TY - JOUR
T1 - A Cloud-Monitoring Service for Manufacturing Environments
AU - Toro, Ricardo
AU - Correa, Jorge E.
AU - Ferreira, Placid M.
N1 - Funding Information:
The authors acknowledge funding from the Digital Manufacturing and Design Innovation Institute (DMDII) at Chicago, Illinois. They also acknowledge assistance from Professor N. Aluru, S. G. Kapoor, and K. Nahrstedt of Illinois, and Professor K. Ehmannand and J. Cao of Northwestern. Glennys Mensing assisted with the preparation and proofing of the manuscript.
Publisher Copyright:
© 2018 Elsevier B.V. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Cloud application services are being implemented in all areas of engineering. Manufacturing engineering could benefit from the implementation of cloud-technologies that lead to an improved production and product-cost reduction. This paper proposes the development of a flexible, scalable, versatile, highly affordable and open-source cloud-platform for implementing sensor networks in support of advanced manufacturing. In particular, a two-layer-network architecture is present and explained through real applications in the area of advanced manufacturing. Two case studies present the collection, storage, and sharing of data over the network. Results show the successful integration of communication protocols across the cyber physical system as well as the reliability of the platform and its ability to log data. This architecture has the potential of generating great impact on the new area of digital manufacturing.
AB - Cloud application services are being implemented in all areas of engineering. Manufacturing engineering could benefit from the implementation of cloud-technologies that lead to an improved production and product-cost reduction. This paper proposes the development of a flexible, scalable, versatile, highly affordable and open-source cloud-platform for implementing sensor networks in support of advanced manufacturing. In particular, a two-layer-network architecture is present and explained through real applications in the area of advanced manufacturing. Two case studies present the collection, storage, and sharing of data over the network. Results show the successful integration of communication protocols across the cyber physical system as well as the reliability of the platform and its ability to log data. This architecture has the potential of generating great impact on the new area of digital manufacturing.
KW - Cloud Manufacturing
KW - Cyber Physical Systems (CPS)
KW - Sensing Networks
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U2 - 10.1016/j.promfg.2018.07.128
DO - 10.1016/j.promfg.2018.07.128
M3 - Conference article
AN - SCOPUS:85052873773
SN - 2351-9789
VL - 26
SP - 1330
EP - 1339
JO - Procedia Manufacturing
JF - Procedia Manufacturing
T2 - 46th SME North American Manufacturing Research Conference, NAMRC 2018
Y2 - 18 June 2018 through 22 June 2018
ER -