在自動化批次製程的操作過程中，不免會發生硬體設備的故障，若無法利用既有線上測量數據，有效率地即時偵測到並診斷出失誤根源，則可能會造成嚴重的災害。本研究根據離散事件系統(discrete event system)理論發展出執行額外測試步驟的策略，以提升診斷效能。具體言之，我們藉由系統化方法建造出自動機模型來表示製程中所有元件和控制規範，即可據以自動搜尋出最適的診斷測試步驟。最後，我們也計畫進行一系列實際案例研究，來驗證提出方法的可行性。

Hardware failures are inevitable random events in operating any batch chemical plant. If fault origins are not diagnosed efficiently and accurately with online sensors, the subsequent consequences may be catastrophic. In order to enhance diagnostic performance, a novel approach is proposed in this study to synthesize test procedures on the basis of discrete-event system (DES) theory. In particular, all components in the given system and the required control specifications are first modeled systematically with automata and, then, an optimal operating procedure can be identified accordingly to differentiate the fault origins as much as possible. Finally, a series of realistic case studies are planned to confirm the validity and effectiveness of this proposed approach.

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