| With the development of automobile industry,the requirement of automobile interior has been gradually improved.As an important part of automobile,the quality of automobile interior plays a decisive role in the performance and aesthetics of the whole vehicle.As the major molding process of automotive interior parts,compression molding has the advantages of efficient in production,simple in mold structure and accurate in product dimension,etc.Domestic molding technology for automotive interior developed relatively late,and the design technology of die forming of automobile interior was relatively backward.The molding process parameters are basically determined by experience,and the quality of internal quality cannot be guaranteed,resulting in waste of manpower and material resources.In order to solve the shortcomings of the existing technology,aiming at the matter of the molding precision,the poor quality of interior parts and the long period of product development,this paper takes the trunk lid trim of a certain model as the research object.The molding process parameters are optimized by using orthogonal test method,BP neural network and genetic algorithm,acquiring the optimization method of the molding process parameters and the optimal combination of process parameters of the trunk lid trim.The maj or research contents include:(1)Design of the trunk lid trim on the basis of theory,experience and effect of loading,further determined the material,demoulding angle,wall thickness,fillet,hole,dimensional accuracy.(2)The compression molding mold of the trunk lid trim is designed.Mechanical theoretical analysis of the molding of the trunk lid trim is carried out as well as the calculation of molding pressure.With the determination of the shrinkage rate,molding direction and parting surface of the trunk lid trim parts,the structure design of the concave and convex mold is completed.Simultaneously,the reinforcement of the mold,the cooling system,the material needle,the material frame,the guide shaft mold base,etc.,are designed.(3)Adoption of the orthogonal experiment,is on premise of the model made by the molding of the trunk lid trim,the evaluation indexes of maximum thinning rate,the maximum thickening rate and the shrinkage rate,and the factors of heating temperature,heating time,molding pressure and holding time.The process parameters of heating temperature,heating time,molding pressure and holding time,etc.,are optimized with the method of extreme difference analysis.Finally,the influence degree of the maximum thinning rate,the maximum thickening rate,the shrinkage rate and the optimal process parameter combination of each evaluation index are obtained.(4)Improvement on the normalization method of training samples,a BP neural network model for the optimization of the molding process parameters of the trunk lid trim is established,in view of BP neural network featured with the shortcomings of poor stability,calculation results greatly influenced by initial values and easily falling into local minimum,etc.,genetic algorithm was selected to optimize the connection weights and thresholds of BP neural networks,after which an optimized genetic neural network model for the molding process parameters of the trunk lid trim is established.The predicted results show that the predicted accuracy of the optimized BP neural network model has improved dramatically,and that the validity and reliability of the established neural network model are verified,as well as the trend of the evaluation index with the process parameters is obtained.(5)The global optimization of the given process parameters is carried out by using the genetic algorithm,the optimal process parameter combination of compression molding of the trunk lid trim is obtained,and the validity of the optimal process parameters is verified as the compression molding experiment is carried out with the rounding optimal process parameters.Innovative points:(1)This paper has analyzed the mechanical theory of the compression molding of the trunk lid trim,deduced the formula for calculating the molding pressure,calculated the molding pressure,and provided a basis for designing the mold and experiment.(2)Analysis of the orthogonal experiment results of the molding of the trunk lid trim by using the extreme difference analysis method.the degree of influence on the heating temperature,the heating time,the pressing pressure and the pressure holding time on the maximum thinning rate,the maximum thickening rate and the shrinkage rate of the trunk lid trim is obtained.(3)Improvement on the normalization method of training samples,an optimized genetic neural network model for the molding process parameters of the trunk lid trim is set up.The optimal process parameter combination for the compression molding of the trunk lid trim can be obtained by utilizing the global optimization function of genetic algorithm. |
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