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Mental workload of local vs remote operator in human-machine interaction case study

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Since late 2019, a novel Coronavirus disease 2019 (COVID-19) has spread globally. As a result, businesses were forced to send their workforce into remote working, wherever possible. While research in this area has seen an increase in studying and developing technologies that allow and support such remote working style, not every sector is currently prepared for such a transition. Especially the manufacturing sector has faced challenges in this regard. In this paper, the mental workload of two groups of participants is studied during a human-robot interaction task. Participants were asked to bring a robotised cell used in a dispensing task to full production by tuning system parameters. After the experiment, a self-assessment of the participants’ perceived mental workload using the NASA Task Load Index (NASA-TLX) was used. The results show that remote participants tend to have lower perceived workload compared to the local participants.

Funding

EPSRC Centre for Doctoral Training in Embedded Intelligence

Engineering and Physical Sciences Research Council

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Digital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)

Engineering and Physical Sciences Research Council

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History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Advances in Manufacturing Technology XXXIV. Proceedings of the 18th International Conference on Manufacturing Research, incorporating the 35th National Conference on Manufacturing Research, 7-10 September 2021, University of Derby, Derby, UK

Pages

33-38

Source

18th International Conference in Manufacturing Research (ICMR 2021)

Publisher

IOS Press

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by IOS Press under the Creative Commons Attribution-Non Commercial 4.0 International Licence (CC BY-NC). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc/4.0/

Acceptance date

18/05/2021

Publication date

2021-09-31

Copyright date

2021

ISBN

9781643681986; 9781643681993

Book series

Advances in Transdisciplinary Engineering. Volume 15: Advances in Manufacturing Technology XXXIV

Language

en

Location

Derby, UK (Virtual)

Event dates

7th September 2021 - 10th September 2021

Depositor

Dr Ali Al-Yacoub. Deposit date: 5 June 2021