Numerical and Experimental Analysis and Optimization of Process Parameters of AA1050 Incremental Sheet Forming

The incremental sheet metal forming (ISMF) process is a new and flexible method that is well suited for small batch production or prototyping. This paper studies the use of the finite element method in the incremental forming process of AA1050 sheets to investigate the influence of tool diameter, vertical step size, and friction coefficient on forming force, spring-back, and thickness distribution. A comparison between numerical and experimental results is made to assess the suitability of the model. An approach for the optimal process factors in the incremental sheet metal forming was proposed, which integrates a finite element simulation technique, artificial neural network, and genetic algorithm. This approach is incorporated to suggest a model for process factors in terms of friction coefficient (μ), vertical step size (S) and tool diameter (D). It is found that the friction coefficient decreases spring-back value whereas vertical step size results vertical force increase and minimum thickness decrease. Tool diameter increases forming force and spring-back values

Keywords:

finite element method , genetic algorithm , incremental sheet metal forming , neural network