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.
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