Processing facilities in a marine environment may not remain safe and available if they are not well maintained. Dynamic risk-based maintenance (RBM) methodology is a tool for maintenance planning and decision making, used to enhance the safety and availability of the equipment. It also assists in identifying and prioritizing the maintenance of equipment based on the level of risk. This article discusses an advanced methodology for the design of an optimum maintenance program integrating a dynamic risk-based approach with a maintenance optimization technique. In this study, Bayesian Network (BN) is employed to develop a new dynamic RBM methodology that is capable of using accident precursor information in order to revise the risk profile. The use of this methodology is based on its failure prediction capability which optimizes the cost of maintenance. The developed methodology is applied to a case study involving a failure of a separator system in the offshore oil and gas production platform considering marine environments. The result shows it is essential that the valve system in the separator needs to be planned for maintenance once every 25 days; however, the cooler system can be planned for repairs once only biennially. A sensitivity analysis is also conducted to study the criticality of the operating system.
History
Publication title
Process Safety Progress
Volume
35
Issue
4
Pagination
399-406
ISSN
1547-5913
Department/School
Australian Maritime College
Publisher
John Wiley & Sons, Inc.
Place of publication
USA
Rights statement
Copyright 2016 American Institute of Chemical Engineers
Repository Status
Restricted
Socio-economic Objectives
Environmentally sustainable energy activities not elsewhere classified