Multi-objective Optimization of Injection Molding Process Based on Vague Set and Response Surface Model
For the multi-objective optimization problem of injection molding,the warpage deformation,volumetric shrinkage rate and shrinkage depth of the plastic parts were taken as the optimization objectives,and the process parameters,such as,melt temperature,mold temperature,injection time,holding pressure and holding time were selected as experimental factors.The central composite experimental design was combined with the moldflow analysis to establish experimental samples,and the similarity of each optimization objective was calculated using the Vague set method,then the influence weight of each optimization objective was calculated by criteria importance through intercriteria correlation(CRITIC)method.A response surface model between the comprehensive similarity and various process parameters was established,and grey wolf algorithm was applied to obtain the optimal combination of process parameters.The results show that the combination of Vague sets and response surface model provide significant optimization results and provide useful reference for practical production processes.
Vague SetResponse Surface ModelGrey Wolf AlgorithmInjection MoldingMulti-objective Optimization
万方数据
维普
