An overview of maintenance management strategies for corroded steel structures in extreme marine environments

Maintenance is playing an important role in integrity management of marine assets such as ship structures, offshore renewable energy platforms and subsea oil and gas facilities. The service life of marine assets is heavily influenced by the involvement of numerous material degradation processes (such as fatigue cracking, corrosion and pitting) as well as environmental stresses that vary with geographic locations and climatic factors. The composition of seawater constituents (e.g. dissolved oxygen, salinity, temperature content, etc.) is one of the major influencing factors in degradation of marine assets. Improving the efficiency and effectiveness of maintenance management strategies can have a significant impact on operational availability and reliability of marine assets. Many research studies have been conducted over the past few decades to predict the degradation behaviour of marine structures operating under different environmental conditions. The utilisation of structural degradation data – particularly on marine corrosion – can be very useful in developing a reliable, risk-free and cost-effective maintenance strategy. This paper presents an overview of the state-of-the-art and future trends in asset maintenance management strategies applied to corroded steel structures in extreme marine environments. The corrosion prediction models as well as industry best practices on maintenance of marine steel structures are extensively reviewed and analysed. Furthermore, some applications of advanced technologies such as computerized maintenance management system (CMMS), artificial intelligence (AI) and Bayesian network (BN) are discussed. Our review reveals that there are significant variations in corrosion behaviour of marine steel structures and their industrial maintenance practices from one climatic condition to another. This has been found to be largely attributed to variation in seawater composition/characteristics and their complex mutual relationships.