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Evaluation and prediction of on‐line maintenance workload in nuclear power plants
Author(s) -
Liang GuoFeng,
Lin JhihTsong,
Hwang SheueLing,
Huang Feihui,
Yenn TzuChung,
Hsu ChongCheng
Publication year - 2008
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20136
Subject(s) - workload , task (project management) , nuclear power plant , reliability engineering , nuclear power , engineering , computer science , simulation , systems engineering , operating system , ecology , physics , nuclear physics , biology
Abstract This study evaluates engineers' mental workload while maintaining digital systems in nuclear power plants (NPPs). First, according to the factors affecting the mental workload, a questionnaire was designed to evaluate the mental workload of maintenance engineers at the Second NPP in Taiwan. Then 16 maintenance engineers from the Second NPP participated in the experiment survey. The results indicated that the mental workload was lower in maintaining digital systems than that in analog systems. Finally, a mental workload model based on the neural network technique was established to predict the mental workload of maintenance engineers in maintaining digital systems. Through predicting mental workload, the manager can organize the human resources for each daily task to sustain the appropriate mental workload as well as improve maintenance performance. © 2008 Wiley Periodicals, Inc.