2011International Journal of Reliability Quality and Safety EngineeringRequires access

SAFETY ASSESSMENT FOR SAFETY-CRITICAL SYSTEMS USING MARKOV CHAIN MODULAR APPROACH

Yangyang Yu, B.W. Johnson

Open publisher page 6 citations

Abstract

The Markov Chain Modular (MCM) approach is proposed in this paper in order to solve part of the failure-state dependency problem. The MCM approach completely avoids the failure-state dependency problem by avoiding the combinatorial modeling. To quantitatively assess safety, a new Markov chain modeling technique is developed to represent an m + 2 state homogenous Markov chain model using a three-state Markov model. The transition rate functions of the three-state Markov model can be determined by the transition rates of the m + 2 state Markov chain model. Given a series system has N modules and each module has O(m) operational states, the MCM approach reduces the operational states to O(N × m2) as opposed to O(m2N) by using the traditional Markov chain model.

About this research paper

What this paper is about

The Markov Chain Modular (MCM) approach is proposed in this paper in order to solve part of the failure-state dependency problem. The MCM approach completely avoids the failure-state dependency problem by avoiding the combinatorial modeling. To quantitatively assess safety, a new Markov chain modeling technique is developed to represent an m + 2 state homogenous Markov chain model using a three-state Markov model. The transition rate functions of the three-state Markov model can be determined by the transition rates of the m + 2 state Markov chain model. Given a series system has N modules and each module has O(m) operational states, the MCM approach reduces the operational states to O(N × m2) as opposed to O(m2N) by using the traditional Markov chain model.

Why it matters

OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The Markov Chain Modular (MCM) approach is proposed in this paper in order to solve part of the failure-state dependency problem. The MCM approach completely avoids the failure-state dependency problem by avoiding the combinatorial modeling. To quantitatively assess safety, a new Markov chain modeling technique is developed to represent an m + 2 state homogenous Markov chain model using a three-state Markov model. The transition rate functions of the three-state Markov model can be determined by the transition rates of the m + 2 state Markov chain model. Given a series system has N modules and each module has O(m) operational states, the MCM approach reduces the operational states to O(N × m2) as opposed to O(m2N) by using the traditional Markov chain model.

Key concepts: Markov chain, Markov model, Dependency (UML), Computer science, Modular design, Additive Markov chain, Variable-order Markov model, Markov process

Related papers

Back to paper searchBrowse research topicsOriginal source
SAFETY ASSESSMENT FOR SAFETY-CRITICAL SYSTEMS USING MARKOV CHAIN MODULAR APPROACH — Research Paper | ScholarLens