Smart In-Process Inspection with Human-Automation Symbiosis in Industry 5.0 Manufacturing Systems
Author(s)
Wang, Shu
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
Since the advent of Industry 4.0, manufacturing industries have been continually integrating cutting-edge technologies into different aspects of manufacturing systems, creating a more complex and dynamic production environment. To maintain high product quality throughout the manufacturing processes, in-process inspection (IPI) becomes an efficient strategy, enabling prompt identification of defective parts and real-time process control through defect mitigation. Consequently, smart in-process inspection (s-IPI) has emerged as a critical research area in manufacturing.
Furthermore, as manufacturing technologies advance, the relationship between humans and automation agents evolves. Industry 5.0, as the next phase in manufacturing, differs from Industry 4.0 by shifting its focus from economic gains to human social value and well-being, emphasizing a human-centric philosophy. This underscores the importance of implementing human-automation symbiosis (HAS), which fosters closer partnership and mutually beneficial collaboration between humans and automation agents.
In this regard, this dissertation envisions smart in-process inspection with human-automation symbiosis in Industry 5.0 manufacturing systems (I5MS) as an emergent research paradigm. It explores the integration of smart in-process inspection into manufacturing systems and the implementation of HAS for I5MS from the task allocation and task execution perspectives, which builds upon multiple disciplines, including advanced manufacturing systems, cognitive engineering, and human-automation interaction.
With s-IPI and HAS as the two technical pillars, four fundamental issues are identified, including in-process inspection, defect mitigation planning, dynamic and adaptive task allocation, and behavioral intervention design for human-automation collaboration. Corresponding technical approaches are proposed for each issue.
Given the interdisciplinary nature, the research findings of this dissertation are poised to have a broad impact within and beyond manufacturing systems, such as service systems or operational systems. They have the potential to influence various sectors by providing a framework for integrating advanced inspection and human-automation symbiosis into diverse industrial applications. This research sets the stage for future innovations in manufacturing, ultimately contributing to the development of more intelligent, efficient, and human-centric environments in the era of Industry 5.0.
Sponsor
Date
2024-08-27
Extent
Resource Type
Text
Resource Subtype
Dissertation (PhD)