D-Index & Metrics Best Publications
Engineering and Technology
Sweden
2022

D-Index & Metrics 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.

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 70 Citations 17,318 611 World Ranking 500 National Ranking 9

Research.com Recognitions

Awards & Achievements

2022 - Research.com Engineering and Technology in Sweden Leader Award

2014 - Fellow of the American Society of Mechanical Engineers

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Operating system
  • Mechanical engineering

His primary areas of investigation include Manufacturing engineering, Cloud computing, Computer-integrated manufacturing, Cloud manufacturing and Machining. His Manufacturing engineering research incorporates elements of Key, Component and Flexibility. The various areas that Lihui Wang examines in his Cloud computing study include Implementation, Service, Systems engineering and Big data.

His study looks at the relationship between Computer-integrated manufacturing and topics such as Distributed manufacturing, which overlap with Job shop scheduling, Multi-agent system, Systems architecture, Signal processing and Interface. Lihui Wang has researched Cloud manufacturing in several fields, including Technical support, Service management, Advanced manufacturing and Engineering management. The study incorporates disciplines such as Control engineering, Variety, Machine tool and Process in addition to Machining.

His most cited work include:

  • Current status and advancement of cyber-physical systems in manufacturing (453 citations)
  • Collaborative conceptual design—state of the art and future trends (430 citations)
  • Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey (347 citations)

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

His primary areas of study are Manufacturing engineering, Machining, Robot, Cloud computing and Cloud manufacturing. His Manufacturing engineering study typically links adjacent topics like Systems engineering. While the research belongs to areas of Systems engineering, Lihui Wang spends his time largely on the problem of Adaptability, intersecting his research to questions surrounding Industrial engineering.

His study explores the link between Machining and topics such as Process that cross with problems in Plan and Block. The Robot study which covers Control engineering that intersects with Simulation. His work on Service expands to the thematically related Cloud computing.

He most often published in these fields:

  • Manufacturing engineering (25.04%)
  • Machining (14.33%)
  • Robot (14.02%)

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

  • Robot (14.02%)
  • Human–robot interaction (6.46%)
  • Manufacturing engineering (25.04%)

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

His scientific interests lie mostly in Robot, Human–robot interaction, Manufacturing engineering, Artificial intelligence and Cloud manufacturing. The Robot study combines topics in areas such as Control, Control theory and Key. His research on Human–robot interaction also deals with topics like

  • Flexibility that intertwine with fields like Systems architecture,
  • Control engineering which connect with Closed loop and Machining.

His biological study focuses on Smart manufacturing. As part of one scientific family, Lihui Wang deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Computer vision, and often Block, Function and Focus. His Cloud manufacturing study contributes to a more complete understanding of Cloud computing.

Between 2019 and 2021, his most popular works were:

  • Enabling technologies and tools for digital twin (86 citations)
  • Smart manufacturing process and system automation – A critical review of the standards and envisioned scenarios (30 citations)
  • Remote human–robot collaboration: A cyber–physical system application for hazard manufacturing environment (22 citations)

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

  • Artificial intelligence
  • Operating system
  • Mechanical engineering

Robot, Human–robot interaction, Distributed computing, Cloud manufacturing and Big data are his primary areas of study. His work in the fields of Robot, such as Workspace, overlaps with other areas such as Pandemic. His work deals with themes such as Industrial robot, Manufacturing engineering, Human–computer interaction, Collision and Flexibility, which intersect with Human–robot interaction.

Lihui Wang combines subjects such as Service and Plan with his study of Distributed computing. His study on Cloud manufacturing is covered under Cloud computing. His Cloud computing research focuses on Upgrade and how it relates to Manufacturing operations.

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

Current status and advancement of cyber-physical systems in manufacturing

Lihui Wang;Martin Törngren;Mauro Onori.
(2015)

845 Citations

Collaborative conceptual design—state of the art and future trends

Lihui Wang;Weiming Shen;Helen Xie;Joseph Neelamkavil.
(2002)

765 Citations

Cloud-based design and manufacturing

Dazhong Wu;David W. Rosen;Lihui Wang;Dirk Schaefer.
(2015)

604 Citations

Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

Weiming Shen;Lihui Wang;Qi Hao.
(2006)

546 Citations

Reconfigurable manufacturing systems: the state of the art

Z. M. Bi;S. Y. T. Lang;W. Shen;Lihui Wang.
(2008)

498 Citations

Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison

Fei Tao;Qinglin Qi;Lihui Wang;A.Y.C. Nee.
(2019)

436 Citations

Cloud-enabled prognosis for manufacturing

Robert Gao;Lihui Wang;Roberto Teti;David Dornfeld.
(2015)

390 Citations

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

Xun Xu;Lihui Wang;Stephen T. Newman.
(2011)

387 Citations

Enabling technologies and tools for digital twin

Qinglin Qi;Fei Tao;Tianliang Hu;Nabil Anwer.
(2021)

336 Citations

Cloud manufacturing: key characteristics and applications

Lei Ren;Lin Zhang;Lihui Wang;Fei Tao.
(2017)

296 Citations

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