Research on Intelligent Optimization Method of Multidimensional Process Quality Parameters

The intelligent optimization of multidimensional process quality parameters are of great significance for improving the process quality and intelligence of manufacturing process. Manufacturing process is complex with numerous parameters. In view of the coupling, nonlinear and uncertainty of multidimensional process quality parameters, this paper uses ensemble learning method to build the parameter mapping model which on behalf of the non-linear mapping relationship between the multidimensional process quality parameters and process quality. The objective function is constructed and the intelligent optimization of multidimensional process quality parameters in manufacturing process is realized by using firefly optimization algorithm. Taking the gluing process as an example, the accuracy of the multidimensional process quality parameter mapping model and the effectiveness of the optimization method are verified, which provide support for improving the process quality and intelligent manufacturing process.