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How To Reduce Unplanned Downtime with Predictive Maintenance

In the marine industry, system downtime can be detrimental often requiring timely and costly repairs that drastically increase overall operating expenses.

Just 2 per cent of the shipping industry has fully adopted condition based maintenance strategies despite the cost and reliability benefits it brings. Condition based maintenance entails the development of a maintenance strategy based on the monitoring of key equipment and systems on ships. If it is done correctly, ship operators and managers can achieve cost efficiencies and increased vessel uptime, and reduce the risk of system failures.

Many smart ship owners have reduced costs and downtime by introducing condition maintenance – monitoring energy consumption and predicting failures before they happen. Installing a £15,000 (US$21,600) condition monitoring system could save a company 10 times that amount. A lube oil pump failure could cost £57,000 to repair, but this could take three days, leading to off-hire losses of £90,000 and other costs such as management time and increased insurance premiums.

Despite this, few shipowners are willing to invest in a condition based monitoring programme, which would involve the installation of sensors, the deployment of suitable software and the retraining of onshore managers and crew.

There is, however, a solution:

Moving from planned to conditional based maintenance

An analytics platform from Icon Research can predict the future condition of a vessel’s assets. It allows companies to monitor vessels in real-time, record and analyse their histories and search for anomalies. It can give early warnings when an asset is exhibiting an off standard behaviour, identifying potential problems before they occur. Therefore ship operators can take action weeks, or even months before a potential failure. This enables them to switch from planned to conditional-based maintenance, reducing downtime and creating potentially significant costs savings.

Switch to Condition based rather than Calendar based

In shipping, maintenance is more calendar-based and much less condition-based. But we can use software and analytics to do condition-based maintenance – there are real applications to reduce maintenance costs. With Icon Research products you can target any potential vessel disruption, identify, and then fix problems when this disruption occurs using our marine digital solution. This would be applicable on cruise ships and ferries, tankers, container ships and bulk carriers, drillships and FPSOs.

Remote monitoring and diagnostics can also alleviate the skills shortages at sea by placing the offshore and maritime expertise on shore, with technical superintendents managing a fleet of ships.

Optimising fuel efficiency for transport vessels

Fuel efficiency is crucial for Liquid Natural Gas Carriers (LNGC), containers and cruise vessels, as in some cases fuel costs account for up to 30-50% of total operational expenses. Predictive analytics tools can provide, for example, the ability to forecast weather conditions to inform optimum propulsion levels, therefore reducing fuel consumption. The ability to predict faults before they occur also help to defer maintenance time.

In conclusion, condition based monitoring should prevent unnecessary refits and overhauls. A planned maintenance system may call for maintenance on a piece of equipment, but the condition based monitoring would recommend leaving it alone.

The aim is to find the right time to conduct maintenance by gaining prior warning from the equipment before failure occurs. Condition based monitoring can improve reliability. For example, bearing wear can be reduced. With condition based maintenance you can predict what problems are coming, improve performance and minimise downtime.

To make the system most effective companies need to address the three biggest challenges to structure the condition based maintenance methodology, the analysis, and creating a culture so that people can understand the link between condition based maintenance and remote diagnostics and system management.