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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Combining deep learning with knowledge graph for macro process planning
Yajun Zhang, Shusheng Zhang, Rui Huang, et al.
Computers in Industry (2022) Vol. 140, pp. 103668-103668
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Towards new-generation human-centric smart manufacturing in Industry 5.0: A systematic review
Chao Zhang, Zenghui Wang, Guanghui Zhou, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102121-102121
Closed Access | Times Cited: 116
Knowledge graph-based manufacturing process planning: A state-of-the-art review
Youzi Xiao, Shuai Zheng, Jiancheng Shi, et al.
Journal of Manufacturing Systems (2023) Vol. 70, pp. 417-435
Closed Access | Times Cited: 62
The resurrection of digital triplet: A cognitive pillar of human-machine integration at the dawn of industry 5.0
Hassan Alimam, Giovanni Mazzuto, Nicola Tozzi, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 10, pp. 101846-101846
Open Access | Times Cited: 26
Evolving to multi-modal knowledge graphs for engineering design: state-of-the-art and future challenges
Xinyu Pan, Xinyu Li, Qi Li, et al.
Journal of Engineering Design (2024), pp. 1-40
Closed Access | Times Cited: 13
Making knowledge graphs work for smart manufacturing: Research topics, applications and prospects
Y Wan, Ying Liu, Zhenyuan Chen, et al.
Journal of Manufacturing Systems (2024) Vol. 76, pp. 103-132
Open Access | Times Cited: 13
Knowledge graph with deep reinforcement learning for intelligent generation of machining process design
Yiwei Hua, Ru Wang, Zuoxu Wang, et al.
Journal of Engineering Design (2024), pp. 1-35
Closed Access | Times Cited: 9
A knowledge graph-based intelligent planning method for remanufacturing processes of used parts
Shuo Zhu, L C Gao, Zhigang Jiang, et al.
Journal of Engineering Design (2025), pp. 1-28
Closed Access | Times Cited: 1
Systematic knowledge modeling and extraction methods for manufacturing process planning based on knowledge graph
Peihan Wen, Yan Ma, Ruiquan Wang
Advanced Engineering Informatics (2023) Vol. 58, pp. 102172-102172
Closed Access | Times Cited: 20
A knowledge graph-based approach to modeling & representation for machining process design intent
Jiachen Liang, Shusheng Zhang, Yajun Zhang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102645-102645
Closed Access | Times Cited: 8
A novel method based on deep reinforcement learning for machining process route planning
Hang Zhang, Wenhu Wang, Shusheng Zhang, et al.
Robotics and Computer-Integrated Manufacturing (2023) Vol. 86, pp. 102688-102688
Closed Access | Times Cited: 14
A Review and Prospects of Manufacturing Process Knowledge Acquisition, Representation, and Application
Zhongyi Wu, Cheng Liang
Machines (2024) Vol. 12, Iss. 6, pp. 416-416
Open Access | Times Cited: 5
Hierarchical construction and application of machining domain knowledge graph based on as-fabricated information model
Qiangwei Bao, Pai Zheng, Sheng Dai
Advanced Engineering Informatics (2024) Vol. 62, pp. 102638-102638
Closed Access | Times Cited: 5
Machining feature process route planning based on a graph convolutional neural network
Zhen Wang, Shusheng Zhang, Hang Zhang, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102249-102249
Closed Access | Times Cited: 12
mKGMPP: A multi-layer knowledge graph integration framework and its inference method for manufacturing process planning
Zechuan Huang, Xin Guo, Chong Jiang, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103266-103266
Closed Access
A novel method for intelligent reasoning of machining step sequences based on deep reinforcement learning
Biao Xiao, Zhengcai Zhao, Baode Xu, et al.
Journal of Manufacturing Systems (2025) Vol. 80, pp. 626-642
Closed Access
An effective NC machining process planning method via integrating grammar knowledge with deep learning
Huang Rui, Fang Zhou, Bo Huang, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123872-123872
Closed Access | Times Cited: 3
A knowledge graph construction and causal structure mining approach for non-stationary manufacturing systems
Mingyuan Xia, Xuandong Mo, Yahui Zhang, et al.
Robotics and Computer-Integrated Manufacturing (2025) Vol. 95, pp. 103013-103013
Closed Access
Cognition and context-aware decision-making systems for a sustainable planet: a survey on recent advancements, applications and open challenges
John Violos, Georgios Mamanis, Ioannis Kompatsiaris, et al.
Discover Sustainability (2025) Vol. 6, Iss. 1
Open Access
Process Planning for Large Container Ship Propeller Shaft Machining Based on an Improved Ant Colony Algorithm
Guotai Du, Hongkui Ma, Yu Bai, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 5, pp. 841-841
Open Access | Times Cited: 2
A multi-dimensional cognitive framework for cognitive manufacturing based on OAR model
Tengyuan Jiang, Jingtao Zhou, Jianhua Zhao, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 469-485
Closed Access | Times Cited: 9
Data-Driven and Knowledge-Guided Approach for NC Machining Process Planning
ZeFan Han, Rui Huang, Bo Huang, et al.
Computer-Aided Design (2023) Vol. 162, pp. 103562-103562
Closed Access | Times Cited: 5
An effective process design intent inference method of process data via integrating deep learning and grammar parsing
Rui Huang, Zefan Han, Mingtao Fei, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102174-102174
Closed Access | Times Cited: 4
A Knowledge-Guided Process Planning Approach with Reinforcement Learning
Lijun Zhang, Hongjin Wu, Chen Ye-lin, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Combining Active Learning and Self-Paced Learning for Cost-Effective Process Design Intents Extraction of Process Data
Rui Huang, Shuyi Zhu, Bo Huang
Journal of Computational Design and Engineering (2024) Vol. 11, Iss. 2, pp. 161-175
Open Access | Times Cited: 1
Employing deep reinforcement learning for machining process planning: An improved framework
Hang Zhang, Wenhu Wang, Yue Wang, et al.
Journal of Manufacturing Systems (2024) Vol. 78, pp. 370-393
Closed Access | Times Cited: 1
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