TY - GEN
T1 - Towards the Adoption of Cyber-Physical Systems of Systems Paradigm in Smart Manufacturing Environments
AU - Ferrer, Borja Ramis
AU - Mohammed, Wael M.
AU - Martinez Lastra, Jose L.
AU - Villalonga, Alberto
AU - Beruvides, Gerardo
AU - Castano, Fernando
AU - Haber, Rodolfo E.
PY - 2018/9/24
Y1 - 2018/9/24
N2 - Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.
AB - Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.
KW - Cyber-Physical Systems
KW - Cyber-Physical Systems of Systems
KW - Industry 4.0
KW - Smart Manufacturing
KW - System of Systems
U2 - 10.1109/INDIN.2018.8472061
DO - 10.1109/INDIN.2018.8472061
M3 - Conference contribution
AN - SCOPUS:85055511921
T3 - IEEE International Conference on Industrial Informatics
SP - 792
EP - 799
BT - Proceedings - IEEE 16th International Conference on Industrial Informatics, INDIN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Industrial Informatics
Y2 - 18 July 2018 through 20 July 2018
ER -