TY - GEN
T1 - Real-time data driven monitoring and optimization method for IoT-based sensible production process
AU - Zhang, Yingfeng
AU - Sun, Shudong
PY - 2013
Y1 - 2013
N2 - Typical challenges that manufacturing enterprises are facing now are compounded by lack of timely, accurate, and consistent information of manufacturing resources of shop floor. Recent developments in wireless sensors, communication and information network technologies have created a new era of the internet of things (IoT). In this paper, an overall architecture of the IoT-enabled manufacturing execution system is presented to provide a new paradigm by extending the techniques of IoT to manufacturing field. Under this architecture, the manufacturing things such as operators, machines, pallets, materials etc. can be embedded with sensors to interact with each other. And the real-time data driven monitoring and optimization for IoT-based sensible production process can be achieved to improve shop-floor productivity and quality, reduce the wastes of manufacturing resources, cut the costs in manufacturing logistics, reduce the risk and improve the efficiency in cross-border customs logistics and online supervision, and improve the responsiveness to production changes.
AB - Typical challenges that manufacturing enterprises are facing now are compounded by lack of timely, accurate, and consistent information of manufacturing resources of shop floor. Recent developments in wireless sensors, communication and information network technologies have created a new era of the internet of things (IoT). In this paper, an overall architecture of the IoT-enabled manufacturing execution system is presented to provide a new paradigm by extending the techniques of IoT to manufacturing field. Under this architecture, the manufacturing things such as operators, machines, pallets, materials etc. can be embedded with sensors to interact with each other. And the real-time data driven monitoring and optimization for IoT-based sensible production process can be achieved to improve shop-floor productivity and quality, reduce the wastes of manufacturing resources, cut the costs in manufacturing logistics, reduce the risk and improve the efficiency in cross-border customs logistics and online supervision, and improve the responsiveness to production changes.
KW - IoT
KW - monitoring
KW - optimization
KW - real-time
KW - sensible manufacturing
UR - http://www.scopus.com/inward/record.url?scp=84881301814&partnerID=8YFLogxK
U2 - 10.1109/ICNSC.2013.6548787
DO - 10.1109/ICNSC.2013.6548787
M3 - 会议稿件
AN - SCOPUS:84881301814
SN - 9781467351980
T3 - 2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
SP - 486
EP - 490
BT - 2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
T2 - 2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013
Y2 - 10 April 2013 through 12 April 2013
ER -