Neural network method for inverse modeling of material deformation

Abstract

A method is described for inverse modeling of material deformation in applications of importance to the sheet metal forming industry. The method was developed in order to assess the feasibility of utilizing empirical data in the early stages of the design process as an alternative to conventional prototyping methods. Because properly prepared and employed artificial neural networks (ANN) were known to be able to codify and generalize large bodies of empirical data, they were the natural choice for this application. The product of the work described here is a desktop ANN system that can produce in one pass an accurate die design for a user-specified part shape.