R
Ray Y. Zhong
Researcher at University of Hong Kong
Publications - 194
Citations - 8990
Ray Y. Zhong is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Computer science & Radio-frequency identification. The author has an hindex of 35, co-authored 166 publications receiving 5414 citations. Previous affiliations of Ray Y. Zhong include Shenzhen University & Harbin Institute of Technology.
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Intelligent Manufacturing in the Context of Industry 4.0: A Review
TL;DR: This paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing and describes worldwide movements in intelligent manufacturing.
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RFID-enabled real-time manufacturing execution system for mass-customization production
TL;DR: In this article, an RFID-enabled real-time manufacturing execution system (RT-MES) is proposed to track and trace manufacturing objects and collect realtime production data.
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Big Data for supply chain management in the service and manufacturing sectors
TL;DR: This paper investigates representative Big Data applications from typical services like finance & economics, healthcare, Supply Chain Management (SCM), and manufacturing sector and discusses current movements on the Big Data for SCM in service and manufacturing world-wide including North America, Europe, and Asia Pacific region.
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A big data approach for logistics trajectory discovery from RFID-enabled production data
TL;DR: A holistic Big Data approach to excavate frequent trajectory from massive RFID-enabled shopfloor logistics data with several innovations highlighted is proposed, which are able to guide end-users to carry out associated decisions.
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Big Data Analytics for Physical Internet-based intelligent manufacturing shop floors
TL;DR: This study introduces a Big Data Analytics for RFID logistics data by defining different behaviours of SMOs and generates managerial implications, which are useful for various users to make logistics decisions under PI-enabled intelligent shop floors.