APPLICATION OF NEURAL SIMULATION METHODS FOR TECHNOLOGICAL PARAMETERS IDENTIFICATION OF COMPOSITE PRODUCTS INJECTION MOLDING PROCESS - Alexandrov, Islam; Mikhailov, Maxim; Olejnik, Andrej (Journal of Applied Engineering Science, 2020)
The article presents the research results of technological parameters of composite material products manufacturing by the injection transfer molding method using automated tools of preproduction engineering. For the verification of computer simulation results, experimental studies have been carried out on the injection-molding machine for products from fibrous polymer composite materials. The conducted comparative analysis of calculated and actual values of impregnation technological parameters has led us to the conclusion that for the effective application of the modern software for preproduction engineering of composite products it may be necessary to make a joint correction of the input data used for the calculation obtained from the preliminary independent experimental research of the complex of properties for each used component of the composite material. For the joint correction of the input data used for the calculation and improvement of the efficiency of automation systems for the preproduction engineering of composite products, the concept of the neural simulation tools application for the technological process of composite products manufacturing by injection molding methods has been proposed. For training and testing of the neural model, experimental studies of the impregnation of the products with the surface curvature of the second-order have been conducted. The optimization problem was solved by forecasting the front movement of the technical fluid in the volume of preforms during transfer molding.
Keywords: automation of technological processes; tools of preproduction engineering; polymer composite materials; finite element analysis; injection-transfer molding; neural simulation; optimization