自動化系統操控績效(ASOP)意指自動化裝置如何為監控者有效的監督及操控。本研究的目的，即由人類動態決策之特性，探討及提升自動化操控的作業績效。過去的研究發現，情境認知(Situation Awareness)與信任度(Trust)是影響自動化系統執行績效的重要因子。本研究第一階段，首先建構一情境認知與信任度的認知決策概念架構，依此架構建構以情境認知、信任度與硬體可靠度為衡量自動化系統執行績效的關係模型；其次，提出自動化系統操控績效的量化評估模型；再應用品質工程穩健設計之技術，建立一衡量情境認知、信任度與可靠度的品質特性目標函數，評估其對自動化操作系統績效的影響效果；接著，設計一核電廠飼水模擬系統環境，並以矩陣正交實驗設計法進行模擬實驗，以驗證該模型之適用性；最後，依照實驗的結果，構建模糊邏輯警戒度警報系統，以提升監控作業績效。經由第一次實驗之結果分析：以動態決策特性所建構之品質目標函數(□值)，可獲致最佳ASOP之控制因子水準組合；擁有正確的情境認知與決策閥，較易做出正確的決策與較佳的執行績效；這其中，適當的警戒度是一重要的關鍵。在第二次實驗之結果分析：應用□值構建模糊邏輯警戒度警報系統，確可有效提升操控績效。本研究之結果顯示品質目標函數可作為衡量ASOP的一種標準，及作為選擇最佳操作者的評價準則之一；結合品質目標函數及模糊控制技術應用於人機介面的設計，以改善認知決策與操控績效確實是一正確而重要的方向。

Automation system operating performance (ASOP) is a concept of how well an automation unit (AU) is monitored and performed by supervisors. The purpose of this research was to study and improve the ASOP for dynamic characteristics of human decision-making in automation. Previous researches have shown that situation awareness (SA) and trust are the important and influential factors of automation system performance. Firstly, a conceptual structure of relationship between SA and trust and a model of automated system performance with relation to SA, trust and automation reliability were developed. Secondly, a quantitative ASOP measuring model was proposed. Thirdly, a matrix experiment based on orthogonal arrays through a simulated system of Auxiliary Feed-Water System (AFWS) was conducted to verify the model specifically on ASOP. Finally, according to the results of the first experiment, a fuzzy logical vigilance performance alarm system was constructed to improve the operating performance. The first experimental results indicated that the quality-objective function (□ value) of human dynamic decision-making characteristics to measure the ASOP is easy and objective, a good situation awareness and correct decision-making calibration may have a greater likelihood of making appropriate decisions and performing well in automation, and keeping appropriated vigilance is an important focus. The second experimental results indicated that applying the □ value to design the fuzzy logical vigilance performance alarm system can improve the ASOP efficiently. The results of this study indicates that the quality-objective function could be regarded as measuring standard of ASOP and evaluating standard of selecting the adapted supervisors in automation. The function combined with fuzzy technique to design human-machine interface on improving cognitive decision and operating performance is a correct and important direction.

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