (FEM) as the baseline for diagnosis. Then, by comparison, the diagnosis can be carried out. A couple of examples are presented in detail together with the experiment validation. Note to Practitioners-These days computer-aided design (CAD) and finite-element modeling (FEM) are widely used for sheet metal stamping, especially in the automotive and aerospace industries. However, fault diagnosis and die tryout still rely heavily on the experiences of the engineers/machinists on the shop floor. An existing diagnosis method compares the strain distribution calculated using FEM and the experimental strain distribution, which is calculated from the measured deformation of the initial grid pattern. However, this method is time consuming as it requires the initial grid pattern preparation by either chemical etching or laser marking. This paper presents a new method for diagnosing sheet metal stamping processes. The new method compares the thermal distribution calculated using FEM and the experimental thermal distribution result, which can be acquired using an infrared (IR) camera. Therefore, it is more convenient to use it on the shop floor. The thermal FEM can be found based on strain FEM. However, the infrared image is 2-D and, hence, 3-D thermal distribution reconstruction is often necessary. This paper includes several practical examples. Some practical concerns, such as the conduction heat lost to the environment and the infrared camera viewing angles, are also discussed