Multi-level optimization of maintenance plan for natural gas system exposed to deterioration process

Ahmad BahooToroody; Mohammad Mahdi Abaei; Ehsan Arzaghi; Farshad BahooToroody; Filippo De Carlo; Rouzbeh Abbassi

doi:10.1016/j.jhazmat.2018.09.044

Multi-level optimization of maintenance plan for natural gas system exposed to deterioration process

J Hazard Mater. 2019 Jan 15:362:412-423. doi: 10.1016/j.jhazmat.2018.09.044. Epub 2018 Sep 14.

Authors

Ahmad BahooToroody¹, Mohammad Mahdi Abaei², Ehsan Arzaghi³, Farshad BahooToroody⁴, Filippo De Carlo⁵, Rouzbeh Abbassi⁶

Affiliations

¹ Department of Industrial Engineering (DIEF), University of Florence, Florence, Italy.
² Renewable Energy Group, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn, Cornwall, TR10 9FE, UK.
³ National Centre for Maritime Engineering and Hydrodynamics, Australian Maritime College, University of Tasmania, Launceston, Tasmania, Australia.
⁴ Department of Civil Engineering, University of Parsian, Qazvin, Iran.
⁵ Department of Industrial Engineering (DIEF), University of Florence, Florence, Italy. Electronic address: filippo.decarlo@unifi.it.
⁶ School of Engineering, Macquarie University, Sydney, NSW, Australia.

PMID: 30261435
DOI: 10.1016/j.jhazmat.2018.09.044

Abstract

In this paper, a risk-based optimization methodology for a maintenance schedule considering Process Variables (PVs), is developed within the framework of asset integrity assessment. To this end, an integration of Dynamic Bayesian Network, Damage Modelling and sensitivity analysis are implemented to clarify the behaviour of failure probability, considering the exogenous undisciplinable perturbations. Discrete time case is considered through measuring or observing the PVs. Decision configurations and utility nodes are defined inside the network to represent maintenance activities and their associated costs. The regression analysis is considered to model the impact of perturbations on PVs for future applications. The developed methodology is applied to a case study of Chemical Plant (Natural Gas Regulating and Metering Stations). To demonstrate the applicability of the methodology, three cases of seasonal observations of specific PV (pressure) are considered. The proposed methodology could either analyse the failure based on precursor data of PVs or obtain the optimum maintenance schedule based on actual condition of the systems.

Keywords: Asset integrity assessment; Dynamic bayesian network; Influence diagram; Regression tools; Risk-based maintenance.