China Plastics ›› 2015, Vol. 29 ›› Issue (09): 54-59 .DOI: 10.19491/j.issn.1001-9278.2015.09.011

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Optimization Design of Injection Molding Based on EBF Neural Network and Particle Swarm Algorithm

  

  • Received:2015-03-23 Revised:2015-06-15 Online:2015-09-26 Published:2015-09-26

Abstract: The EBF neural network model was established to describe the relationship between the process parameters and warpage based on the Latin hypercube method. Compared with Kriging model, the EBF neural network model could more accurately describe the relationship between the process parameters and warpage. The process parameters were optimized with the EBF model combined with multiobjective particle swarm algorithm, and the result was compared with Neighborhood Cultivation Genetic Algorithm. It was indicated that the injection parameter optimization method based on the EBF neural network and multiobjective particle swarm algorithm approach was feasible, and the warpage was decreased by 11.64 %,production time was shortened because the packing time and cooling time were decreased by 2.53 s.

Key words: warpage analysis, neural network, particle swarm algorithm, optimization