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RAM assessment of the repairable industrial structure with genuine human-mistake working conditions with generalized fuzzy numbers

Pooja Dhiman (Department of Mathematics, Faculty of Technology and Sciences, Lovely Professional University, Phagwara, India)
Amit Kumar (Department of Mathematics, Faculty of Technology and Sciences, Lovely Professional University, Phagwara, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 15 December 2020

Issue publication date: 16 July 2021

112

Abstract

Purpose

The present paper investigated a skim milk powder production plant with genuine human mistake for analyzing its performance in terms of its reliability, availability and maintainability (RAM) indices along with mean time between failure (MTBF) and expected number of failure (ENOF).

Design/methodology/approach

In the proposed work, the generalized fuzzy lambda–tau methodology has been used to carry out the analysis of the repairable structure using the improved arithmetic operations for generalized fuzzy numbers by considering the degree of confidence levels.

Findings

RAM indices along with MTBF and ENOF are obtained to increase the quality of skim milk powder manufacturing structures of a dairy plant with genuine human-mistake working conditions.

Originality/value

In the present paper, a mathematical model for a complex industrial system based on fuzzy has been developed. Finally, the results are more realistic and comprehensive for the decision-maker for farther application.

Keywords

Acknowledgements

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Citation

Dhiman, P. and Kumar, A. (2021), "RAM assessment of the repairable industrial structure with genuine human-mistake working conditions with generalized fuzzy numbers", International Journal of Quality & Reliability Management, Vol. 38 No. 7, pp. 1614-1627. https://doi.org/10.1108/IJQRM-12-2019-0370

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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