A reliability cost optimisation model for maintenance scheduling of wastewater treatment's power generation engines
Date
2021
Authors
Gorjian Jolfaei, N.
Jin, B.
Vanderlinden, L.
Gunawan, I.
Gorjian, N.
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Advisors
Journal Title
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Type:
Journal article
Citation
Quality and Reliability Engineering International, 2021; 38(1):2-17
Statement of Responsibility
Neda Gorjian Jolfaei, Bo Jin, Leon van der Linden, Indra Gunawan, Nima Gorjian
Conference Name
DOI
Abstract
Power generation engines in wastewater treatment plants (WWTPs) are critical and strategic assets as major elements of an effective energymanagement system. Therefore, water utilities seek a smart tool to optimise the maintenance program on overall cost and reliability of these assets. In the previous study, a reliability model with consideration of redundancy was developed to estimate failure modes, reliability and availability of power generation engines in a WWTP. This study examines a joint model of reliability index using the Weibull model, operating maintenance cost using the steepest descent method and quasi-Newton algorithm. This research is the first application of this joint model to power generation engines in WWTPs. A genetic algorithm has been employed to analyse and validate the modelling results as a global optimisation method. Results of the optimal solution are compared with conventional maintenance regimes of these engines based on recommended original equipmentmanufacturer (OEM). Results show an average of 22.3% reduction in maintenance costs of three engines after the implementation of the proposed cost-optimization model. In addition, the manufacturer’s recommended maintenance regime is not an appropriate maintenance strategy due to differences between the assumed and actual operating conditions. Also, hazard and reliability estimate using historical failure, operating and maintenance cost data has been ignored in the recommended OEM maintenance strategy.
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Dissertation Note
Provenance
Description
First published: 22 July 2021
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© 2021 John Wiley & Sons Ltd.