Modelling and Simulation Method for Production Process Automation in Steel Casting Foundry

• Autorzy: Kampa A. , Gołda G.

Identyfikatory

DOI

10.24425/118810

• Języki publikacji: EN

Abstrakty

EN

The problem of production flow in steel casting foundry is analysed in this paper. Because of increased demand and market competition, a reorganisation of the foundry process is required, including the elimination of manual labour and the implementation of automation and robotisation of certain processes. The problem is how to determine the real difference in work efficiency between human workers and robots. We show an analysis of the production efficiency of steel casting foundry operated by either human operators or industrial robots. This is a problem from the field of Operations Research for which the Discrete Event Simulation (DES) method is used. Three models are developed, including the foundry before and after automation when taking into consideration parameters of the availability of machines, operators and robots. We apply the OEE (Overall Equipment Effectiveness) indicator to present how the availability, performance and quality parameters influence the foundry’s productivity. In addition, stability of the simulation model was analysed. This approach allows for a better representation of real production processes and the obtained results can be used for further economic analysis.

Słowa kluczowe

EN

automation in foundry; robotics in foundry; transport systems in foundry; discrete event simulation; human factors; overall equipment effectiveness

PL

automatyzacja odlewnictwa; robotyka w odlewni; systemy transportowe w odlewni; symulacja zdarzeń dyskretnych; czynniki ludzkie; ogólna efektywność sprzętowa

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2018
• Tom: Vol. 18, iss. 1
• Strony: 47--52
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Kampa A.

• Silesian University of Technology, Institute of Engineering Processes Automation and Integrated Manufacturing Systems, Gliwice, Poland

autor

Gołda G.

• Silesian University of Technology, Institute of Engineering Processes Automation and Integrated Manufacturing Systems, Gliwice, Poland

Bibliografia

• [1] Creighton, D. & Nahavandi, S. (2003). Application of discrete event simulation for robust system design of a melt facility. Robotics and Computer Integrated Manufacturing. 19(6), 469-477. DOI: 10.1016/S0736-5845(03)00057-7.
• [2] Kukla, S. (2008). Rationalization of foundry processes on the basis of simulation experiment. Archives of Foundry Engineering. 8(3), 65-68.
• [3] Matuszek, J. & Kukla, S. (2009). Analysis of foundry production systems on the basis of modelling and simulation. Acta Mechanica Slovaca. 13(2), 106-111.
• [4] Saidabad, A.A. & Taghizadeh, H. (2015). Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry). American Journal of Computational Mathematics. 05(04), 431-446.
• [5] Hans, E. & van de Velde, S. (2011). The lot sizing and scheduling of sand casting operations. International Journal of Production Research. 49(9), 2481-2499. DOI: 10.1080/00207543.2010.532913.
• [6] Stawowy, A. & Duda, J. (2012). Models and algorithms for production planning and scheduling in foundries – current state and development perspectives. Archives of Foundry Engineering. 12(2), 69-74. DOI: 10.2478/v10266-012-0039.
• [7] Mourtzis, D., Doukas, M. & Bernidaki, D. (2014). Simulation in Manufacturing: Review and Challenges. Procedia CIRP, 25, 213-229. http://dx.doi.org/10.1016/j.procir.2014.10.032.
• [8] Kampa, A., Gołda, G. & Paprocka, I. (2017). Discrete Event Simulation Method as a Tool for Improvement of Manufacturing Systems. Computers. 6, 10; DOI:10.3390/computers6010010.
• [9] Robinson, S. (2008). Conceptual modelling for simulation part I: definition and requirements. Journal of the Operational Research Society. 59(3), 278 - 290.
• [10] Gołda, G., Kampa, A. & Paprocka, I. (2016). Modeling and simulation of manufacturing line improvement. International Journal of Computational Engineering Research. 6(10), 26- 31.
• [11] Paprocka, I., Kempa, W., Kalinowski, K., Grabowik, C. (2015.) Estimation of overall equipment effectiveness using simulation programme. In Modern Technologies in Industrial Engineering (ModTech2015), 17-20 June 2015, Mamaia, Romania. Eds.: E. Oanta, R. Comaneci, C. Carausu, M. Placzek, V. Cohal, P. Topala, D. Nedelcu. Bristol: Institute of Physics Publishing, 1-6.
• [12] Hansen, R.C. (2005). Overall Equipment Effectiveness. New York: Industrial Press.
• [13] Barney, M., McCarty, T. (2001). The new Six Sigma. New York: Prentice Hall Professional.
• [14] Vorne. World Class Manufacturing. Retrieved May 16, 2017, from http://www.oee.com/world-class-oee.html.
• [15] Madanhire, I., Mbohwa, Ch. (2015). Enhancing Maintenance Practices at a Casting Foundry: Case Study. In Proceedings of the World Congress on Engineering 2015 Vol. II WCE 2015, July 1 - 3, London, http://www.iaeng.org/publication/WCE2015.
• [16] Kukla, S. (2009). Total productive maintenance on example of automated foundry lines. Archives of Foundry Engineering. 9(3), 71-74.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)