In this paper, the finite element and abductive network methods were used to obtain a runner-system design to reach minimum warpage on an injection moulded parts with free-form geometry. This study uses the diameter and length of the runner-system as the major control parameters. In the model creation stage, FEM simulation data were used to derivate an accurate abductive network model for predicting warpage in injection moulded parts corresponding to different control parameters.In the optimization stage, the simulated annealing (SA) method was used. This abductive methodology allows user to efficiently discover an optimal set of parameters without involving complex iteration between the optimization process and FEM simulation.
The subject of this study is a finite element and abductive network method application for the multicavity die. In order to select the optimal cooling system parameters to minimise the warp of a die-casting die, the Taguchis method and the abductive network are used. These methods are applied to create an efficient model with functional nodes for the considered problem. Once the cooling system parameters are developed, this network can be used to predict the warp for the die-casting die accurately. A simulated annealing (SA) optimisation algorithm with a performance index is then applied to the neural network for searching for the optimal cooling system parameters, and obtains a rather satisfactory result as compared with the corresponding finite element verification.
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