Journal ArticleDOI
Designing intelligent manufacturing systems through Human-Machine Cooperation principles: A human-centered approach
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TLDR
The lack of attention paid to the correct integration of humans in Intelligent Manufacturing Systems is highlighted and solutions based on Human-Machine Cooperation principles to retain humans in the process control loop with different levels of involvement identified by the levels of automation are provided.About:
This article is published in Computers & Industrial Engineering.The article was published on 2017-09-01. It has received 206 citations till now. The article focuses on the topics: Intelligent decision support system & Computer-integrated manufacturing.read more
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Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context
TL;DR: The proposed research work is focused on the design and development of a practical solution, called Sophos-MS, able to integrate augmented reality contents and intelligent tutoring systems with cutting-edge fruition technologies for operators’ support in complex man-machine interactions.
Journal ArticleDOI
Industry 4.0: A bibliometric analysis and detailed overview
TL;DR: This paper summarizes the growth structure of Industry 4.0 during the last 5 years and provides the concise background overview of Industry 5.0 related works and various application areas.
Journal ArticleDOI
Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing
TL;DR: The evolutionary footprint of intelligent manufacturing is reviewed from the perspective ofHCPSs, and the implications, characteristics, technical frame, and key technologies of HCPSs for NGIM are then discussed in depth.
Journal ArticleDOI
Augmented reality in support of intelligent manufacturing - a systematic literature review
Johannes Egger,Tariq Masood +1 more
TL;DR: The results of this review indicate that the context of research concerning AR gets increasingly broader, especially by addressing challenges when implementing AR solutions, and that the state of the art, the current challenges, and future directions of manufacturing related AR research get increasingly broader.
Journal ArticleDOI
Current research and future perspectives on Human Factors and Ergonomics in Industry 4.0
TL;DR: A systematic literature review is presented, consisting of quantitative and qualitative data, focusing on investigating to what extent, what type, and how academic publications on Industry 4.0 integrate human factors and ergonomics in their research.
References
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Book ChapterDOI
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
TL;DR: In this article, the results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed, including task-, behavior-, and subject-related correlates of subjective workload experiences.
Journal ArticleDOI
Toward a Theory of Situation Awareness in Dynamic Systems
TL;DR: A theoretical model of situation awareness based on its role in dynamic human decision making in a variety of domains is presented and design implications for enhancing operator situation awareness and future directions for situation awareness research are explored.
Journal ArticleDOI
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
TL;DR: A unified 5-level architecture is proposed as a guideline for implementation of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space.
Journal ArticleDOI
A model for types and levels of human interaction with automation
TL;DR: A model for types and levels of automation is outlined that can be applied to four broad classes of functions: 1) information acquisition; 2) information analysis; 3) decision and action selection; and 4) action implementation.
Book
Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models
TL;DR: In this paper, a discussion of the requirement for different types of models for representing performance at the skill-, rule-, and knowledge-based levels, together with a review of the different levels in terms of signals, signs, and symbols is presented.