Mixture of Human and Machine Intelligence in Digital Manufacturing, 2nd Edition

A special issue of Designs (ISSN 2411-9660). This special issue belongs to the section "Smart Manufacturing System Design".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2

Special Issue Editors

School of Science, Technology and Health, York St John University, York YO31 7EX, UK
Interests: human-in-the-loop system design; digital intervention; cyber security; artificial intelligence; decision making
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Digital and Intelligent Technology Department, Beijing Bohua Xinzhi Technology Co., Ltd., Beijing, China
Interests: artificial intelligent for condition monitoring; fault diagnosis; prognostic health management; especially for deep learning; transfer learning; few-shot learning method and their application for the large industrial environment; reinforcement learning for control and its applications
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Department of Bioengineering, Imperial College London and School of Engineering, Lancaster University, Lancaster, UK
Interests: human–robot interaction; assistive robotics; teleoperation; reinforcement learning; control theory and applications
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Special Issue Information

Dear Colleagues,

This is the second edition of a previous successful Special Issue titled “Mixture of Human and Machine Intelligence in Digital Manufacturing” (https://www.mdpi.com/journal/designs/special_issues/R78POOKP14).

Industry 4.0 and digital manufacturing describe new paradigms for seamless human–machine interface (HMI). A number of definitions of HMI have emphasized the significance of understanding how user interface technologies that enable the development of useful, usable, and aesthetic software and hardware are designed. Modern interaction technology has moved from simple use of computers as tools to the establishment of human relationships with autonomous entities, which gradually emphasizes human factors in various steps of interaction processes (De Visser and Shaw, 2018). In this regard, an organic combination of human and machine would leverage their intelligence in a dynamic fashion and motivate computational intelligence development, providing more opportunities for traditional manufacturing system design. While machines interact with manufacturing systems and make human-relevant decisions, new design patterns in perception, control, and arbitration are required to support the integration of human expertise. In addition, sensory data collection and analysis can further aid digital decision-making.

HMI is regarded as a solution for effective operation of machine systems by humans without potential error. Addressing the developments in HMI in an Industry 4.0 context is not sufficient. The objective of this Special Issue is therefore to provide a forum for academics and industrial practitioners to share their latest achievements, identify critical issues and challenges for advanced designs, and highlight applications of HMI in manufacturing.

Dr. Yang Lu
Dr. Ming Zhang
Dr. Ziwei Wang
Guest Editors

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Keywords

  • human–machine interface
  • human–robot collaboration
  • human-in-the-loop (HITL)
  • human-centered design
  • human factors: intent, gaze, emotion, and sensation
  • ergonomics and muscle activation analysis
  • gamification in manufacturing
  • machine/computer intelligence
  • optimization
  • virtual reality, augmented reality, and mixed reality
  • resilience, sustainability, and digitalization
  • deep learning, machine learning, and artificial intelligence
  • cyber–physical systems
  • trustworthy autonomous systems

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