What is he best known for?
The fields of study he is best known for:
- Operating system
- Software
- Information technology
His primary areas of investigation include Radio-frequency identification, Scheduling, Big data, Real-time computing and Cloud manufacturing.
The study incorporates disciplines such as Prefabrication, Systems engineering, Traceability, Interoperability and Testbed in addition to Radio-frequency identification.
His Scheduling study incorporates themes from Advanced planning and scheduling, Production planning and Web service.
His work deals with themes such as Supply chain management and Data science, which intersect with Big data.
His Data science research is multidisciplinary, incorporating elements of Integrated logistics support, Smart manufacturing and Data warehouse, Data mining.
His biological study spans a wide range of topics, including Manufacturing engineering, Computer-integrated manufacturing and Genetic algorithm scheduling.
His most cited work include:
- Intelligent Manufacturing in the Context of Industry 4.0: A Review (680 citations)
- RFID-enabled real-time manufacturing execution system for mass-customization production (318 citations)
- A big data approach for logistics trajectory discovery from RFID-enabled production data (266 citations)
What are the main themes of his work throughout his whole career to date?
Ray Y. Zhong focuses on Radio-frequency identification, Cloud computing, Manufacturing engineering, Big data and Supply chain management.
His work carried out in the field of Radio-frequency identification brings together such families of science as Scheduling, Real-time computing, Automated guided vehicle and Traceability.
His Cloud computing research includes themes of Cyber-physical system, Systems engineering and Implementation.
His Manufacturing execution system study, which is part of a larger body of work in Manufacturing engineering, is frequently linked to Work, bridging the gap between disciplines.
His work focuses on many connections between Big data and other disciplines, such as Data science, that overlap with his field of interest in Smart manufacturing.
His Supply chain management study combines topics in areas such as Engineering management and Operations management.
He most often published in these fields:
- Radio-frequency identification (22.88%)
- Cloud computing (16.34%)
- Manufacturing engineering (13.07%)
What were the highlights of his more recent work (between 2019-2021)?
- Manufacturing engineering (13.07%)
- Cloud computing (16.34%)
- Supply chain (9.80%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Manufacturing engineering, Cloud computing, Supply chain, Cyber-physical system and Data science.
His study in the field of Cloud manufacturing is also linked to topics like Future studies.
His Cloud manufacturing study integrates concerns from other disciplines, such as Manufacturing, Advanced manufacturing and Combinatorial auction.
The concepts of his Cyber-physical system study are interwoven with issues in Virtualization, Industrial engineering, Engineering management and Traceability.
His Data science research incorporates elements of Data analysis and Big data.
His Data-driven research is multidisciplinary, relying on both Quality and Radio-frequency identification.
Between 2019 and 2021, his most popular works were:
- System architecture for blockchain based transparency of supply chain social sustainability (40 citations)
- Blockchain-based life cycle assessment: An implementation framework and system architecture (30 citations)
- A proactive material handling method for CPS enabled shop-floor (28 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Software
- Information technology
The scientist’s investigation covers issues in Process management, Service, Big data, Service provider and Cyber-physical system.
The Service study combines topics in areas such as Agile software development, Digital transformation, Industry 4.0 and Systems engineering, Reference model.
His study looks at the relationship between Big data and fields such as Systems architecture, as well as how they intersect with chemical problems.
His research integrates issues of Virtualization, Information technology and Engineering management in his study of Cyber-physical system.
The concepts of his Quality study are interwoven with issues in Radio-frequency identification and Data-driven.
Ray Y. Zhong works mostly in the field of Radio-frequency identification, limiting it down to topics relating to Process and, in certain cases, Data science, as a part of the same area of interest.
This overview was generated by a machine learning system which analysed the scientist’s
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