Study of Residual Wall Thickness and Multiobjective Optimization for Process Parameters of Water-Assisted Injection Molding
Autor: | Shengrui Yu, Ming Yu, Jiangen Yang |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Materials science Article Subject Polymers and Plastics General Chemical Engineering Design of experiments Organic Chemistry Particle swarm optimization Core (manufacturing) 02 engineering and technology Molding (process) 021001 nanoscience & nanotechnology Residual Multi-objective optimization 020901 industrial engineering & automation TP1080-1185 Water cooling Response surface methodology Polymers and polymer manufacture Composite material 0210 nano-technology |
Zdroj: | Advances in Polymer Technology, Vol 2020 (2020) |
ISSN: | 1098-2329 0730-6679 |
Popis: | Residual wall thickness is an important indicator for water-assisted injection molding (WAIM) parts, especially the maximization of hollowed core ratio and minimization of wall thickness difference which are significant optimization objectives. Residual wall thickness was calculated by the computational fluid dynamics (CFD) method. The response surface methodology (RSM) model, radial basis function (RBF) neural network, and Kriging model were employed to map the relationship between process parameters and hollowed core ratio, and wall thickness difference. Based on the comparison assessments of the three surrogate models, multiobjective optimization of hollowed core ratio and wall thickness difference for cooling water pipe by integrating design of experiment (DOE) of optimized Latin hypercubes (Opt LHS), RBF neural network, and particle swarm optimization (PSO) algorithm was studied. The research results showed that short shot size, water pressure, and melt temperature were the most important process parameters affecting hollowed core ratio, while the effects of delay time and mold temperature were little. By the confirmation experiments for the best solution resulted from the Pareto frontier, the relative errors of hollowed core ratio and wall thickness are 2.2% and 3.0%, respectively. It demonstrated that the proposed hybrid optimization methodology could increase hollowed core ratio and decrease wall thickness difference during the WAIM process. |
Databáze: | OpenAIRE |
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