D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 57 Citations 7,575 225 World Ranking 863 National Ranking 3

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Operating system
  • Software

Xun Xu mainly focuses on Manufacturing engineering, Cloud manufacturing, STEP-NC, Nanotechnology and Numerical control. The various areas that Xun Xu examines in his Manufacturing engineering study include Sustainable design, Structure and Manufacturing process. His studies in Cloud manufacturing integrate themes in fields like Computer-integrated manufacturing, Engineering management, Industry 4.0, Scheduling and Process management.

His Process management research includes themes of Resource, Service provider, Cloud computing and Service. His biological study spans a wide range of topics, including Data modeling, Engineering drawing, Machine tool and Interoperability. The study incorporates disciplines such as Porous carbon, Electrochemistry, Honeycomb structure and Chemical stability in addition to Nanotechnology.

His most cited work include:

  • From cloud computing to cloud manufacturing (1145 citations)
  • Intelligent Manufacturing in the Context of Industry 4.0: A Review (680 citations)
  • Sulfur-graphene composite for rechargeable lithium batteries (330 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Manufacturing engineering, Machining, Condensed matter physics, STEP-NC and Superconductivity. His research in Manufacturing engineering intersects with topics in Cloud manufacturing and Process. Xun Xu has researched Cloud manufacturing in several fields, including Manufacturing and Process management.

Xun Xu combines subjects such as Interface and Machine tool with his study of Machining. His research investigates the connection between STEP-NC and topics such as Engineering drawing that intersect with problems in Process. In his research on the topic of Process development execution system, Cloud computing is strongly related with Integrated Computer-Aided Manufacturing.

He most often published in these fields:

  • Manufacturing engineering (14.97%)
  • Machining (13.72%)
  • Condensed matter physics (13.31%)

What were the highlights of his more recent work (between 2019-2021)?

  • Nanotechnology (13.10%)
  • Chemical engineering (6.24%)
  • Industry 4.0 (3.33%)

In recent papers he was focusing on the following fields of study:

His main research concerns Nanotechnology, Chemical engineering, Industry 4.0, Energy transformation and Personalization. His Nanotechnology study combines topics from a wide range of disciplines, such as Electrocatalyst, Absorption, Near-infrared spectroscopy, Material Design and Liquid metal. He has included themes like Anode, Metal, Nonmetal and Sodium in his Chemical engineering study.

His study in Industry 4.0 is interdisciplinary in nature, drawing from both Agile software development and Digital transformation. His work in Reference model covers topics such as Information and Communications Technology which are related to areas like Manufacturing engineering. His Manufacturing engineering research is multidisciplinary, incorporating elements of Cloud manufacturing, Machine tool and Interoperability.

Between 2019 and 2021, his most popular works were:

  • Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues (158 citations)
  • High-performance room-temperature sodium–sulfur battery enabled by electrocatalytic sodium polysulfides full conversion (38 citations)
  • A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment (38 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Operating system
  • Software

His primary areas of study are Chemical engineering, Nanotechnology, Industry 4.0, Water splitting and Transition metal. His Chemical engineering research is multidisciplinary, incorporating perspectives in Nanodot, Sodium, Sodium–sulfur battery and Sulfur utilization. His Nanotechnology research incorporates elements of Photocatalysis, Material structure, Energy transformation, Absorption and Near-infrared spectroscopy.

His work deals with themes such as Digital transformation and Industrial organization, which intersect with Industry 4.0. His Water splitting study integrates concerns from other disciplines, such as Electrocatalyst, Lithium cobalt oxide, Platinum, Hydrogen production and Material Design. His study looks at the relationship between Transition metal and topics such as Selectivity, which overlap with Metal.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

From cloud computing to cloud manufacturing

Xun Xu.
Robotics and Computer-integrated Manufacturing (2012)

1844 Citations

Intelligent Manufacturing in the Context of Industry 4.0: A Review

Ray Y. Zhong;Xun Xu;Eberhard Klotz;Stephen T. Newman.
Engineering (2017)

1159 Citations

Sulfur-graphene composite for rechargeable lithium batteries

Jia-Zhao Wang;Lin Lu;Mohammad Choucair;John A. Stride;John A. Stride.
Journal of Power Sources (2011)

383 Citations

Computer-aided process planning-A critical review of recent developments and future trends

Xun Xu;Lihui Wang;Stephen T. Newman.
International Journal of Computer Integrated Manufacturing (2011)

357 Citations

Making CNC machine tools more open, interoperable and intelligent: a review of the technologies

X. W. Xu;S. T. Newman.
Computers in Industry (2006)

348 Citations

Striving for a total integration of CAD, CAPP, CAM and CNC

X.W Xu;Q He.
Robotics and Computer-integrated Manufacturing (2004)

337 Citations

Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Pai Zheng;Honghui wang;Zhiqian Sang;Runyang Zhong.
Frontiers in Mechanical Engineering (2018)

327 Citations

An interoperable solution for Cloud manufacturing

Xi Vincent Wang;Xun W. Xu.
Robotics and Computer-integrated Manufacturing (2013)

322 Citations

STEP-compliant NC research: the search for intelligent CAD/CAPP/CAM/CNC integration

Xun W. Xu;H Wang;Jian Mao;S T. Newman.
International Journal of Production Research (2005)

269 Citations

Industry 4.0 and Cloud Manufacturing: A Comparative Analysis

Yongkui Liu;Xun Xu.
Journal of Manufacturing Science and Engineering-transactions of The Asme (2017)

268 Citations

Best Scientists Citing Xun Xu

Lihui Wang

Lihui Wang

Royal Institute of Technology

Publications: 101

Shi Xue Dou

Shi Xue Dou

University of Wollongong

Publications: 78

Fei Tao

Fei Tao

Beihang University

Publications: 58

Lin Zhang

Lin Zhang

Beihang University

Publications: 55

Stephen T. Newman

Stephen T. Newman

University of Bath

Publications: 39

Yingfeng Zhang

Yingfeng Zhang

Northwestern Polytechnical University

Publications: 37

Xiangyu Wang

Xiangyu Wang

Curtin University

Publications: 36

George Q. Huang

George Q. Huang

University of Hong Kong

Publications: 34

Dimitris Mourtzis

Dimitris Mourtzis

University of Patras

Publications: 34

Yanwei Ma

Yanwei Ma

Chinese Academy of Sciences

Publications: 32

Ray Y. Zhong

Ray Y. Zhong

University of Hong Kong

Publications: 31

Yi Du

Yi Du

Beihang University

Publications: 27

Chun-Hsien Chen

Chun-Hsien Chen

Nanyang Technological University

Publications: 27

Jung Ho Kim

Jung Ho Kim

University of Wollongong

Publications: 25

Jing Liu

Jing Liu

Chinese Academy of Sciences

Publications: 25

Yan Yu

Yan Yu

University of Science and Technology of China

Publications: 22

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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