EXCELL foresees the collaboration of academics from 4 European countries (Hungary, Germany, UK, Belgium) in the multidisciplinary topic of Big Data Applications for Cyber-Physical Systems in Production and Logistics Networks. The main scientific and innovation focus of EXCELL was devised both from world-wide tendencies and local requirements (expressed by the regional smart specialization strategies-S3), departing from the present competences of the cooperating partners (SZTAKI, Fraunhofer-FIT, Aston and KU Leuven).
One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet.
Typically, logistics networks generate billions of new data items on a monthly basis that can be used to help predict potential customer behaviour. Lorries transport thousands of pallets on hundreds of trailers for millions of customers scattered across hundreds of thousands of postcodes. Customers are continuously placing orders with information being generated about what they want to transport, where it will be coming from, where it will be going and what their service requirements are.
Context-aware systems in intelligent environments digest large amounts of data and personal information to gain situational awareness as a way to assist individuals with their daily activities, enhance their experiences and adapt to their needs and intention, whenever and wherever they are. Large amounts of data drive these environments, motivating the adoption of big data and cloud technologies. A similar digital transformation is taking place in the Factory of the Future and Industry 4.0, two paradigms on creating smart products through smart processes and procedures.
Typical learning factories are characterized by selective simplification or scaling-down of complex and large-scale production processes, while also safely containing risks in the case of process failures inherent to experimental and didactic activities. The variety of aspects preserved by these scaled-down environments allow different approaches to be taken in research and education. The paper compares two facilities, at TU Wien and at MTA SZTAKI in Budapest, respectively, and highlights differences in their modes of operation, the resulting variations of course-based vs.