Idea of the optimization strategy for industrial processes

• Autorzy: Kuś W. , Mucha W.

Warianty tytułu

Programowanie genetyczne w sterowaniu otwieraniem dyszy kadzi

• Języki publikacji: EN

Abstrakty

EN

The paper is devoted to strategies used in the optimization of processes. The strategy for optimization of a process incorporates modelling with the use of design parameters, metamodelling, global sensitivity analysis and optimization algorithms. The paper discusses also the strategy for choosing a proper organization algorithm and provide an example of a computer implementation of a simple expert system, designed to help the end user follow the strategies. The presented strategy contains also some information concerning modelling with the use of the finite element method. The strategy is included as an expert system in the ManuOpti optimization of the industrial processes system.

PL

Artykuł jest poświęcony jest strategii optymalizacji procesów. Przedstawiono w nim sposób redukcji liczby zmiennych projektowych, skrócenia czasu przy użyciu metamodeli. Omówiono użycie globalnej analizy wrażliwości w celu określenia najważniejszych zmiennych projektowych. W artykule przedstawiono strategię wyboru metody optymalizacji oraz podano przykładową implementację systemu ekspertowego wspomagającego użytkownika podczas stosowania jednej z przedstawionych strategii.

Słowa kluczowe

EN

strategy; optimization; optimization algorithms; modelling

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Methods in Materials Science
• Rocznik: 2014
• Tom: Vol. 14, No. 1
• Strony: 13--19
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Kuś W.

• ŠTORE STEEL do.o., Železarska cesta 3, SI-3220 Štore, Laboratory for Multiphase Processes, University of Nova Gorica, Vipavska 13, SI-5000, Slovenia

autor

Mucha W.

• Institute of Computational Mechanics and Engineering, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland

Bibliografia

• Baudin. M., Martinez, J., M., 2012, Introduction to sensitivity analysis with NISP, downloaded from wiki.scilab.org/NISP Module, last access: 1.12.2013.
• Bonte, M. H. A., van den Boogaard, A. H., Huetink, J., 2008, An optimisation strategy for industrial metal forming processes. Modelling, screening and solving of optimisation problems in metal forming, Struct. Multidisc. Op-tim., 35,571-586.
• Bonte M. H. A., Fourment, L., Do, T., van den Boogaard, A. H., Huetink, J., 2010, Optimization of forging processes using Finite Element simulations, A comparison of Sequential Approximate Optimization and other algo¬rithms, Struct. Multidisc. Optim., 42, 797-810.
• Jarosz, P., P., Burczyński, T., 2010, Coupling of Immune Algorithms and Game Theory in Multiobjective Optimization, Artiftcal Intelligence and Soft Computing, Lecture Sotes in Computer Science, 6114, 500-507.
• Kennedy. J., Eberhart, R. C, Shi, Y., 2001, Swarm Intelligence, Morgan Kaufmann Publishers, San Francisco, USA.
• Kuś.W., Burczyński, T., 2008, Parallel bioinspired algorithms in optimization of structures, Lecture Notes in Computational Sciences, 4967', 1285-1292.
• Kuś, W., Burczyński, T., 2009, Parallel evolutionary optimization in multiscale problems, Computer Methods in Material Science, 9, 2, 347-351.
• Kuś, W., Długosz, A., Burczyński, T., 2011, OPTIM - Library of bioinspired optimization algorithms in engineering applications, Computer Methods in Material Science, 11, 1,9-15.
• Michalewicz, Z., 1996, Genetic algorithms + data structures = evolutionary algorithms, Springer-Verlag, Berlin.
• Orantek, P., 2004, Hybrid Evolutionary Algorithms in Optimization of Structures under Dynamical Loads, IUTAM Symposium on Evolutionary Methods in Mechanics, Solid Mechanics and Its Applications, 117, 297-308.
• Piegl, L., Tiller W., 1997, The NURBS Book, Series: Monographs in Visual Communication, Springer.
• Sandoval, E. H., Anstett-Colilin, F., Basset, M., 2012, Sensitivity study of dynamic systems using polynominal chaos, Reliability Engineering and System Safety, 104, 15-26.
• Szeliga, D., 2013, Metal forming identification problems. Comprehensive study, AGH, Kraków.
• de Castro, L. N., Timmis J., 2003, Artificial Immune Systems as a Novel Soft Computing Paradigm, Soft Computing, 7(8), 526-544.
• Venugopal, S., Mannan, S. L., Rodriguez, P., 2004, Strategy for the design of thermomechanical processes for AISI type 304L stainless steel using dynamic materials model (DMM) stability criteria and model for the evolution of microstructure, Journal of Materials Science, 39, 5557-5560.
• Wang, G.G., Shan, S., 2006, Review of Metamodeling Techniques in Support of Engineering Design Optimization, J. Mech. Des., 129(4), 370-380.
• Zienkiewicz, O. C, Taylor, R. L., Zhu, J. Z., 2005, The Finite Element Method: Its Basis and Fundamentals, 6th Edition, Butterworth-Heinemann, Oxford.
• ManuOpti, 2013, web page: www.projects.isim.agh.edu.pl/ ~isimproj/manuopti/page/project, last access: 1.12.2013.