Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. D. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds. DEVELOPMENT OF AN OPEN-SOURCE DISCRETE EVENT SIMULATION CLOUD ENABLED PLATFORM Cathal Heavey Sebastian Robin Georgios Dagkakis Marco Mariani Panagiotis Barlas Jerome Perrin Ioannis Papagiannopoulos Enterprise Research Center Nexedi University of Limerick 270 Bd Clémenceau Limerick, IRELAND Lille, 59700, FRANCE ABSTRACT Discrete Event Simulation (DES) is traditionally one of the most popular operation research techniques. Nevertheless, organizations, and especially Small and Medium Enterprises (SMEs), are often reluctant to invest in DES projects. The lack of flexibility, high cost of developing and maintaining DES models, the high volume of data that these need in order to provide valid results and the difficulty in embedding them in real time problems, are some of the problems that deter organizations from adopting DES based solutions. DREAM is an FP7 project with the aim to develop an Open Source (OS) platform, which will confront the above issues. The DREAM architecture consists of three cloud enabled modules, a semantic free Simulation Engine (SE), a Knowledge Extraction (KE) tool and a customizable web-based Graphical User Interface (GUI). We present how these components cooperate and how an advanced user can manipulate them in order to develop tailored solutions for companies. 1 INTRODUCTION Simulation is a powerful tool that provides the ability to allow practitioners to design and develop new systems, run experiments to observe performance and evaluate the outcome of alternative scenarios (Shannon 1998). Simulation can be used to study and compare alternative designs or to troubleshoot existing systems (Fowler 2004). Also, it has been demonstrated as technology for reducing costs and improving quality (Brown and Sturrock 2009). Given the fact that manufacturing systems, processes, and data are growing and becoming more complex (Ramirez and Nembhard 2004), product design, manufacturing engineering, and production management decisions involve the consideration of many interdependent factors and variables. These often complex, interdependent factors and variables are too many for the human mind to deal with at one time (Heilala et al. 2010). Thus, simulation is becoming a preferred modelling approach for a big variety of manufacturing systems, because due to its flexibility it does not require strict simplifying assumptions and the models’ detail level can be adjusted according to the analysis purposes. By reducing the programming effort and the time needed to develop a simulation model, Commercial-off-the-self (COTS) DES software packages have contributed significantly to the spread of DES in the academic and industrial community (Taylor et al. 2009). COTS software packages asset is that they offer the user tools for modelling, debugging and experimentation (Pidd and Cavalho 2006). The programming effort and the required time are considerably reduced as already developed DES objects can be manipulated through a user friendly GUI. The lack of flexibility to embed simulation into Decision Support Systems (DSS) due to the lack of modularity of COTS DES tools and to a lesser degree the high