Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/98408
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Data-driven system reliability and failure behavior modelling using FMECA
Author: Khorshidi, H.
Gunawan, I.
Ibrahim, M.Y.
Citation: IEEE Transactions on Industrial Informatics, 2016; 12(3):1253-1260
Publisher: IEEE
Issue Date: 2016
ISSN: 1551-3203
1941-0050
Statement of
Responsibility: 
Hadi A. Khorshidi, Indra Gunawan, and M. Yousef Ibrahim
Abstract: System reliability modelling needs a large amount of data to estimate the parameters. In addition, reliability estimation is associated with uncertainty. This paper aims to propose a new method to evaluate the failure behavior and reliability of a large system using failure modes, effects and criticality analysis (FMECA). Therefore, qualitative data based on the judgment of experts is used when data is not sufficient. The subjective data of failure modes and causes has been aggregated through the system to develop an overall failure index (OFI). This index not only represents the system reliability behavior but also prioritizes corrective actions based on improvements in system failure. In addition, two optimization models are presented to select optimal actions subject to budget constraint. The associated costs of each corrective action are considered in risk evaluation. Finally, a case study of a manufacturing line is introduced to verify the applicability of the proposed method in industrial environments. The proposed method is compared with conventional FMECA approach. It is shown that the proposed method has a better performance in risk assessment. A sensitivity analysis is provided on the budget amount and the results are discussed.
Keywords: Failure modes, effects and criticality analysis; Qualitative data; Uncertainty; Reliability modelling; Universal generating function; Overall failure index; Genetic algorithm.
Rights: © 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
RMID: 0030042545
DOI: 10.1109/TII.2015.2431224
Appears in Collections:Entrepreneurship, Commercialisation, and Innovation Centre publications

Files in This Item:
File Description SizeFormat 
hdl_98408.pdfAccepted version197.18 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.