eCite Digital Repository

Availability analysis of safety critical systems using advanced fault tree and stochastic Petri net formalisms


Talebberrouane, M and Khan, FI and Lounis, Z, Availability analysis of safety critical systems using advanced fault tree and stochastic Petri net formalisms, Journal of Loss Prevention in the Process Industries, 44 pp. 193-203. ISSN 0950-4230 (2016) [Refereed Article]

Copyright Statement

2016 Elsevier Ltd. All rights reserved.

DOI: doi:10.1016/j.jlp.2016.09.007


Failure scenarios analysis constitutes one of the cornerstones of risk assessment and availability analysis. After a detailed review of available methods, this paper identified two distinct formalisms to analyze failure scenarios and systems availability: generalized stochastic Petri nets (GSPN) and Fault tree driven Markov processes (FTDMP). The FTDMP formalism is a combination of the Markov process and the fault tree. This aims to overcome fault tree limitations while maintaining the use of deductive logic. The GSPN is a Petri net with probabilistic analysis using Monte Carlo simulation. The effectiveness of both methods is studied through an emergency flare system including a knockout drum. It is observed that GSPN provides a robust and reliable mechanism for accident scenario analysis. It provides additional information such as events frequencies at operating and failing modes and expected occurrence timing and durations resulting from different complex sequences. Even for multi-state variables which could be used to design a safety management system. Although FTDMP is a powerful formalism, it provides limited information.

Item Details

Item Type:Refereed Article
Keywords:fault tree, Monte Carlo simulation, multi-phase Markov model, safety analysis, stochastic petri nets, availability, intelligent systems, Markov processes, Monte Carlo methods, petri nets, preventive maintenance, random access storage, fault-trees
Research Division:Engineering
Research Group:Engineering practice and education
Research Field:Risk engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, FI (Professor Faisal Khan)
ID Code:120362
Year Published:2016
Web of Science® Times Cited:41
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-23
Last Modified:2017-11-06

Repository Staff Only: item control page