Dunbing Tang

4.6k total citations · 2 hit papers
142 papers, 3.3k citations indexed

About

Dunbing Tang is a scholar working on Industrial and Manufacturing Engineering, Management of Technology and Innovation and Mechanical Engineering. According to data from OpenAlex, Dunbing Tang has authored 142 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Industrial and Manufacturing Engineering, 45 papers in Management of Technology and Innovation and 43 papers in Mechanical Engineering. Recurrent topics in Dunbing Tang's work include Manufacturing Process and Optimization (50 papers), Scheduling and Optimization Algorithms (43 papers) and Product Development and Customization (40 papers). Dunbing Tang is often cited by papers focused on Manufacturing Process and Optimization (50 papers), Scheduling and Optimization Algorithms (43 papers) and Product Development and Customization (40 papers). Dunbing Tang collaborates with scholars based in China, Spain and United Kingdom. Dunbing Tang's co-authors include Adriana Giret, Miguel Á. Salido, Haihua Zhu, Min Dai, Weidong Li, Zequn Zhang, Tong Zhou, Min Dai, Yong Gui and Inayat Ullah and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Dunbing Tang

133 papers receiving 3.2k citations

Hit Papers

Dynamic job shop scheduling based on deep reinforcement l... 2022 2026 2023 2024 2022 2023 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Dynamic job shop scheduling based on deep reinforcement learning for multi-agent manufacturing systems
    2022 151 citations Yi Zhang, Haihua Zhu et al. Robotics and Computer-Integrated Manufacturing profile →
  2. Dynamic scheduling for flexible job shop using a deep reinforcement learning approach
    2023 104 citations Yong Gui, Dunbing Tang et al. Computers & Industrial Engineering profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dunbing Tang China 28 2.3k 647 565 403 245 142 3.3k
Deyi Xue Canada 33 1.4k 0.6× 1.0k 1.6× 1.1k 2.0× 397 1.0× 229 0.9× 139 3.2k
József Váncza Hungary 27 2.1k 0.9× 539 0.8× 380 0.7× 433 1.1× 188 0.8× 109 3.3k
Damien Trentesaux France 36 2.8k 1.2× 291 0.4× 178 0.3× 487 1.2× 229 0.9× 154 3.9k
Sudarsan Rachuri United States 24 1.3k 0.6× 434 0.7× 511 0.9× 132 0.3× 305 1.2× 89 1.9k
Jaime A. Camelio United States 27 1.5k 0.7× 229 0.4× 714 1.3× 303 0.8× 111 0.5× 85 2.5k
Luca Fumagalli Italy 25 2.4k 1.0× 223 0.3× 230 0.4× 253 0.6× 121 0.5× 112 3.7k
Nikolaos Papakostas Greece 27 1.6k 0.7× 490 0.8× 320 0.6× 316 0.8× 101 0.4× 86 2.5k
Guanghui Zhou China 30 1.6k 0.7× 141 0.2× 678 1.2× 186 0.5× 108 0.4× 106 2.8k
Chaoyong Zhang China 41 3.6k 1.5× 113 0.2× 450 0.8× 513 1.3× 533 2.2× 155 4.5k
Ying Cheng China 28 2.9k 1.3× 842 1.3× 248 0.4× 238 0.6× 283 1.2× 89 4.4k

Countries citing papers authored by Dunbing Tang

Since Specialization
Citations

This map shows the geographic impact of Dunbing Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dunbing Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dunbing Tang more than expected).

Fields of papers citing papers by Dunbing Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dunbing Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dunbing Tang. The network helps show where Dunbing Tang may publish in the future.

Co-authorship network of co-authors of Dunbing Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Dunbing Tang. A scholar is included among the top collaborators of Dunbing Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dunbing Tang. Dunbing Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Changchun, et al.. (2025). Enhancing machine tool predictive maintenance: A dual-model approach integrating improved deep autoencoders and graph attention network. Computers & Industrial Engineering. 203. 111048–111048. 2 indexed citations
2.
3.
Li, Dongdong, Dunbing Tang, Changchun Liu, Zequn Zhang, & Lei Wang. (2025). Research on dynamic obstacle avoidance for industrial AGVs using decay model-based multi-objective Q-learning. Knowledge-Based Systems. 333. 115000–115000.
4.
5.
Gui, Yong, Zequn Zhang, Dunbing Tang, Haihua Zhu, & Yi Zhang. (2024). Collaborative dynamic scheduling in a self-organizing manufacturing system using multi-agent reinforcement learning. Advanced Engineering Informatics. 62. 102646–102646. 24 indexed citations
6.
Zhang, Yi, Zequn Zhang, Yuqian Lu, Haihua Zhu, & Dunbing Tang. (2023). Dynamic decision-making for knowledge-enabled distributed resource configuration in cloud manufacturing considering stochastic order arrival. Robotics and Computer-Integrated Manufacturing. 87. 102712–102712. 8 indexed citations
7.
Liu, Changchun, et al.. (2023). A mixed perception-based human-robot collaborative maintenance approach driven by augmented reality and online deep reinforcement learning. Robotics and Computer-Integrated Manufacturing. 83. 102568–102568. 25 indexed citations
8.
Zhang, Zequn, et al.. (2023). Enabling collaborative assembly between humans and robots using a digital twin system. Robotics and Computer-Integrated Manufacturing. 86. 102691–102691. 42 indexed citations
9.
Nie, Qingwei, et al.. (2023). A multi-agent and cloud-edge orchestration framework of digital twin for distributed production control. Robotics and Computer-Integrated Manufacturing. 82. 102543–102543. 45 indexed citations
10.
Liu, Changchun, Haihua Zhu, Dunbing Tang, et al.. (2022). A transfer learning CNN-LSTM network-based production progress prediction approach in IIoT-enabled manufacturing. International Journal of Production Research. 61(12). 4045–4068. 23 indexed citations
11.
Zhang, Zequn, Dunbing Tang, Haihua Zhu, Liping Wang, & Qingwei Nie. (2022). A dynamic dispatching control system for processing workshop based on multi-agent and value matching. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 237(1-2). 144–153. 6 indexed citations
12.
Liu, Changchun, Haihua Zhu, Dunbing Tang, et al.. (2022). Probing an intelligent predictive maintenance approach with deep learning and augmented reality for machine tools in IoT-enabled manufacturing. Robotics and Computer-Integrated Manufacturing. 77. 102357–102357. 82 indexed citations
13.
Zhang, Zequn, et al.. (2021). Research on Workers Integration in Smart Factories With Multi-Agent Control System. IEEE Access. 9. 132508–132521. 1 indexed citations
14.
Zhang, Yi, et al.. (2021). A flexible configuration method of distributed manufacturing resources in the context of social manufacturing. Computers in Industry. 132. 103511–103511. 28 indexed citations
15.
Nie, Qingwei, et al.. (2021). A multi-agent and internet of things framework of digital twin for optimized manufacturing control. International Journal of Computer Integrated Manufacturing. 35(10-11). 1205–1226. 16 indexed citations
16.
Liu, Changchun, Dunbing Tang, Haihua Zhu, & Qingwei Nie. (2021). A Novel Predictive Maintenance Method Based on Deep Adversarial Learning in the Intelligent Manufacturing System. IEEE Access. 9. 49557–49575. 48 indexed citations
17.
Zhou, Tong, Dunbing Tang, Haihua Zhu, & Liping Wang. (2020). Reinforcement Learning With Composite Rewards for Production Scheduling in a Smart Factory. IEEE Access. 9. 752–766. 40 indexed citations
18.
Ullah, Inayat, Dunbing Tang, Qi Wang, & Leilei Yin. (2017). Least Risky Change Propagation Path Analysis in Product Design Process. Systems Engineering. 20(4). 379–391. 17 indexed citations
19.
Tang, Dunbing & Min Dai. (2015). Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem. Chinese Journal of Mechanical Engineering. 28(5). 1048–1055. 52 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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