焦炭乾式淬火（Coke Dry Quenching , CDQ）系統是煉焦工場最重要之節能減碳技術，將熱焦炭淬火後產生的顯熱回收來產製電力或蒸汽，並同時降低焦碳濕式淬火所造成之汙染問題以及增加焦碳之性能。此系統循環風進入CDQ，在冷卻焦炭的過程中，帶走焦炭中部分的C，其與補入空氣中的氧燃燒，本研究的主要目的在於讓燒損的C完全燃燒，降低能源的浪費。
本研究利用數據建模的方式控制CDQ系統以提升蒸氣產量。首先，證實蒸氣產量與鍋爐進氣溫度間有高度相關性，接著以非線性變數選取方法分別建立鍋爐進氣溫度及循環氣體中一氧化碳成分之模型，以此達到模型預測控制(Model Predictive Control , MPC)，用於調整補空氣量以提升至最大蒸氣產量。研究結果，與原工廠操作比較，MPC操作確實能有效提升蒸氣產量達7%。本研究所提出的方法，藉由大量的操作數據建立預測模式，無需修改現有的系統，也不需要額外的設備投資，以投資回收的角度來看，本研究方法對於製程的改善相當顯著。

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