The genetic algorithm approach for shape optimization of powder compaction processes considering contact friction and cap plasticity models
Purpose - The purpose of this paper is to present a shape optimization technique for powder forming processes based on the genetic algorithm approach. The genetic algorithm is employed to optimize the geometry of component based on a fixed-length vector of design variables representing the changes in nodal coordinates. The technique is used to obtain the desired optimal compacted component by changing the boundaries of component and verifying the prescribed constraints. Design/methodology/approach - The numerical modeling of powder compaction simulation is applied based on a large deformation formulation, powder plasticity behavior, and frictional contact algorithm. A Lagrangian finite element formulation is employed for large powder deformations. A cap plasticity model is used in numerical simulation of nonlinear powder behavior. The influence of powder-tool friction is simulated by the use of penalty approach in which a plasticity theory of friction is incorporated to model sliding resistance at the powder-tool interface. Findings - Finally, numerical examples are analyzed to demonstrate the feasibility of the proposed optimization algorithm for designing powder components in the forming process of powder compaction. Originality/value - A shape optimization technique is presented for powder forming processes based on the genetic algorithm approach.
powders friction plasticity material deforming processes production processes