Fault Troubleshooting Using Bayesian Network and Multicriteria Decision Analysis

Yingping Huang, Yusha Wang, Renjie Zhang

    Research output: Contribution to journalArticle

    7 Citations (Scopus)
    92 Downloads (Pure)


    Fault troubleshooting aims to diagnose and repair faults at the highest efficacy and a minimum cost. The efficacy depends on multiple criteria like fault probability, cost, time, and risk of a repair action. This paper proposes a novel fault troubleshooting approach by combining Bayesian network withmulticriteria decision analysis (MCDA). Automobile engine start-up failure is used as a case study. Bayesian network is employed to establish fault diagnostic model for reasoning and calculating standard values of uncertain criteria like fault probability.MCDA is adopted to integrate the influence of the four criteria and calculate utility value of the actions in each troubleshooting step. The approach enables a cost-saving, high efficient, and low risky troubleshooting.
    Original languageEnglish
    Article number282013
    JournalAdvances in Mechanical Engineering
    Issue numberArticle ID 282013
    Publication statusPublished - 2014

    Bibliographical note

    This is an open access article distributed under the Creative Commons Attribution
    License. The full text is available at: http://dx.doi.org/10.1155/2014/282013


    • fault troubleshooting


    Dive into the research topics of 'Fault Troubleshooting Using Bayesian Network and Multicriteria Decision Analysis'. Together they form a unique fingerprint.

    Cite this