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Stochastic behaviour analysis of real industrial system

Author

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  • Dilbagh Panchal

    (Amity University)

  • Dinesh Kumar

    (Indian Institute of Technology Roorkee)

Abstract

This research work seeks to propose qualitative and quantitative approaches based integrated framework for studying the behavior of a real industrial system. Under quantitative analysis, the series/parallel arrangement of the considered system is represented by Petri-Net approach. Various reliability parameters of the system were computed at different spread and the system failure behavior is studied under uncertainty. Further, for improving system’s availability, qualitative analysis has been done using root cause analysis (RCA) approach and the failure causes listed under RCA approach were used to carry system’s failure mode effect analysis (FMEA). The limitations of FMEA in risk ranking were nullified by using fuzzy FMEA and grey relation analysis approaches and the raking results so obtained were compared with FMEA approach based results. The comparison of ranking results would be of high importance for the analyst in deciding the critical/risky component of the considered system with high accuracy. The analysis results were further shared with the maintenance manager of the plant for planning and implementing a suitable maintenance policy accordingly. The planned maintenance policy will help in improving the plant’s availability and profitability. The proposed framework has been implemented to carry out the quantitative and qualitative behavioral analysis of a coal handling system in a coal fired thermal power plant located in North India.

Suggested Citation

  • Dilbagh Panchal & Dinesh Kumar, 2017. "Stochastic behaviour analysis of real industrial system," 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. 8(2), pages 1126-1142, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0579-7
    DOI: 10.1007/s13198-017-0579-7
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    References listed on IDEAS

    as
    1. S.P. Sharma & Harish Garg, 2011. "Behavioural analysis of urea decomposition system in a fertiliser plant," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 8(3), pages 271-297.
    2. Wang, Ling & Chu, Jian & Wu, Jun, 2007. "Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 107(1), pages 151-163, May.
    3. Dilbagh Panchal & Dinesh Kumar, 2017. "Risk analysis of compressor house unit in thermal power plant using integrated fuzzy FMEA and GRA approach," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 25(2), pages 228-250.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    2. J. Wakiru & P. N. Muchiri & L. Pintelon & P. Chemweno, 2019. "A cost-based failure prioritization approach for selecting maintenance strategies for thermal power plants: a case study context of developing countries," 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. 10(5), pages 1369-1387, October.
    3. Nitin Panwar & Sanjeev Kumar, 2022. "Mathematical modelling and performance analysis of screening unit in paper plant," 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. 13(5), pages 2751-2763, October.

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