Effective strategies of metamodelling of industrial metallurgical processes. (November 2015)

• Record Type: Journal Article
• Authors: Kusiak, J.; Sztangret, Ł.; Pietrzyk, M.
• Is Part Of: Advances in engineering software. Volume 89(2015)
• Page Start: 90
• Page End: 97
• Publication Date: 2015-11
• Subjects: Metamodelling -- Artificial Neural Network -- Kriging -- Response Surface Methodology -- Process modelling -- Optimization; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2015.02.002
• Languages: English
• ISSNs: 0965-9978

Abstract

Abstract: The main objective of the metamodelling is replacing the model of analysed process by its simple (with respect to the computation time) approximation. Metamodel gives a significant reduction of computation time of considered process simulation, as well as its further analysis (sensitivity analysis, optimization, etc.). The paper discusses the idea of metamodelling and compares the effectiveness of three techniques: Response Surface Methodology (RSM), Kriging method and Artificial Neural Network (ANN) applied to the benchmark functions. An example of the use of the considered metamodelling techniques in optimization of the problem of laminar cooling of rolled Dual Phase (DP) steel strips is presented. Metamodelling and optimization of a real industrial metal forming problems seems a novel approach in the field of research on Artificial Intelligence and Optimization practical applications.