What is he best known for?
The fields of study he is best known for:
- Operating system
- Polymer
- Artificial intelligence
Yingfeng Zhang mainly focuses on Radio-frequency identification, Manufacturing engineering, Systems engineering, Traceability and Embedded system.
His Radio-frequency identification research is multidisciplinary, incorporating elements of Wireless, Engineering management, Advanced manufacturing and Synchronization.
Yingfeng Zhang focuses mostly in the field of Advanced manufacturing, narrowing it down to matters related to Work in process and, in some cases, Manufacturing execution system.
His Manufacturing engineering research integrates issues from Physical Internet, Process and Big data.
His work in Systems engineering addresses subjects such as Production logistics, which are connected to disciplines such as Cloud computing.
Yingfeng Zhang combines subjects such as Scheduling and Service with his study of Computer-integrated manufacturing.
His most cited work include:
- A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products (205 citations)
- RFID-based wireless manufacturing for real-time management of job shop WIP inventories. (194 citations)
- RFID-based wireless manufacturing for walking-worker assembly islands with fixed-position layouts (188 citations)
What are the main themes of his work throughout his whole career to date?
Yingfeng Zhang mainly investigates Manufacturing engineering, Energy consumption, Scheduling, Industrial engineering and Distributed computing.
In Manufacturing engineering, he works on issues like Service, which are connected to Software engineering.
His research in Energy consumption focuses on subjects like Manufacturing, which are connected to Big data.
His Scheduling study combines topics in areas such as Production planning, Dynamic priority scheduling and Job shop scheduling.
His work deals with themes such as Quality and Key, which intersect with Industrial engineering.
In his study, Service provider is strongly linked to Cloud computing, which falls under the umbrella field of Distributed computing.
He most often published in these fields:
- Manufacturing engineering (22.93%)
- Energy consumption (19.75%)
- Scheduling (16.56%)
What were the highlights of his more recent work (between 2018-2021)?
- Energy consumption (19.75%)
- Manufacturing engineering (22.93%)
- Cloud computing (11.46%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Energy consumption, Manufacturing engineering, Cloud computing, Product lifecycle and Distributed computing.
His Energy consumption research incorporates themes from Industrial engineering, Distribution center, Fuel efficiency, Manufacturing and Cyber-physical system.
His Industrial engineering research incorporates elements of Quality, Production planning and Key.
In his articles, he combines various disciplines, including Manufacturing engineering and Cleaner production.
Service, Big data and Process management are fields of study that intersect with his Product lifecycle research.
His studies deal with areas such as Cloud manufacturing, Scheduling, Dynamic priority scheduling and Augmented Lagrangian method as well as Distributed computing.
Between 2018 and 2021, his most popular works were:
- A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions (128 citations)
- Energy-cyber-physical system enabled management for energy-intensive manufacturing industries (35 citations)
- Multiagent and Bargaining-Game-Based Real-Time Scheduling for Internet of Things-Enabled Flexible Job Shop (35 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Polymer
His primary scientific interests are in Energy consumption, Distributed computing, Cloud computing, Cyber-physical system and Utilization rate.
His work carried out in the field of Energy consumption brings together such families of science as Quality, Virtualization, Information technology and Communications system.
His studies in Distributed computing integrate themes in fields like Scheduling, Dynamic priority scheduling and Implementation.
His Cloud computing study incorporates themes from Service provider and Engineering management.
His study in Cyber-physical system is interdisciplinary in nature, drawing from both Smart environment, Industrial engineering, Performance indicator, Traceability and Key.
The Cloud manufacturing study combines topics in areas such as Manufacturing engineering, Task and Augmented Lagrangian method.
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