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Prediction of the Behavior of a Power System Using Root Cause Failure Analysis

Seyed Mohammad Seyed Hosseini*, Kamran Shahanaghi, Safar Shasfand

Iran University of Science and Technology, Tehran, 1684613114, Iran

* Corresponding Author: Seyed Mohammad Seyed Hosseini. Email: email

(This article belongs to the Special Issue: Advances in Fluid Flow and Smart Materials)

Fluid Dynamics & Materials Processing 2022, 18(3), 815-833. https://doi.org/10.32604/fdmp.2022.019626

Abstract

The thermo-economic performance of a gas turbine is simulated using a fish bone technique to characterize the major equipment failure causes. Moreover a fault tree analysis and a Pareto technique are implemented to identify the related failure modes, and the percentage and frequency of failures, respectively. A pump 101 and drier 301 belonging to the Tabriz Petrochemical Company are considered for such analysis, which is complemented with a regression method to determine a behavioral model of this equipment over a twenty-year period. Research findings indicate that 81% of major failure factors in production equipment are related to the executive procedures (24%), human error (22%), poor quality of materials and parts (20%), and lack of personnel training (15%).


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APA Style
Hosseini, S.M.S., Shahanaghi, K., Shasfand, S. (2022). Prediction of the behavior of a power system using root cause failure analysis. Fluid Dynamics & Materials Processing, 18(3), 815-833. https://doi.org/10.32604/fdmp.2022.019626
Vancouver Style
Hosseini SMS, Shahanaghi K, Shasfand S. Prediction of the behavior of a power system using root cause failure analysis. Fluid Dyn Mater Proc. 2022;18(3):815-833 https://doi.org/10.32604/fdmp.2022.019626
IEEE Style
S.M.S. Hosseini, K. Shahanaghi, and S. Shasfand "Prediction of the Behavior of a Power System Using Root Cause Failure Analysis," Fluid Dyn. Mater. Proc., vol. 18, no. 3, pp. 815-833. 2022. https://doi.org/10.32604/fdmp.2022.019626



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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