Abstract: System dynamic reliability for manufacturing system is investigated based on stochastic failure sequence(SFS) analysis, Petri nets theory and Monte Carlo simulation. The definitions of SFS, importance of sequence, and key components of system are given out. The analysis procedure for SFS is discussed. Analysis model for system reliability is established based on Petri nets theory, the state identification table of the system is built and the reachability tree is created, and all SFSs of the system can be obtained. System’s failure states can be determined with the method of minimal path sets, and the method for avoiding components’ excessive failure during simulation is also considered. Monte Carlo simulation is used to compute the occurrence of all the failure sequences and system dynamic reliability. By means of calculating the number of times, frequency, and time of duration of each failure sequence, we can get the key components and bottleneck parts which influence system reliability, it provides theoretical basis for system reliability growth. A case study for an oil supply system is presented, the simulation results demonstrate the validity and effectiveness of the proposed method.

Key words: Dynamic reliability, Failure sequence, Minimal path set, Petri nets, Simulation, CFD method, Combined analytic-CFD method, Engineering analytic method, Externally pressurized gas journal bearing, Orifice compensation