A petri-net based reasoning procedure for fault identification in sequential operations

In implementing any hazard analysis method, there is a need to reason deductively for identifying all possible fault origins that could lead to an undesirable consequence. Due to the complex time-variant cause-and-effect relations between events and states in sequential operations, the manual deduction process is always labor intensive and often error-prone. The theme of the present study is thus concerned mainly with the development of Petri-net based reasoning algorithms for automating such cause-finding procedures. The effectiveness and correctness of this approach are demonstrated with a realistic example in this paper.