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A robust system reliability analysis using partitioning and parallel processing of Markov chain

Published online by Cambridge University Press:  30 September 2014

Po Ting Lin ,
Yu-Cheng Chou ,
Yung Ting ,
Shian-Shing Shyu  and
Chang-Kuo Chen
Po Ting Lin
Affiliation:
Department of Mechanical Engineering, Research and Development Center for Microsystem Reliability, Center for Biomedical Technology, Chung Yuan Christian University, Chungli City, Taiwan
Yu-Cheng Chou*
Affiliation:
Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung City, Taiwan
Yung Ting
Affiliation:
Department of Mechanical Engineering, Chung Yuan Christian University, Chungli City, Taiwan
Shian-Shing Shyu
Affiliation:
Institute of Nuclear Energy Research, Atomic Energy Council, Chungli City, Taiwan
Chang-Kuo Chen
Affiliation:
Institute of Nuclear Energy Research, Atomic Energy Council, Chungli City, Taiwan
*
Reprint requests to: Yu-Cheng Chou, Institute of Undersea Technology, National Sun Yat-sen University, 70 Lienhai Road, Kaohsiung City 80424, Taiwan. E-mail: ycchou@mail.nsysu.edu.tw
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Abstract

This paper presents a robust reliability analysis method for systems of multimodular redundant (MMR) controllers using the method of partitioning and parallel processing of a Markov chain (PPMC). A Markov chain is formulated to represent the N distinct states of the MMR controllers. Such a Markov chain has N2 directed edges, and each edge corresponds to a transition probability between a pair of start and end states. Because N can be easily increased substantially, the system reliability analysis may require large computational resources, such as the central processing unit usage and memory occupation. By the PPMC, a Markov chain's transition probability matrix can be partitioned and reordered, such that the system reliability can be evaluated through only the diagonal submatrices of the transition probability matrix. In addition, calculations regarding the submatrices are independent of each other and thus can be conducted in parallel to assure the efficiency. The simulation results show that, compared with the sequential method applied to an intact Markov chain, the proposed PPMC can improve the performance and produce allowable accuracy for the reliability analysis on large-scale systems of MMR controllers.

Keywords

Fault ToleranceMarkov ChainM-PartitioningParallel ProcessingReliability Analysis

Information

Type
Special Issue Articles
Information
AI EDAM , Volume 28 , Issue 4: Design of Complex Engineered Systems , November 2014 , pp. 311 - 322
Copyright
Copyright © Cambridge University Press 2014 

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