Qing Chang

3.6k total citations · 1 hit paper
149 papers, 2.7k citations indexed

About

Qing Chang is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Qing Chang has authored 149 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 97 papers in Industrial and Manufacturing Engineering, 36 papers in Control and Systems Engineering and 26 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Qing Chang's work include Scheduling and Optimization Algorithms (64 papers), Flexible and Reconfigurable Manufacturing Systems (44 papers) and Manufacturing Process and Optimization (27 papers). Qing Chang is often cited by papers focused on Scheduling and Optimization Algorithms (64 papers), Flexible and Reconfigurable Manufacturing Systems (44 papers) and Manufacturing Process and Optimization (27 papers). Qing Chang collaborates with scholars based in United States, China and United Kingdom. Qing Chang's co-authors include Jorge Arinez, Guoxian Xiao, Stephan Biller, Jing Huang, Jun Ni, Robert X. Gao, Jianjing Zhang, Jing Zou, Junfeng Wang and Chengying Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Scientific Reports.

In The Last Decade

Qing Chang

133 papers receiving 2.6k citations

Hit Papers

Artificial Intelligence i... 2020 2026 2022 2024 2020 50 100 150 200 250
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. Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook
    2020 298 citations Jorge Arinez, Qing Chang et al. Journal of Manufacturing Science and 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
Qing Chang United States 29 1.6k 474 452 376 288 149 2.7k
Jorge Arinez United States 28 1.4k 0.9× 242 0.5× 268 0.6× 351 0.9× 384 1.3× 114 2.4k
Moneer Helu United States 22 1.1k 0.7× 263 0.6× 145 0.3× 281 0.7× 127 0.4× 43 1.8k
Damien Trentesaux France 36 2.8k 1.7× 487 1.0× 125 0.3× 145 0.4× 420 1.5× 154 3.9k
Luca Fumagalli Italy 25 2.4k 1.5× 253 0.5× 402 0.9× 63 0.2× 350 1.2× 112 3.7k
Marco Macchi Italy 25 2.3k 1.4× 355 0.7× 523 1.2× 54 0.1× 510 1.8× 173 3.6k
Dunbing Tang China 28 2.3k 1.4× 403 0.9× 121 0.3× 208 0.6× 207 0.7× 142 3.3k
Deyi Xue Canada 33 1.4k 0.8× 397 0.8× 169 0.4× 128 0.3× 136 0.5× 139 3.2k
Guanghui Zhou China 30 1.6k 1.0× 186 0.4× 154 0.3× 215 0.6× 150 0.5× 106 2.8k
Hung-An Kao United States 9 2.7k 1.6× 516 1.1× 230 0.5× 52 0.1× 569 2.0× 9 4.1k
Tullio Tolio Italy 31 2.6k 1.6× 289 0.6× 320 0.7× 60 0.2× 795 2.8× 155 3.5k

Countries citing papers authored by Qing Chang

Since Specialization
Citations

This map shows the geographic impact of Qing Chang'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 Qing Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing Chang more than expected).

Fields of papers citing papers by Qing Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qing Chang. 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 Qing Chang. The network helps show where Qing Chang may publish in the future.

Co-authorship network of co-authors of Qing Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Chang. A scholar is included among the top collaborators of Qing Chang 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 Qing Chang. Qing Chang 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.
Chang, Qing, et al.. (2025). Demand-driven hierarchical integrated planning-scheduling control for a mobile robot-operated flexible smart manufacturing system. Robotics and Computer-Integrated Manufacturing. 95. 103015–103015. 4 indexed citations
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Chang, Qing, et al.. (2025). Generative AI-powered planning: A hybrid graph-diffusion approach for demand-driven flexible manufacturing systems. Journal of Manufacturing Systems. 83. 175–195. 1 indexed citations
5.
Chang, Qing, et al.. (2025). Train small, deploy large: Scaling multi-agent reinforcement learning for multi-stage manufacturing lines. Journal of Manufacturing Systems. 81. 155–168.
6.
Li, Chen, et al.. (2024). Multi-agent reinforcement learning for integrated manufacturing system-process control. Journal of Manufacturing Systems. 76. 585–598. 6 indexed citations
7.
Tan, Yanchao, Marvin Carl May, Qing Chang, et al.. (2024). Unlocking the Potential of Remanufacturing Through Machine Learning and Data-Driven Models—A Survey. Algorithms. 17(12). 562–562. 1 indexed citations
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Chang, Qing, et al.. (2023). An integrated control strategy for simultaneous robot assignment, tool change and preventive maintenance scheduling using Heterogeneous Graph Neural Network. Robotics and Computer-Integrated Manufacturing. 84. 102594–102594. 11 indexed citations
10.
Huang, Jing, et al.. (2022). Dynamic Robot Assignment for Flexible Serial Production Systems. IEEE Robotics and Automation Letters. 7(3). 7303–7310. 16 indexed citations
11.
Huang, Jing, Jianjing Zhang, Qing Chang, & Robert X. Gao. (2021). Integrated process-system modelling and control through graph neural network and reinforcement learning. CIRP Annals. 70(1). 377–380. 11 indexed citations
12.
Huang, Jing, et al.. (2021). Data-Enabled Permanent Production Loss Analysis for Serial Production Systems With Variable Cycle Time Machines. IEEE Robotics and Automation Letters. 6(4). 6418–6425. 8 indexed citations
13.
Li, Yang, et al.. (2021). Energy-Saving Control in Multistage Production Systems Using a State-Based Method. IEEE Transactions on Automation Science and Engineering. 19(4). 3324–3337. 10 indexed citations
14.
Huang, Jing, et al.. (2021). Deep multi-agent reinforcement learning for multi-level preventive maintenance in manufacturing systems. Expert Systems with Applications. 192. 116323–116323. 54 indexed citations
15.
Tian, Yu, Jing Huang, & Qing Chang. (2020). Mastering the Working Sequence in Human-Robot Collaborative Assembly Based on Reinforcement Learning. IEEE Access. 8. 163868–163877. 38 indexed citations
16.
Wang, Jianwei, Chao Gao, Shi Dong, et al.. (2020). Current Status and Future Prospects of Existing Research on Digitalization of Highway Infrastructure. Zhongguo gonglu xuebao. 33(11). 101. 18 indexed citations
17.
Huang, Jing, Qing Chang, & Nilanjan Chakraborty. (2019). Machine Preventive Replacement Policy for Serial Production Lines Based on Reinforcement Learning. 76. 523–528. 9 indexed citations
18.
Huang, Jing, Qing Chang, Jing Zou, Jorge Arinez, & Guoxian Xiao. (2018). Real-time Control of Maintenance on Deteriorating Manufacturing System. 4. 211–216. 2 indexed citations
19.
Lei, Yong, et al.. (2016). Intermittent Connection Fault Diagnosis for CAN Using Data Link Layer Information. IEEE Transactions on Industrial Electronics. 64(3). 2286–2295. 18 indexed citations
20.
Chang, Qing. (2004). Investigation and analysis of zinc in suburban soil in Chongqing.

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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