We envision future factories being designed by compositions of smart connected components, with a large part of the intelligence residing in the Cloud. This will enable increased flexibility and evolvability of manufacturing, as well as pave the way for new business models where production facilities can be accessible as cloud services.
Moving a large part of the production complexity to the Cloud has benefits in cost, energy efficiency, sharing of resources, increased flexibility, adaptability and evolvability, and provide in general a strong basis for innovation. There are however associated challenges, including providing efficient and predictable (safe and secure) computation and communication, and coping with the huge amounts of data needed to provide the envisioned intelligence. These challenges are particularly demanding in safety-relevant systems, such as transportation and manufacturing.
FiC will provide generic solutions for Future factories in the Cloud in the form of an integrated set of techniques and generic tools for future smart products and production systems, including architectural templates for cloud based production; algorithms and tools for safe and secure communication and computation, specifically handling big-data; and techniques for efficient and predictable sharing of computation and communication resources. The research will be based on real usage scenarios and results demonstrated and evaluated in industrial contexts.
|First Name||Last Name||Title|
Modelling and Control of Big Data Frameworks (Jul 2017) Alberto Leva , Alessandro Papadopoulos 20th World Congress of the International Federation of Automatic Control (IFAC 17)
Designing End-to-end Resource Reservations in Predictable Distributed Embedded Systems (Jun 2017) Mohammad Ashjaei, Nima Khalilzad, Saad Mubeen, Moris Behnam, Ingo Sander , Luis Almeida, Thomas Nolte Real-Time Systems (RTSJ)
Agent-centred Approach for Assuring Ethics in Dependable Service Systems (Jun 2017) Irfan Sljivo, Elena Lisova, Sara Afshar 13th IEEE World Congress on Services (SERVICES 2017)
Performance modeling of stream joins (Jun 2017) Vincenzo Gulisano , Alessandro Papadopoulos, Yiannis Nikolakopoulos , Marina Papatriantafilou , Philippas Tsigas 11th ACM International Conference on Distributed and Event-Based Systems (DEBS 17)
Comparing Model-Based Predictive Approaches to Self-Adaptation: CobRA and PLA (May 2017) Gabriel Moreno , Alessandro Papadopoulos, Konstantinos Angelopoulos , Javier Camara Moreno , Bradley Schmerl 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 17)
Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (May 2017) Martina Maggio , Alessandro Papadopoulos, Antonio Filieri , Henry Hoffmann 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 17)