Fault Diagnosis: Human Performance in the Digital and Automation Context

Xi Lyu 1
Manrong She 2
Dan Pan 3
Xiaojun Wu 2
Kejin Chen 2
Zhizhong Li 2
Publication typeBook Chapter
Publication date2022-10-01
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ISSN2193472X, 21934738
Abstract
Diagnosis is a cognitivelyCognitively difficult task for operators working in the control rooms of complex industrial systems. The complexity of contemporary industrial systems increases with the application of digital and automation technologies, making fault diagnosis of such systems even more challenging to human operators. This chapter proposes a framework for human factors research on fault diagnosis, including diagnosis models and strategies, factors influencing human diagnosis performance, and methods to improve diagnosis task performance. As a general idea, automation should facilitate, help, and even collaborate with human operators to perform fault diagnosis.
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Lyu X. et al. Fault Diagnosis: Human Performance in the Digital and Automation Context // Automation, Collaboration, & E-Services. 2022. pp. 265-288.
GOST all authors (up to 50) Copy
Lyu X., She M., Pan D., Wu X., Chen K., Li Z. Fault Diagnosis: Human Performance in the Digital and Automation Context // Automation, Collaboration, & E-Services. 2022. pp. 265-288.
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TY - GENERIC
DO - 10.1007/978-3-031-10780-1_14
UR - https://doi.org/10.1007/978-3-031-10780-1_14
TI - Fault Diagnosis: Human Performance in the Digital and Automation Context
T2 - Automation, Collaboration, & E-Services
AU - Lyu, Xi
AU - She, Manrong
AU - Pan, Dan
AU - Wu, Xiaojun
AU - Chen, Kejin
AU - Li, Zhizhong
PY - 2022
DA - 2022/10/01
PB - Springer Nature
SP - 265-288
SN - 2193-472X
SN - 2193-4738
ER -
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@incollection{2022_Lyu,
author = {Xi Lyu and Manrong She and Dan Pan and Xiaojun Wu and Kejin Chen and Zhizhong Li},
title = {Fault Diagnosis: Human Performance in the Digital and Automation Context},
publisher = {Springer Nature},
year = {2022},
pages = {265--288},
month = {oct}
}