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Analysis of an industrial system under uncertain environment by using different types of fuzzy numbers

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  • Harish Garg

    (Thapar Institute of Engineering & Technology (Deemed University))

Abstract

Uncertainties play a dominant role in the performance analysis of the system. For managing it, fuzzy set theory and its corresponding triangular fuzzy numbers have been utilized by most of the researchers for quantifying the data. However, in this manuscript, this hypothesis has been calmed by defining the different types of numbers, namely gamma, normal, Cauchy and triangular for uncertainties. Based on it, behavior, performance and sensitivity analysis of the system have been investigated at different levels of confidence and the preferences as provided by the decision makers towards the data. Based on it, various expressions of the system such as failure rate, repair time, reliability, availability etc., are obtained corresponding to these different types of the numbers. From the computed results, it is concluded that these indices are reduced range of prediction as compared to the existing approaches. A numerical example has been taken for demonstrating the approach.

Suggested Citation

  • Harish Garg, 2018. "Analysis of an industrial system under uncertain environment by using different types of fuzzy numbers," 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 525-538, April.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:2:d:10.1007_s13198-018-0699-8
    DOI: 10.1007/s13198-018-0699-8
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    References listed on IDEAS

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    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.
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    Cited by:

    1. Adane Abebaw Gessesse & Rajashree Mishra & Mitali Madhumita Acharya & Kedar Nath Das, 2020. "Genetic algorithm based fuzzy programming approach for multi-objective linear fractional stochastic transportation problem involving four-parameter Burr distribution," 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(1), pages 93-109, February.
    2. Mingwei Lin & Chao Huang & Zeshui Xu, 2019. "TOPSIS Method Based on Correlation Coefficient and Entropy Measure for Linguistic Pythagorean Fuzzy Sets and Its Application to Multiple Attribute Decision Making," Complexity, Hindawi, vol. 2019, pages 1-16, October.
    3. Irfan Ali & Srikant Gupta & Aquil Ahmed, 2019. "Multi-objective linear fractional inventory problem under intuitionistic fuzzy environment," 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(2), pages 173-189, April.

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