A method to prevent excessive numbers of Markov states in Markov models for quantitative safety and reliability assessment

Knegtering, B.; Brombacher, Aarnout

doi:10.1016/s0019-0578(99)00041-5

Cited by 17 publications

(5 citation statements)

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“…However, certain limitations and difficulties are encountered while using the Markov approach, such as network explosion, even when dealing with a small unit. These difficulties can be effectively addressed through the Petri nets modelling technique or by applying the method for reducing the excessive number of states proposed by Knegtering and Brombacher [24].…”

Section: Discussionmentioning

confidence: 99%

Stochastic Approach in Performance Modelling of a Repairable Industrial System

2024

IJEM

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This paper aims to present a quantitative investigation of a case study based on a live industrial refrigeration system exhibiting complex and dynamic behaviour such as randomness, concurrency, and time dependency. The study employs a state-space stochastic Markovian process to model the interactions among the key functional elements of the system. Furthermore, the scientific approach pursued in this study would help improve the availability of the considered plant by establishing a trade-off between investment, economy and quality. Based on the analysis of results, a framework for Decision Support Priorities (DSP) is proposed, emphasizing the criticality of various functional units. This framework could also help set and prioritize maintenance, spare parts, and human resource requirements accordingly.

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Section: Discussionmentioning

confidence: 99%

Stochastic Approach in Performance Modelling of a Repairable Industrial System

2024

IJEM

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“…However, it is very difficult to build and handle large Markov models and is very susceptible to modeling errors and solving will be a time-consuming task. To prevent excessive numbers of Markov states in Markov models, splitting up a full Markov model into "Micro" Markov models could dramatically reduce the model states and calculation efforts [12].…”

Section: Discussion and Recommendationsmentioning

confidence: 99%

Special Protection System Reliability Assessment

Hsiao

2007

2007 IEEE/IAS Industrial &Amp; Commercial Power Systems Technical Conference

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Special protection systems (SPS) are sometimes perceived by the electric power industry as attractive alternatives to constructing new transmission facilities for maintaining system stability and security. One of the main concerns in the design of SPS is to assure whether the system could fit with the reliability requirements specification. Currently, there are only a few literatures that discuss the SPS reliability assessment. In one study conducted by the authors, some reliability evaluation techniques, including, reliability block diagram method, fault tree analysis, Markov modeling and Monte Carlo simulations, are applied to assess the probability that the decision process fails to respond as designed in an actual event-based SPS implemented by Taiwan Power Company (Taipower). Experiences acquired from using these methods for SPS reliability assessment and some recommendations are given in this paper.

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“…Dedicated instrumentation, which also makes process control more and more complex, is expected to control and safeguard these processes. As a consequence of the growing complexity of the process installations, the control instrumentation, and safeguarding instrumentation, safety-related business processes have become even more difficult to manage [10,11].…”

Section: Root Cause Of Accidentsmentioning

confidence: 99%

Practical Implementation of Safety Verification in LNG Production Facilities

Rastogi¹

2011

OJSST

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Many energy and production facilities are operating without clear formal safety requirements, which are con- sidered the base for good process safety management practices. Safety requirements are typically specified during process design based on identified hazard scenarios. This paper proposes a practical framework and methods to systematically synthesize safety requirements based on qualitative and quantitative fault and hazard scenarios. Our aim will be to design a proper safety verification framework which would provide some guidelines regarding the sequence of steps to be taken in the plant for the verification of the safety of that plant. The objective of this paper is to show how the safety verification techniques meet the safety requirements of any production plant. We will clarify Safety Life Cycle and the detailed steps for safety design and verification and also analyze current practices and challenges of safety verification in instrumented/non-in- strumented systems. We will also develop possible activity model for safety verification process and will propose safety requirements representation that will facilitate safety verification. Case study of experimental setup is used to demonstrate the proposed framework, which will support safety design and verification

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A method to prevent excessive numbers of Markov states in Markov models for quantitative safety and reliability assessment

Cited by 17 publications

References 1 publication

Stochastic Approach in Performance Modelling of a Repairable Industrial System

Stochastic Approach in Performance Modelling of a Repairable Industrial System

Special Protection System Reliability Assessment

Practical Implementation of Safety Verification in LNG Production Facilities

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