Sheet Metal Forming Process Design Rules Development

Abstract

Finite element analysis (FEA) is a powerful tool to evaluate the formability of stamping parts during process and die design development procedures. However, in order to achieve good product quality and process reliability, FEA application has to be performed many times exploring different process parameters combinations. Meanwhile, it is very difficult to perform an exhaustive process design definition when many parameters play a fundamental role to define such a complex problem. So, under the needs of reduction in: design time, development cost and parts weight, there is an urgent need to develop and apply more efficient methods in order to improve the current design procedures. For a generic component it is clear how its shape, among several parameters, has a direct influence on its feasibility. Starting from this assumption, the authors have developed a new approach grouping components upon their shapes analyzing component formability within a given “component family”. Nowadays, it exists only a process designer “sensitivity” that produces a ranking upon shape/feasibility ratio. Having as reference industrial test cases, the authors have defined appropriate shape parameters in order to have dimensionless coefficients representative for the given geometries. In particular, the components have been classified using a parameters set defining similarity families: related to geometrical aspects and to constitutive material. From the geometrical point of view the following parameters have been defined: family name, shape factor, punch radius-thickness ratio, die radius-thickness ratio, while for the constitutive material a code has been defined. FEA has been extensively used in order to: define, investigate and validate each shape parameter with a proper comparison to the macro feasibility of the chosen component geometry. The feasibility configuration definition, for a given shape, has been made through an appropriate study of the influence of each process variable on the properly process performances.