SPN as a tool for risk modeling of fires in process industries

Grunt, Ondřej; Briš, Radim

doi:10.1016/j.jlp.2015.01.024

Cited by 15 publications

(5 citation statements)

References 18 publications

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Section: Methodsmentioning

confidence: 99%

“…Due to its versatility, this particular Petri module has been used in several fields of application, such as: safety instrumented systems, 31,45 oil and gas, 11,32,46 offshore wind turbines, [47][48][49][50] power systems, 51 process industries, 52 and controlled systems. 53 Petri nets can model a system and simulate its behavior by using the following three basic elements: places and transitions (nodes), which model conditions and events (e.g., fail) of a system, respectively; directed arcs, which connect places to transitions (input places); and transitions to places (output places), establishing relations between network nodes.…”

Section: Petri Netsmentioning

confidence: 99%

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Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

2018

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The paper addresses repairable multi-unit systems with a series–parallel configuration for which maintenance strategies are modeled by generalized stochastic Petri nets (GSPN) with predicates coupled with Monte Carlo simulation. Four maintenance strategies consisting of basic periodic preventive and corrective maintenance, and both combined with opportunistic maintenance (OM) strategies, are considered. Failure and repair distributions of the system components are independent, and repairs are considered to be perfect. Times to failure of degraded components follow a Weibull distribution with increasing failure rate over time. The maintenance strategies are optimized so as to minimize the total maintenance costs of the system while maximizing availability. A comparison is drawn between OM and non-OM. The aim is to show that GSPN with predicates, in combination with Monte Carlo simulation, is a powerful, flexible, efficient, and intuitive approach for modeling and optimizing practical maintenance strategies on multi-unit complex systems, modeling the dynamic behavior resulting from the interaction between system components and economic dependencies. The merits and advantages of GSPN coupled with Monte Carlo simulation are enhanced relative to other, analytical, approaches.

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Section: Methodsmentioning

confidence: 99%

Section: Petri Netsmentioning

confidence: 99%

Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

2018

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“…Hybrid Petri-net (HPN) extends the basic Petri-net to model continuous and discrete behaviors of a system [37]. Various types of Petri-nets have been used in process industries [38][39][40][41][42], also in the framework of emergency response planning [14,15], [43][44][45][46][47].…”

Section: Petri-net Based Modeling and Simulation Approachmentioning

confidence: 99%

A Petri-net approach for firefighting force allocation analysis of fire emergency response with backups

Zhou

Reniers

Cozzani

2023

Reliability Engineering & System Safety

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“…Pinto et al conclude the importance of Petri nets in maintenance management because it is beneficial for analyzing and simulating complex systems to increase asset function and operation reliability and availability [1]. Grunt and Briš suggest using an extension of Petri nets, i.e., Stochastic Petri Nets (SPNs), as a suitable modeling tool for time-dependent events such as fire escalation or gas cloud explosion [17]. Aloini et al used Colored Petri Nets (CPNs) to model risk factors in Enterprise Resource Planning (ERP) projects to deal with the problem of interdependence in risk assessment [18].…”

Section: Petri Netsmentioning

confidence: 99%

Stochastic versus Fuzzy Models—A Discussion Centered on the Reliability of an Electrical Power Supply System in a Large European Hospital

et al. 2022

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This paper discusses the Reliability, Availability, Maintainability, and Safety (RAMS) of an electrical power supply system in a large European hospital. The primary approach is based on fuzzy logic and Petri nets, using the CPNTools software to simulate and determine the most important modules of the system according to the Automatic Transfer Switch. Fuzzy Inference System is used to analyze and assess the reliability value. The stochastic versus fuzzy approach is also used to evaluate the reliability contribution of each system module. This case study aims to identify and analyze possible system failures and propose new solutions to improve the system reliability of the power supply system. The dynamic modeling is based on block diagrams and Petri nets and is evaluated via Markov chains, including a stochastic approach linked to the previous analysis. This holistic approach adds value to this type of research question. A new electrical power supply system design is proposed to increase the system’s reliability based on the results achieved.

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SPN as a tool for risk modeling of fires in process industries

Cited by 15 publications

References 18 publications

Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

A Petri-net approach for firefighting force allocation analysis of fire emergency response with backups

Stochastic versus Fuzzy Models—A Discussion Centered on the Reliability of an Electrical Power Supply System in a Large European Hospital

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