一個典型的鋼鐵廠鍋爐所使用之燃料有許多種，如COG
(煉焦爐氣)、BFG(高爐氣和轉爐氣混合而成)、天然氣、LSO(低硫油)、煤等。其中BFG為高爐氣和轉爐氣混合而成，而混合比例每個時間不一樣，因此BFG熱值隨時間一直在變動，鋼鐵廠鍋爐之效率不容易控制，在本研究中，利用統計方法研究影響鍋爐效率之重要變數。針對部分數據作stepwise regression尋找重要變數，在利用複迴歸得到鍋爐效率之模型，而模型對鍋爐效率之評估利用Kalman filter理論減少估計的誤差，最後再建立一個虛擬工廠，證實能夠提升燃料混燒鍋爐之熱效率。

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