Contribute to the development of industry-relevant research topics, to comply with customer and legal requirements
Actions for Excellence in Smart Cyber-Physical Systems applications through the exploitation of Big Data methodologies and techniques
Environmental dynamism in enterprises, high degree of fault-tolerance and unconditional system responsivity
Journal publication (2015)
Ilie-Zudor, E.; Ekárt, A.; Kemény, Zs.; Buckingham, C.D.; Welch, P.G.; Monostori, L.: Advanced predictive-analysis-based decision support for collaborative logistics networks, Supply Chain Management: An International Journal, vol. 20, no. 4, pp. 369-388, 2015, (ISSN: 1359-8546) (DOI: 10.1108/SCM-10-2014-0323)
Download : http://www.emeraldinsight.com/doi/full/10.1108/SCM-10-2014-0323
Much of the resilience and flexibility of production networks lies in the transparency of processes that allows timely perception of actual process states and adequate decisions or intervention at the proper point of the production system.
Business processes in production and logistics need to be monitored in order to comply with official regulations, to schedule and plan the production or transport route, to ensure quality and find errors, but also to optimize the process itself. Often this monitoring needs to be done in real-time, e.g.
The first version of the EXCELL Flipboard magazine is ready and is centred on a set of topics on Industry 4.0 and EXCELL project related topics covering Industry 4.0, logistics, manufacturing, Big Data, security, the Internet of Things and Cyber Physical Systems.
The magazine covers both scientific articles and technological news from around the world. The first version is now available, with continuous updates throughout the whole project period.
The quickest way to get an overview of the EXCELL Project activities is to glance through our brochure, which is organized into different sections: consortium, contacts, strategic objectives, main actions and project facts.
Click here to download the EXCELL Leaflet in PDF format.
Journal publication (2016, January)
Preuveneers, D.; Berbers, Y.; Joosen, W.: SAMURAI: A batch and streaming context architecture for large-scale intelligent applications and environments, Journal of Ambient Intelligence and Smart Environments, vol. 8, no. 1, pp. 63-78, 2016, (ISSN: 1876-1364) (DOI: 10.3233/AIS-150357)
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 691829.
Institute for Computer Science and Control, Hungarian Academy of Sciences
Fraunhofer-Gesellschaft zur Förderung der Angewandten Forschung e.V. (FhG) - Institute for Applied Information Technology FIT
Aston University
KU Leuven
