In today’s manufacturing, there is an increase in the need for fast and accurate operational production planning and scheduling. Usually, scheduling is performed several times each day, and new information,which is retrieved from the manufacturing facilities, has to be taken into consideration. Scheduling is normally performed with the aid of tools available on the market today. However, Discrete Event Simulation (DES) can address the facility’s dynamic behavior with the help of data from the facility, data including both historical and snapshot data with information about how the system currently is performing. This data needs to be structured in such a way that it can be used in the simulation model. This paper presents an approach for
this problem and examples of solutions. The main focus of the research and the paper is on the methodology and system architecture