ESM is a Belgian provider of ships for the operation, transportation and transformation of gas, with fleets of ships in liquefied natural gas (LNG) and liquefied petroleum gas (LPG), along with a number of other vessels. It plans to use IOT to enable early maintenance work on machinery. According to Danielle Lammens, it will be used in monitoring the equipment for “machinery data” using vibration measurement, ultrasound measurement, infrared cameras and other systems to determine when exactly any repairs need to be carried out. 

 This approach brings several major advantages. Most importantly, it means that ESM will only need to dismantle a piece of equipment for repairs when absolutely necessary. Ship-based machinery must currently be dismantled after a certain time period. However, by using IOT techniques, ESM can determine if the item actually needs to be fixed; if not, there is no need to dismantle it. 

– This would allow us to postpone the overhaul if there is no risk and if approved by the appropriate classification society, says Lammens.

This brings major cost advantages, according to Lammens. For example, it costs about $150,000 for each overhaul of a high-pressure send-out pump, even if the equipment does not need to be fixed. If this could be done once every 60,000 running hours, rather than once every 20,000 running hours, ‘you can save a lot of money’. 

Additionally, dismantling a piece of equipment can increase the risk of failures with the machinery.

– The biggest problems are often after dismantling, not before it. The aim is to only open things when it is necessary, she said. 

Finally, gathering machinery data will allow ESM to better plan and schedule its activities, improving the safety of workers and the quality of the work.

– If you wait for a failure or a breakdown then it’s completely different.

ESM’s major focus is currently its LPG fleet. It plans to implement vibration monitoring on one of its LPG vessels in June, with the aim to gradually expand this across the remainder of the fleet of more than 30 vessels. The company has already installed vibration modelling and other measuring techniques on its LNG fleet, though there is a different maintenance strategy for these vessels, with varying priorities around cost and so on. 

The company is currently concentrating on machinery data: vibration monitoring and other parameters that can be measured on the machinery itself. However, it also aims to increase its focus on operational data: information on areas such as flow pressure and temperature.

The goal is to eventually combine the machinery and operational data to create a more predictive maintenance model, Lammens notes. 

– While ESM uses the data it already collects to provide a limited form of predictive maintenance, it still needs to be optimised, she said. This will only be possible when the two types of data are combined and may take a few years. 

Text: BEMAS - Belgian Maintenance Association