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A framework for operator – workstation interaction in Industry 4.0.

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Title: A framework for operator – workstation interaction in Industry 4.0.
Authors: Golan, Maya1 (AUTHOR) mayag@afeka.ac.il, Cohen, Yuval1 (AUTHOR), Singer, Gonen1 (AUTHOR)
Source: International Journal of Production Research. Apr2020, Vol. 58 Issue 8, p2421-2432. 12p. 1 Diagram, 1 Chart.
Subjects: Industry 4.0, Manufacturing workstations, Artificial intelligence, Affective computing
Abstract: We draw on cognitive and behavioural theories and on the artificial intelligence literature in order to propose a framework of future operator – workstation interaction in the 'Industry 4.0' era. We name the proposed framework 'Operator – Workstation Interaction 4.0'. The latter's capabilities permit an adaptive, ongoing interaction that aims to improve operator safety, performance, well-being, and satisfaction as well as the factory's production measures. The framework is composed of three subsystems: (1) the observation subsystem which observes the operator and the processes occurring in the workstation, (2) the analysis subsystem which generates understanding and implications of the observations output, (3) the reaction subsystem which determines if and how to respond. The paper describes these elements and illustrate them using an example of a fatigued worker. The contributions, implications, and limitations of the proposed framework are discussed, and future research directions are presented. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A framework for operator – workstation interaction in Industry 4.0.
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  Data: <searchLink fieldCode="AR" term="%22Golan%2C+Maya%22">Golan, Maya</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mayag@afeka.ac.il</i><br /><searchLink fieldCode="AR" term="%22Cohen%2C+Yuval%22">Cohen, Yuval</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Singer%2C+Gonen%22">Singer, Gonen</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Apr2020, Vol. 58 Issue 8, p2421-2432. 12p. 1 Diagram, 1 Chart.
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  Data: <searchLink fieldCode="DE" term="%22Industry+4%2E0%22">Industry 4.0</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+workstations%22">Manufacturing workstations</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Affective+computing%22">Affective computing</searchLink>
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  Data: We draw on cognitive and behavioural theories and on the artificial intelligence literature in order to propose a framework of future operator – workstation interaction in the 'Industry 4.0' era. We name the proposed framework 'Operator – Workstation Interaction 4.0'. The latter's capabilities permit an adaptive, ongoing interaction that aims to improve operator safety, performance, well-being, and satisfaction as well as the factory's production measures. The framework is composed of three subsystems: (1) the observation subsystem which observes the operator and the processes occurring in the workstation, (2) the analysis subsystem which generates understanding and implications of the observations output, (3) the reaction subsystem which determines if and how to respond. The paper describes these elements and illustrate them using an example of a fatigued worker. The contributions, implications, and limitations of the proposed framework are discussed, and future research directions are presented. [ABSTRACT FROM AUTHOR]
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  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Manufacturing workstations
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      – SubjectFull: Artificial intelligence
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      – SubjectFull: Affective computing
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              Text: Apr2020
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