Simulation of manufacturing and logistics systems for the 21th century

• Autorzy: Palajová S. , Figa S. , Gregor M.
• Języki publikacji: EN

Abstrakty

EN

This paper deals with computer simulation of manufacturing systems. It contains the basic simulation theory and principles of a simulation project management. Furthermore the authors introduced the idea of parametric simulation model, followed by special application areas of simulation, e.g. scheduling, emulation, metamodelling. The paper discusses the possibility to utilize a cloud computing technology in simulation. The case example of the application of simulation by the optimization of real production system concludes the working part of paper. The final part summarizes benefits and recommendations.

Słowa kluczowe

EN

simulation; emulation; metamodelling; cloud computing

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2012
• Tom: Vol. 8, no 1
• Strony: 45--57
• Opis fizyczny: Bibliogr. 11 poz., fig., tab.

Twórcy

autor

Palajová S.

• University of Zilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Univezitná 1, 010 26 Žilina, Slovak Republic

autor

Figa S.

• University of Zilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Univezitná 1, 010 26 Žilina, Slovak Republic

autor

Gregor M.

• University of Zilina, Faculty of Mechanical Engineering, Department of Industrial Engineering, Univezitná 1, 010 26 Žilina, Slovak Republic

Bibliografia

• [1] Barton R. R.: Metamodels for simulation input-output relations. In 24th Winter Simulation Conference: proceedings. New York: IEEE, 1992. ISBN 0-7803-0798-4, p. 289-299.
• [2] Figa Š., Gregor M.: JSS using simulation-based and evolutionary methods. In Digital factory management methods and techniques in engineering production. Bielsko-Biała: Wydawnictwo Akademii Techniczno-Humanistycznej, 2011. ISBN 978-83-62292-57-8. p. 19-24.
• [3] Gregor M.: Metamodel draft for modeling and simulation of continuous manufacturing systems. 2005.
• [4] Gregor M. Hromada J. Matuszek J.: Digital factory supported by simulation and metamodelling. Inżynieria produkcji 2008.
• [5] Gregor M. Medvecký Š., Mičieta B.: ZIMS- Zilina Intelligent Manufacturing System. Study, University of Žilina, 2010, p. 35.
• [6] Gregor M., Štefánik A.. Hromada J.: Lean manufacturing systems optimization supported by metamodelling. 2008.
• [7] Hromada J.: Simulation of manufacturing systems. Thesis, Žilina, 2004.
• [8] Palajová S., Figa Š.: Advanced approach in simulation of production and logistics processes. In Digital Factory 2011. ISBN 978-80-970440-1-5.
• [9] Persson A., Grimm H., Ng A.: Simulation-based optimization using local search and neural network metamodels. [online] [cit.2010-06-10]. On the Internet: http://www.his.se
• [10] Pinedo, M. 2002. Scheduling: Theory, Algorithms, and Systems. In 2nd ed. Englewood Cliffs. Prentice-Hall, NJ, 2002.
• [11] Škorík P., Štefánik A.: Emulation environment – reliable approach for designing and testing of management principles in production based on simulation, optimization and metamodelling. In InvEnt 2010.