CC BY-NC-ND 4.0Berkhan, PatriciaPatriciaBerkhanKärcher, SusannSusannKärcherBauernhansl, ThomasThomasBauernhansl2025-11-062025-11-062024https://publica.fraunhofer.de/handle/publica/498812https://doi.org/10.24406/publica-609810.1016/j.procir.2024.10.25010.24406/publica-60982-s2.0-852130410102-s2.0-85215008026Matrix production systems are modular and flexible production systems that offer advantages in environments characterized by volatility, difficult predictability, and multivariance. Compared to classic production systems, such as production lines or single assembly stations, many degrees of freedom must be considered when planning, controlling and operating matrix production systems. This leads to an increasing level of complexity in the overall system. In particular, the agile and resource-orientated control of material and information flows requires increasing connectivity and intelligence of the objects involved in the value-creation process. In order to cope with this complexity, real-time location data can serve as an enabler for various use cases in matrix production systems. This data can be captured using Real-time Location Systems (RTLS), which allow objects to be tracked in space and time as they move around the production shop floor. This paper systematically derives the benefits of locating data in matrix production systems. Furthermore, the work extends the theoretical considerations by categorizing over 80 real-world use cases into the established framework.entruecomplexitydata acquisitionMatrix manufacturingjournal article