Sensor and data: key elements of human-machine interaction for human-centric smart manufacturing

Yang, Jialu ORCID: https://orcid.org/0000-0003-1463-2677, Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940 and Morgan, Phillip ORCID: https://orcid.org/0000-0002-5672-0758 2023. Sensor and data: key elements of human-machine interaction for human-centric smart manufacturing. Presented at: 5th International Conference on Industry 4.0 and Smart Manufacturing, 22-24 November 2023. Procedia Computer Science. Elsevier,

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Abstract

The proposal of Industry 5.0 has made sustainability, human-centric and resilience the core of digital manufacturing, which also puts forward new requirements for the human-machine interaction (HMI) paradigm in human-centric smart manufacturing (HCSM). In the manufacturing scenario, the process of HMI can be divided into four parts: 1) Sensors and hardware, where the environment information and input signals are collected, 2) Data processing, where the signals are converted into data, 3) Transmission mechanism, where the data is transmitted to the processing centre, and 4) Interaction and collaboration. Among them, sensors and data are expected to become breakthrough points in optimising HMI. This is not only due to the emergence of new research, innovation and technologies but also because they are closely influenced by the new design concepts brought about by Industry 5.0. This paper analyses the latest studies and technologies in the sensor field and their possible applications in HCSM scenarios. Then, opportunities and challenges of data analysis in the HMI in Industry 5.0 are discussed. Finally, based on the design concepts and requirements of Industry 5.0, this paper demonstrates how they will become the key points for future HMI development.

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Engineering Psychology
Publisher:	Elsevier
ISSN:	1877-0509
Date of First Compliant Deposit:	25 November 2023
Date of Acceptance:	20 September 2023
Last Modified:	29 Nov 2023 16:45
URI:	https://orca.cardiff.ac.uk/id/eprint/164372

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