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Fault diagnosis of automobile systems using fault tree based on digraph modeling

Author

Listed:
  • Ajith Tom James

    (Indian Institute of Technology Delhi)

  • O. P. Gandhi

    (Indian Institute of Technology Delhi)

  • S. G. Deshmukh

    (Indian Institute of Technology Delhi)

Abstract

Fault diagnosis of automobile systems is critical, as it adds-up to repair and maintenance time. It is, therefore, desired to make it efficient and effective. One of the conventional approaches is to use the fault tree diagram. But this approach is inadequate with its implicit system structure. Structure of the system means system elements and their interrelations. To alleviate this limitation, a new approach is suggested wherein the structure is in-built, i.e. incorporated explicitly, through digraph modeling that employs a systems approach of graph theory. A system digraph is developed, considering relationships among input and output parameters of subsystems/components of the automobile system in normal and failed conditions. Fault tree of a failure symptom that represents abnormality or a breakdown of the automobile system is obtained from the system digraph. The novelty is extension of the structural approach to automobile systems using digraph model, which has been successfully applied to chemical and process systems. Step-by-step methodology of the structural approach is presented. Its two main two steps are Steps 1 and 2, i.e. ‘Development of Fault tree diagram’ and ‘Diagnosis of fault using the tree diagram’, respectively. The suggested approach is illustrated for hydraulic power steering, an automobile system that is fitted on all current automobiles and particularly, in special purpose vehicles like heavy-duty trucks, earthmovers, dumpers, etc. The suggested approach guides how to diagnose root causes of a fault. The approach is not only helpful to maintenance personnel in effective diagnosis but also in guiding designers in development of reliable automobile systems, accident investigations of automobiles, etc.

Suggested Citation

  • Ajith Tom James & O. P. Gandhi & S. G. Deshmukh, 2018. "Fault diagnosis of automobile systems using fault tree based on digraph modeling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(2), pages 494-508, April.
  • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:2:d:10.1007_s13198-017-0693-6
    DOI: 10.1007/s13198-017-0693-6
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    References listed on IDEAS

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    1. E. M. Kelly & L. M. Bartlett, 2007. "Aircraft fuel rig system fault diagnostics based on the application of digraphs," Journal of Risk and Reliability, , vol. 221(4), pages 275-284, December.
    2. N. A. Snooke & C. J. Price, 2007. "Integrating reliability analysis and diagnostics for complex technical systems," Journal of Risk and Reliability, , vol. 221(2), pages 153-159, June.
    3. E. E. Hurdle & L. M. Bartlett & J. D. Andrews, 2007. "System fault diagnostics using fault tree analysis," Journal of Risk and Reliability, , vol. 221(1), pages 43-55, March.
    4. E M Kelly & L M Bartlett, 2008. "Enhanced diagnosis of faults using the digraph approach applied to a dynamic aircraft fuel system," Journal of Risk and Reliability, , vol. 222(4), pages 561-572, December.
    5. Bartlett, L.M. & Hurdle, E.E. & Kelly, E.M., 2009. "Integrated system fault diagnostics utilising digraph and fault tree-based approaches," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1107-1115.
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    Cited by:

    1. Zhiqiang Liu & Wenbo Zhu & Hongzhou Zhang & Shengjin Wang & Lu Fang & Weijun Hong & Hua Shao & Guopeng Wang, 2020. "Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network," International Journal of Distributed Sensor Networks, , vol. 16(3), pages 15501477209, March.
    2. Mohamed Alawadhi & Jumah Almazrouie & Mohammed Kamil & Khalil Abdelrazek Khalil, 0. "Review and analysis of the importance of autonomous vehicles liability: a systematic literature review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-23.
    3. Mohamed Alawadhi & Jumah Almazrouie & Mohammed Kamil & Khalil Abdelrazek Khalil, 2020. "Review and analysis of the importance of autonomous vehicles liability: a systematic literature review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1227-1249, December.
    4. Hamzeh Soltanali & Mehdi Khojastehpour & José Torres Farinha & José Edmundo de Almeida e Pais, 2021. "An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing," Energies, MDPI, vol. 14(22), pages 1-21, November.

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