SIMULATIONS-OVERVIEW OF HYBRID SIMULATION MODELS
MSc Bojan Jovanovski * Ss. Cyril and Methodi University, Faculty of Mecahical Engineering, Skopje, Macedonia Dr Robert Minovski Ss. Cyril and Methodi University, Faculty of Mecahical Engineering, Skopje, Macedonia Dr Siegfried Voessner Institute of Engineering and Business Informatics, TU Graz, Austria Dr Gerald Lichtenegger Institute of Engineering and Business Informatics, TU Graz, Austria doi:10.5937/jaes10-2512
A methodology for Integrating and Synchronizing the System Dynamics and Discrete Event Simulation Paradigms
With the adoption of integration and system perspectives in managing the manufacturing systems and the pressure imposed by the increased competition and rapidly changing business environment, the need has arisen for new approaches for simulating the manufacturing enterprise. We have proposed SDDES; a hybrid System Dynamics Discrete Event Simulation approach to simulating the integrated manufacturing enterprise. SDDES offers comprehensive simulation models that encompass all management levels and recognize the differences between them in terms of scope and frequency of decision making as well as the levels of details preferred and used at each level. SDDES maintains the integrity of the two simulation paradigms and can use existing/legacy simulation models without requiring learning new simulation skills. In this paper we describe the modular structure of SDDES, our method to synchronize and coordinate SD and DES, and the functional model of the SDDES controller, which manages the integration of the two simulation methodologies.
On developing system dynamics model for business process simulation
Business operations can be formally described in business process models that capture activities, information, and flow embedded in business operation. System dynamics modeling is a set of conceptual tools that enable business process designers to build computer simulations of complex business process behaviors. System dynamics models provide accurate description of system behavior along the time dimension. It gives a convenient tool to conduct what if analysis though dynamics points of view. However, to develop system dynamics models requires keen understanding of the "physics" of the target business operations, business organizations, and financial structures and so on. This paper is aimed to provide heuristics and guidelines of developing system dynamics models based on given business process models along with associated reference contexts. An example, from supply chain management domain, of using business process models to derive system dynamics models is given in the paper