A Software Framework for Optimization of Process Parameters in Material Production

Abstract

A framework for optimization of process parameters in material processing and production is described. The framework is designed for effective set up and solution of optimization problems as part of process design, as well as to support development of numerical models by inverse identification of model parameters. The general framework is outlined, which has been supplemented by a neural networks module in order to enable real time decision support. Simulator based on meshless method with radial basis functions (RBF) has been utilized.

Application of Artificial Neural Networks to Improve Steel Production Process

“…A fair number of parameters must be properly adjusted in order to have efficient production of material with required properties. A software framework has been developed for adjusting process parameters in material production in order to obtain the desired outcomes [22]. The framework was initially intended for use in production of carbon nanomaterials in the arc discharge reactors, and has later been applied to continuous casting of steel.…”