Discrete event simulation is becoming increasingly important in the planning and operation of complex manufacturing systems. A major problem with today's approach to manufacturing simulation studies is the collection and processing of data from heterogeneous sources, because the data is often of poor quality and does not contain all the necessary information for a simulation. This work introduces a framework that uses a real-time indoor localization systems (RTILS) as a central main data harmonizer, that is designed to feed production data into a manufacturing simulation from a single source of truth. It is shown, based on different data quality dimensions, how this contributes to a better overall data quality in manufacturing simulation. Furthermore, a detailed overview on which simulation inputs can be derived from the RTILS data is given.
Mieth, C., Meyer, A., & Henke, M. (2019). Framework for the usage of data from real-time indoor localization systems to derive inputs for manufacturing simulation. In Procedia CIRP (Vol. 81, pp. 868–873). Elsevier B.V. https://doi.org/10.1016/j.procir.2019.03.216