Human–AI Hybrid Models Towards Cognitive Manufacturing and Service Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 476

Special Issue Editors


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Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: industrial intelligence; cyber-physical systems; deep learning; human-centric assessment

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Guest Editor
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Interests: digital twins; engineering product lifecycle management; knowledge graphs; human-robot collaboration; smart manufacturing; resilient supply chains

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Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: human-AI collaboration; human factors; affective computing

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Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: human factors and human performance; human-centered design; human machine interface (HMI); usability evaluation

Special Issue Information

Dear Colleagues,

Nowadays, the rapid advancements and widespread implementations of artificial intelligence (AI), digital twins (DTs), robotics, and human–machine interaction (HMI) have brought about remarkable transformations in the manufacturing and service industries, reshaping how humans and machines collaborate to achieve superior performance. As we move into the era of Industry 5.0, the synergy between human intelligence and AI is becoming pivotal in terms of creating systems with higher cognitive intelligence that are more efficient, adaptive, and human-centric. To pave the way toward this future, in-depth investigations should be conducted from the human and AI aspects, facilitating their seamless integration and collaboration to realize optimized decision-making, enhanced productivity, and improved user experiences.

This Special Issue invites contributions that explore innovative human–AI hybrid models, methodologies, frameworks, applications, and reviews to advance cognitive manufacturing and service systems. We aim to provide a platform for researchers, practitioners, and industry experts to share insights on how such hybrid systems can address the growing complexity of modern manufacturing and service operations while ensuring ethical, sustainable, and human-focused outcomes. Research topics may include (but are not limited to) the following:

  • Frameworks for human-AI collaboration;
  • Cognitive models in hybrid intelligent systems;
  • Trustworthy and interpretable methods for manufacturing and service systems;
  • Human-centric systems design;
  • Innovative design of HMI;
  • Human factor engineering and ergonomics studies;
  • Human-robot collaboration;
  • Human-AI-assisted DT applications;
  • Cognitive DTs and human DTs;
  • Human-in-the-loop service design;
  • User experience studies;
  • AI-driven decision-making;
  • Case studies in manufacturing and service systems.

We look forward to receiving your contributions.

Dr. Bufan Liu
Dr. Kendrik Yan Hong Lim
Dr. Ziqing Xia
Dr. Meng-Hsueh Hsieh
Guest Editors

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Keywords

  • artificial intelligence
  • human intelligence
  • cognitive models
  • human-AI hybrids
  • digital twins
  • robotics
  • human-centric methods
  • intelligent cognitive manufacturing and service

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Published Papers (1 paper)

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Research

19 pages, 2028 KiB  
Article
Blockchain-Based Information Sharing Mechanism for Complex Product Supply Chain
by Xin Guo, Geng Zhang and Yingfeng Zhang
Electronics 2025, 14(9), 1780; https://doi.org/10.3390/electronics14091780 - 27 Apr 2025
Viewed by 182
Abstract
In recent years, the rapid development and widespread application of new generation information technology has profoundly influenced the new round of manufacturing industry transformation. Information sharing is a key factor in determining the efficiency of supply chain operations and remains one of the [...] Read more.
In recent years, the rapid development and widespread application of new generation information technology has profoundly influenced the new round of manufacturing industry transformation. Information sharing is a key factor in determining the efficiency of supply chain operations and remains one of the hot issues of supply chain management research. Considering the disrupted and unstable information flow of current complex product supply chain, this paper constructs a blockchain-based complex product supply chain information sharing system (BC-CPSCISS). A blockchain-based information storage and access method is proposed to promote secure, transparent, and efficient information interaction. A decision model for complex product supply chain information sharing was established based on Stackelberg game theory. The impact of blockchain application cost and its value gain on the optimal decision is herein discussed. The condition of applying blockchain technology under economic objective is also analyzed. The results indicate that complex product supply chain enterprises should fully consider the cost of applying blockchain and its impact on overall economic benefits before making their decision. Full article
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