龍門核電廠運轉員心智負荷預測方法之探討

龍門核電廠與過去核電廠不同之處在於龍門核電廠改採用數位儀控的系統。雖然系統操作變簡單，但卻呈現太多警報資訊，卻造成運轉員心智負荷提高。因此如何準確的衡量運轉員的心智負荷，變成電廠很重要的課題。現有主要心智負荷衡量方法中，皆為事後或於任務進行中衡量人員心智負荷情形。本研究提供一個預測模型，能事先預測運轉員注意力資源的需求與衝突情況於執行任務，並以20位運轉員填寫之NASA-TLX問卷結果驗證此模型。研究結果顯示本研究之預測模型與NASA-TLX的問卷結果相關係數為0.971，而迴歸模型的解釋能力為92.5%。此模型可提供核電廠預測運轉員處理異常狀況時的心智負荷，並能提供幫助核電廠進行流程改善的建議。

關鍵字

龍門核電廠；心智負荷； NASA-TLX ；多重資源理論

並列摘要

Different from the traditional nuclear power plants (NPPs) , Lungman NPP applys digital control systems. Although digital systems are easily operated, they convey a lot of information which consequently increases operators' mental workload. Therefore, it is an important issue for Lungman NPP to measure operators’ mental workload correctly. Most of current methods for mental workload measurement are measured during performing tasks. The study proposes a model to predict operators’ mental resource demands and possible conflicts on performing tasks so that operators' mental workload　could be predicted in advance. The model was validated with the data of 20 operators who answered the NASA-TLX questionnaire. Results showed that the correlation coefficient was 0.971 between the prediction and the data. The coefficient of determination was 92.5% for the regression model. This predictive model will be able to predict operators' mental workload when they perform the abnormal operation procedures and to provide suggestions for improving these procedures.

並列關鍵字

Lungmen Nuclear Power Plant ； Mental Workload ； NASA-TLX ； multiple resource model

參考文獻

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龍門核電廠運轉員心智負荷預測方法之探討

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