Izvorni znanstveni članak
Automating the Simulation of SME Processes through a Discrete Event Parametric Model
Francesco Aggogeri
; Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy
Rodolfo Faglia
; Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy
Marco Mazzola
; Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy
Angelo Merlo
; Centro Studi Industriali, Milan, Italy
Sažetak
At the factory level, the manufacturing system can be described as a group of processes governed by complex weaves of engineering strategies and technologies. Decision- making processes involve a lot of information, driven by managerial strategies, technological implications and layout constraints. Many factors affect decisions, and their combination must be carefully managed to determine the best solutions to optimize performances. In this way, advanced simulation tools could support the decisional process of many SMEs. The accessibility of these tools is limited by knowledge, cost, data availability and development time. These tools should be used to support strategic decisions rather than specific situations. In this paper, a novel approach is proposed that aims to facilitate the simulation of manufacturing processes by fast modelling and evaluation. The idea is to realize a model that is able to be automatically adapted to the user’s specific needs. The model must be characterized by a high degree of flexibility, configurability and adaptability in order to automatically simulate multiple/heterogeneous industrial scenarios. In this way, even a SME can easily access a complex tool, perform thorough analyses and be supported in taking strategic decisions. The parametric DES model is part of a greater software platform developed during COPERNICO EU funded project.
Ključne riječi
discrete event simulation; manufacturing system parametrization; automatic modelling; SMEs
Hrčak ID:
142330
URI
Datum izdavanja:
1.1.2015.
Posjeta: 1.196 *