A SIMULATION EXPERIMENT AND MULTI-CRITERIA ASSESSMENT OF MANUFACTURING PROCESS FLOW VARIANTS TESTED ON A COMPUTER MODEL
Sławomir KUKLA
skukla@ath.bielsko.plDepartment of Production Engineering, University of Bielsko-Biala,ul. Willowa 2, 43-309 Bielsko-Biała (Poland)
Marek SMETANA
Department of Civil Protection, Faculty of Safety Engineering, VŠB – Technical University of Ostrava, (Czechia)
Abstract
The article presents issues relating to designing and improvement of manufacturing processes based on a modelling and simulation method. The 3D model of a production line has been designed and simulation experiment, conducted on the Arena model prepared in a versatile package for modelling and simulation of manufacturing systems and representing functioning of the system, has been carried out. The results obtained from the experiment and analyses of time and ergonomics of work at a work station were subject to multi-criteria assessment based on a point-by-point method of assessment according to Yager.
Keywords:
computer model, simulation experiment, multi-criteria assessmentReferences
Dennis, P. (2016). Lean Production simplified. Boca Raton: CRC Press Taylor &Francis Group.
Google Scholar
Dima, I., Man, M. (2015). Modelling and simulation in management. Switzerland: Springer International Publishing.
DOI: https://doi.org/10.1007/978-3-319-16592-9
Google Scholar
Falzon, P. (2015). Constructive ergonomics. Boca Raton: CRC Press.
DOI: https://doi.org/10.1201/b17456
Google Scholar
Kelton, W. D., Sadowski, R. P., & Sturrock, D. T. (2007). Simulation with ARENA. New York: McGraw-Hill Inc.
Google Scholar
Kłos, S., Patalas-Maliszewska, J., & Trebuna, P. (2016). Improving manufacturing processes using simulation methods. Applied Computer Science, 12(4), 7–17.
Google Scholar
Kukla, S. (2014). Multi-criterion assessment of different variants of casts manufacturing processes. Archives of Foundry Engineering, 14(3), 47–50.
DOI: https://doi.org/10.2478/afe-2014-0060
Google Scholar
Kukla, S. (2016). Quality and safety assurance of iron casts and manufacturing processes. Archives of Foundry Engineering, 16(2), 17–20.
DOI: https://doi.org/10.1515/afe-2016-0019
Google Scholar
Maciąg, A., Piertroń, R., & Kukla, S. (2013). Prognozowanie i symulacja w przedsiębiorstwie. Warszawa: Polskie Wydawnictwo Ekonomiczne.
Google Scholar
Manas, J. (2015). The resource management and capacity planning handbook. USA: McGraw-Hill Companies.
Google Scholar
Pisz, I., Sęk, T., & Zielecki, W. (2013). Logistyka w przedsiębiorstwie. Warszawa: Polskie Wydawnictwo Ekonomiczne.
Google Scholar
Plinta, D. (2015). Modelowanie i symulacja procesów produkcyjnych. Bielsko-Biała: Wydawnictwo Naukowe Akademii Techniczno-Humanistycznej.
Google Scholar
Rainey, L. B., Tolk, A. (2015). Modeling and simulation support for system of systems engineering applications. New Jersey: John Wiley & Sons.
DOI: https://doi.org/10.1002/9781118501757
Google Scholar
Rossetti, M. D. (2016). Simulation modelling and Arena. New Jersey: John Wiley& Sons.
Google Scholar
Sobaszek, Ł., & Gola, A. (2015). Computer-aided production task scheduling. Applied Computer Science, 11(4), 58–69.
Google Scholar
Authors
Sławomir KUKLAskukla@ath.bielsko.pl
Department of Production Engineering, University of Bielsko-Biala,ul. Willowa 2, 43-309 Bielsko-Biała Poland
Authors
Marek SMETANADepartment of Civil Protection, Faculty of Safety Engineering, VŠB – Technical University of Ostrava, Czechia
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