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https://open.uns.ac.rs/handle/123456789/14207
Nаziv: | Design methodology for discrete event simulation solutions in manufacturing environment | Аutоri: | Pavlović, M. Arsovski S. Arsovski Z. Mirović, Z. Lazić, M. |
Dаtum izdаvаnjа: | 1-апр-2011 | Čаsоpis: | Strojarstvo | Sažetak: | The paper considers Discrete Event Simulation design methodology. Primary objective is proposal of comprehensive, scientifically established design methodology to structure, guide, and improve manufacturing processes modeling efforts. Proposed approach replicate structure and behavior of original system at desired level of abstraction, incorporates specific academic knowledge in simulation solution and results in object oriented application architecture completely consistent with production planning and scheduling ontology. The paper begins pointing out importance of modeling and equality between knowledge and models from viewpoint of modern cybernetic science and referenced cybernetics theory relocates in manufacturing systems and discrete event simulation domain. Paper then proceeds to discuss a structure and main steps of proposed methodology with a more detailed discussion of simulation based production planning and scheduling. Finally, an example of successfully designed simulation solution is given. Proposed approach gives verbal and mathematical problem description, builds ontology of problem domain, uses Extended Petri Nets, event graphs and activity cycle diagrams as modeling tools, in order to obtain faithful model which easily can be replicated in object oriented class and object hierarchy. Methodology highlights inevitability of knowledge transfer between business processes, software development and academic research experts. Integration and overlapping of mentioned fields of knowledge result in object oriented application architecture fully consistent with ontology derived from conceptual phase of design methodology. Proposed methodology enables convergence of comprehensive but static MIS knowledge in dynamic simulation model in order to fully utilize its prediction power for effective integration of strategic and tactical decision making. | URI: | https://open.uns.ac.rs/handle/123456789/14207 | ISSN: | 05621887 |
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