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System Failure Analysis Through Counters of Petri Net Models
Author(s) -
Adamyan Angela,
He David
Publication year - 2004
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.545
Subject(s) - petri net , fault tree analysis , reachability , computer science , stochastic petri net , process architecture , reliability engineering , failure rate , reliability (semiconductor) , fault (geology) , flexibility (engineering) , petri dish , tree (set theory) , distributed computing , algorithm , engineering , mathematics , mathematical analysis , power (physics) , statistics , physics , biology , genetics , geology , quantum mechanics , seismology
Petri nets are a powerful technique widely used in the modeling and analysis of complex manufacturing systems and processes. Due to their capability in modeling the dynamics of the systems, Petri nets have been combined with fault tree analysis techniques to determine the average rate of occurrence of system failures. Current methods in combining Petri nets with fault trees for system failure analysis compute the average rate of occurrence of system failures by tracking the markings of the Petri net models. The limitations of these methods are that tracking the markings of a Petri net represented by a reachability tree can be very complicated as the size of the system grows. Therefore, these methods offer less flexibility in analyzing sequential failures in the system. To overcome the limitations of the current methods in applying Petri nets for system failure assessment, this paper expands and extends the concept of counters used in Petri net simulation to perform the failure and reliability analysis of complex systems. The presented method allows the system failures to be modeled using general Petri nets with inhibitor arcs and loops, which employs fewer variables than existing marking‐based methods and substantially accelerates the computations. It can be applied to real system failure analysis where basic events can have different failure rates. Copyright © 2003 John Wiley & Sons, Ltd.