%0 Journal Article
%@ 10668527
%A Ahsan, S.
%A Lemma, T.A.
%A Gebremariam, M.A.
%D 2020
%F scholars:13434
%I John Wiley and Sons Inc.
%J Process Safety Progress
%K Availability; Failure (mechanical); Failure analysis; Gas turbines; Least squares approximations; Marine applications; Marine engineering; Maximum likelihood estimation; Mean square error; Outages; Parameter estimation; Reliability; Weibull distribution, Bathtub shaped failure rate; Least square methods; Maintenance intervals; Operational reliability; Reliability approach; Root mean square errors; Three parameter Weibull distribution; Time between failures, Reliability analysis
%N S1
%R 10.1002/prs.12115
%T Reliability analysis of gas turbine engine by means of bathtub-shaped failure rate distribution
%U https://khub.utp.edu.my/scholars/13434/
%V 39
%X During reliability analysis, analysts often encounter multiple repairable units operating in different environments for various applications such as marine, power generation, and propulsion. Thus, a reliability approach that accounts for varying operating conditions is invaluable to ensure system availability. Therefore, fault probability described by some characteristic parameters and their accurate estimation has been a vital task for understanding system's behavior. The time between failures is utilized to estimate Weibull parameters that define the system. The application of gas turbine is presented as a case study. Five different cases are discussed based on distinct operating conditions and faults. The results obtained demonstrate the effectiveness of the proposed method for assessing operational reliability. The three-parameter Weibull distribution was found to best fit the failure data with the root mean square error between 0.0369 and 0.0688 for maximum likelihood estimation and 0.04184 and 0.0733 for the least square method. Based on these results, it is deduced that the system under consideration is at the end of its operational life. Furthermore, it is observed that an increase in maintenance interval leads to a decline in meantime to failure, which is indicative of the need to select maintenance interval wisely. Findings from this study helps to improve the understanding of gas turbine behavior based on reliability and survival analysis. © 2019 American Institute of Chemical Engineers
%Z cited By 15