Analysis and optimization of variable depth increments in sheet metal incremental forming

A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm. Initially, a finite element method (FEM) model was set up and then experimentally verified. And the relation between depth increment and the minimum thickness t(min) as well as its location was analyzed through the FEM model. Afterwards, the variation of depth increments was defined. The designed part was divided into three areas according to the main deformation mechanism, with D-i (i=1, 2) representing the two dividing locations. And three different values of depth increment, Delta z(i) (i=1, 2, 3) were utilized for the three areas, respectively. Additionally, an orthogonal test was established to research the relation between the five process parameters (D and Delta z) and t(min) as well as its location. The result shows that Delta z(2) has the most significant influence on the thickness distribution for the corresponding area is the largest one. Finally, a single evaluating indicator, taking into account of both t(min) and its location, was formatted with a linear weighted model. And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index. The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.