一般而言，若與常見的連續製程比較，批次製程中的非穩態操作步驟較為複雜，造成操作過程中意外事故產生的機率相對提高，因此失誤診斷也會較為困難。本論文將以批次製程為對象，採用派屈網模型來表示考慮時間的失誤傳播機制，並據以改善文獻中已存在之診斷器建構步驟，具體言之本論文中提出了過去研究缺乏的感測器故障模式，且發展出新的診斷效能提昇策略 (包括計時器及額外驅動設備的設置方法)，以便達到可以分辨多重失誤情境的目標。

Due to the inherent complexity of unsteady-state operations, the probabilities of accidents in batch processes are high and the corresponding diagnosis tasks are quite difficult. In this work, the standard untimed Petri nets are used to model the dynamic fault propagation mechanisms for batch operations over a finite time horizon and, also, to improve the existing procedure for dianoser construction. Specifically, the following new features are developed in this research to enhance the diagnoser performance during multi-failure scenarios:
1. A generalized Petri net has been proposed to characterize sensors and their failures;
2. Several revamp strategies have been proposed to upgrade any given system by incorporating emergency steps in SFC, and by introducing additional timers, sensors and actuation devices into the P&ID.

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