Ding Zhang

Dr. Ding Zhang

Guangdong University of Technology
orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2021 in Journal of Manufacturing Systems
Verified
Journal Article
Closed access
JLJiewu Leng
Jiewu Leng
DWDewen Wang
Dewen Wang
Weiming ShenWeiming Shen
Weiming Shen
XLXinyu Li
Xinyu Li
DZDing Zhang
Ding Zhang
XCXin Chen
Xin Chen

2 June 2018 in Journal of Ambient Intelligence and Humanized Computing
Verified
Journal Article
Closed access
PDF file
JLJiewu Leng
Jiewu Leng
HZHao Zhang
Hao Zhang
DYDouxi Yan
Douxi Yan
DZDing Zhang
Ding Zhang
XCXin Chen
Xin Chen
DZDing Zhang
Ding Zhang

18 December 2020 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
JLJiewu Leng
Jiewu Leng
SYShide Ye
Shide Ye
MZMan Zhou
Man Zhou
JZJ. Leon Zhao
J. Leon Zhao
DZDing Zhang
Ding Zhang
LFLeijie Fu
Leijie Fu
Blockchain is a new generation of secure information technology that is fueling business and industrial innovation. Many studies on key enabling technologies for resource organization and system operation of blockchain-secured smart manufacturing in Industry 4.0 had been conducted. However, the progression and promotion of these blockchain applications have been fundamentally impeded by various issues in scalability, flexibility, and cybersecurity. This survey discusses how blockchain systems can overcome potential cybersecurity barriers to achieving intelligence in Industry 4.0. In this regard, eight cybersecurity issues (CIs) are identified in manufacturing systems. Ten metrics for implementing blockchain applications in the manufacturing system are devised while surveying research in blockchain-secured smart manufacturing. This study reveals how these CIs have been studied in the literature. Based on insights obtained from this analysis, future research directions for blockchain-secured smart manufacturing are presented, which potentially guides research on urgent cybersecurity concerns for achieving intelligence in Industry 4.0.

12 September 2023 in Journal of Manufacturing Systems
Verified
Journal Article
Closed access
JLJiewu Leng
Jiewu Leng
YZYuanwei Zhong
Yuanwei Zhong
ZLZisheng Lin
Zisheng Lin
KXKailin Xu
Kailin Xu
Dimitris MourtzisDimitris Mourtzis
Dimitris Mourtzis
Weiming ShenWeiming Shen
Weiming Shen

6 August 2019 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
JLJiewu Leng
Jiewu Leng
DYDouxi Yan
Douxi Yan
DZDing Zhang
Ding Zhang
KXKailin Xu
Kailin Xu
JZJ. Leon Zhao
J. Leon Zhao
XCXin Chen
Xin Chen
The growth of individualized product demands drives high flexibility of manufacturing processes, which requires large-scale deployment of Industrial Internet of Things (IIoT). Since centralized control of IIoT suffers from poor flexibility in coping with disturbances and changes, a decentralized organization structure is a better choice, in which a permissioned blockchain-driven IIoT can enable partially decentralized self-organization and thus offload and accelerate the optimization of upper-level manufacturing planning. A novel iterative bi-level hybrid intelligence model named ManuChain is proposed to get rid of unbalance/inconsistency between holistic planning and local execution in individualized manufacturing systems. Lower-level blockchain-driven smart contracts proactively decentralize fine-grained and individualized task execution among machine tools via Raspberry Pi-based smart gateways and make the results available on an upper-level digital twin model for iterative coarse-grained holistic optimization. A prototype ManuChain based on a permissioned blockchain network is presented to realize both lower-level crowd self-organizing intelligence and upper-level holistic optimization intelligence.

29 February 2024 in Journal of Manufacturing Systems
Verified
Journal Article
Closed access
JLJiewu Leng
Jiewu Leng
XZXiaofeng Zhu
Xiaofeng Zhu
ZHZhiqiang Huang
Zhiqiang Huang
XLXingyu Li
Xingyu Li
PZPAI ZHENG
PAI ZHENG
DZDing Zhang
Ding Zhang