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Sensors, Vol. 18, Pages 1961: A Fog Computing Based Cyber-Physical System for the Automation of Pipe-Related Tasks in the Industry 4.0 Shipyard

Sensors, Vol. 18, Pages 1961: A Fog Computing Based Cyber-Physical System for the Automation of Pipe-Related Tasks in the Industry 4.0 Shipyard

Sensors doi: 10.3390/s18061961

Authors: Tiago M. Fernández-Caramés Paula Fraga-Lamas Manuel Suárez-Albela Manuel A. Díaz-Bouza

Pipes are one of the key elements in the construction of ships, which usually contain between 15,000 and 40,000 of them. This huge number, as well as the variety of processes that may be performed on a pipe, require rigorous identification, quality assessment and traceability. Traditionally, such tasks have been carried out by using manual procedures and following documentation on paper, which slows down the production processes and reduces the output of a pipe workshop. This article presents a system that allows for identifying and tracking the pipes of a ship through their construction cycle. For such a purpose, a fog computing architecture is proposed to extend cloud computing to the edge of the shipyard network. The system has been developed jointly by Navantia, one of the largest shipbuilders in the world, and the University of A Coruña (Spain), through a project that makes use of some of the latest Industry 4.0 technologies. Specifically, a Cyber-Physical System (CPS) is described, which uses active Radio Frequency Identification (RFID) tags to track pipes and detect relevant events. Furthermore, the CPS has been integrated and tested in conjunction with Siemens’ Manufacturing Execution System (MES) (Simatic IT). The experiments performed on the CPS show that, in the selected real-world scenarios, fog gateways respond faster than the tested cloud server, being such gateways are also able to process successfully more samples under high-load situations. In addition, under regular loads, fog gateways react between five and 481 times faster than the alternative cloud approach.

Authors:   Fernández-Caramés, Tiago M.; Fraga-Lamas, Paula ; Suárez-Albela, Manuel ; Díaz-Bouza, Manuel A.
Journal:   Sensors
Volume:   18
edition:   6
Year:   2018
Pages:   1961
DOI:   10.3390/s18061961
Publication date:   17-Jun-2018
Facts, background information, dossiers
  • Spain
  • samples
  • production
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