(Springer, 2024-10-31) Gil del Val, Alain; Penalva Oscoz, Mariluz; Veiga Suárez, Fernando; El Moussaoui, Bilal; Ingeniería; Ingeniaritza
Minimizing geometric error in the bending of large sheets remains a challenging endeavor in the industrial environment. This specific industrial operation is characterized by protracted cycles and limited batch sizes. Coupled with extended cycle times, the process involves a diverse range of dimensions and materials. Given these operational complexities, conducting practical experimentation for data extraction and control of industrial process parameters proves to be unfeasible. To gain insights into the process, finite element models serve as invaluable tools for simulating industrial processes for reducing experimental cost. Consequently, the primary objective of this research endeavor is to develop an intelligent finite element model capable of providing operators with pertinent information regarding the optimal range of key parameters to mitigate geometric error in the bending of large sheets. This prediction model is based on response surface method to predict the bending diameter of the pipe taking into account three main process parameters: the plate thickness, the length, and the roll displacement. These results present promising prospects for the automation of the industrial process because the average geometric error in curvature is recorded at 0.97%, thereby meeting the stringent industrial requirement for achieving such bending with minimal equivalent plastic deformation.
