Application Of Radial Basis Function Metamodel For Optimization Of Sheet Metal Forming

Sheet metal forming is a very important plastic working technology which has been widely used in such industrial domains as motocar, aviation and spaceflight, etc.. However, sheet metal forming usually experiences very complicated deforming processes, which make it vital reasonably deciding the forming process in order to improve the product quality and guarantee the production reliability. Furthermore, nowadays, the international manufacturing industry competitively aims at shortening the cycle time of product development and manufacture, cutting the development expenses, and lightening the product weight. Therefore, the optimal designs of sheet metal forming and mould structure have been paid more and more attentions by engineers and researchers of many countries.With the quick development of computer science and finite element analysis theory, making use of numerical simulation to optimize sheet metal forming has become one of the most important methods. This method can decrease mould trial cost and increase production efficiency. Nevertheless, numerical simualtion is often of blindness, which results in great consumption of time and cost, and even not obtaining satisfactory optimum relust. Sheet metal forming is generally required to meet such demands as no fracture, no wrinkle and minimum springback. While the tradidional weighted method can not well deal with the multi-objectvie optimization problem of sheet metal forming. In order to solve the problems mentioned above, the dissertation carried out researches on the following topics and obtained the corresponding results.In order to increase the moulding presicion of sheet metal forming optimization based on numerical simulation, in the dissertation, by comparing the advantages and disadvanteges of four kinds of popolar metamodel methodology, Radial Basis Function (RBF) metamodel method was proposed for sheet metal forming. By using testing functions to make comparative research on the precision of approximate models which were built by RBF under the condition of different sample amounts and different kernel function types, a conclusion was drawn: the model quality built by Reciprocal Multiquadric RBF as kernel function was highest when the sample amout was big, and the model quality built by Gaussian RBF as kernel function was highest when the sample amount was small. It was also proved that RBF metamodel methodology had high efficiency and precision. Applying this method in the forming process optimization of a cup with flange, a metamodel of relatively high precision was built, which involved blank holder force and friction coefficient's effects on the even degree of flange edge and the maximum drawing depth.In order to reduce the opitimization time of sheet metal forming approximate model, four kinds of popular multi-objective genetic algorithms were introducted, among which, NSGA-II algorithm was selected in this study. As population ranking method, elite strategy and binary tournament selecting method were adopted in NSGA-II, this algorithm became perfect and highly efficient. Testing by three different types of funcitons, it was proved that NSGA-II with high efficiency was suitable for large engineering problem adoption.RBF-NSGAII method, as a sheet metal forming optimization method based on RBF and NSGA-II, was put forward. This method was realized by programm design in matlab 7.5. The basic principle of RBF-NSGAII is as follows: setting the implicit nonlinear relation between design variables and responses through RBF metamodel methodology and Latin Hypercube Sampling design of experiment (DOE), searching Pareto resolutions and finally the optimal parameter group by NSGA-II.Application of RBF-NSGAII method in sheet metal forming process was researched. Two cases were quoted to illustrate blank shape and process parameters optimization designs. Each case included the following contents: problem description, design variables and constraint condition selection, objective function definition, DOE as well as optimization using RBF-NSGAII method. The two cases showed the feasibility and validity of RBF-NSGAII method.Application of BRF-NSGAII method in sheet metal springback was also studied. Two cases were cited to demonstrate the applying process of RBF-NSGAII in sheet metal springback optimization. Case 1 was that, to control springback after forming through optimizing technological parameters; Case 2 was that, to control auto panel springback after drawing and triming through optimizing drawbead. Each case contained the following contents: problem description, design variables and constraint condition selection, objective function definition, DOE and optimization using RBF-NSGAII method. In case 2, the optimum result was put into manufacturing practice, which showed that RBF-NSGAII method was effecive in controling and optimizing sheet metal springback.