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Journal Article

Citation

Tsao L, Chang J, Ma L. Appl. Ergon. 2017; 62: 131-141.

Affiliation

Department of Industrial Engineering, Tsinghua University, 100084 Beijing, China. Electronic address: liangma@tsinghua.edu.cn.

Copyright

(Copyright © 2017, Elsevier Publishing)

DOI

10.1016/j.apergo.2017.02.021

PMID

28411723

Abstract

Fatigue is an identifiable and preventable cause of accidents in transport operations. Regarding the railway sector, incident logs and simulation studies show that employee fatigue leads to lack of alertness, impaired performance, and occurrence of incidents. China has one of the largest rail systems in the world, and Chinese railway employees work under high fatigue risks; therefore, it is important to assess their fatigue level and find the major factors leading to fatigue. We designed a questionnaire that uses Multidimensional Fatigue Instrument (MFI-20), NASA-TLX and subjective rating of work overtime feelings to assess employee fatigue. The contribution of each influential factor of fatigue was analysed using structural equation modelling. In total, 297 employees from the rail maintenance department and 227 employees from the locomotive department returned valid responses. The average scores and standard deviations for the five subscales of MFI-20, namely General Fatigue, Physical Fatigue, Reduced Activity, Reduced Motivation, and Mental Fatigue, were 2.9 (0.8), 2.8 (0.8), 2.5 (0.8), 2.5 (0.7), and 2.4 (0.8) among the rail maintenance employees and 3.5 (0.8), 3.5 (0.7), 3.3 (0.7), 3.0 (0.6), and 3.1 (0.7), respectively, among the locomotive employees. The fatigue of the locomotive employees was influenced by feelings related to working overtime (standardized r = 0.22) and workload (standardized r = 0.27). The work overtime control and physical working environment significantly influenced subjective feelings (standardized r = -0.25 and 0.47, respectively), while improper work/rest rhythms and an adverse physical working environment significantly increased the workload (standardized r = 0.48 and 0.33, respectively).

Copyright © 2017 Elsevier Ltd. All rights reserved.


Language: en

Keywords

Fatigue; Railway safety; Structural equation modelling

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