Machine Prognostics digitalises the ship machinery inspection process, providing real-time updates on asset health, and presenting actionable data in a user-friendly interface.
Similar to the automotive industry, where private owners of vehicles perform yearly maintenance inspection and oil changes, the vast majority – 98 per cent – of vessels and offshore platforms implement time-based maintenance (TBM) strategies. TBM consists of periodic machinery inspection and periodic replacement of parts, regardless of their actual condition.
These practices generate significant direct and indirect environmental costs in the form of considerable crew time dedicated to machinery inspection, wasteful replacement and discarding of still-functional parts, and unnecessary storage of spare parts.
Using highly accurate algorithms embedded in sensors, Machine Prognostics’ solution digitalises the ship machinery inspection process.
The sensors are simply bolted onto the asset, making the solution easy to retrofit. A single cable powers and transmits data from up to 50 sensors. The raw data is digitised and compressed to a few kilobytes for transmission to shore via a ship’s satellite communication system.
The data is collected autonomously and interpreted without human interaction, so no training or data analysis skills are needed to understand the data.
In addition, the solution is interoperable with ship maintenance planning software.
Machine Prognostics’ solution removes the guesswork from machine diagnostics by estimating the asset’s remaining useful life before maintenance and makes this data available in real-time to everyone in a user-friendly format.
The solution helps to cut physical inspection costs and lower costs related to the unnecessary replacement and storage of spare parts. In addition, by extending the lifetime of the asset, it can reduce resource use and related environmental impacts.
Machine Prognostics’ target market is the global maritime industry, specifically the vessels and offshore platforms segments.
The vessels segment is huge, with some 88 050 classed vessels over 25 years old in addition to some 64 000 motorised fishing vessels over 24 m in length. Meanwhile, there are 1 332 offshore platforms worldwide. Thus, Machine Prognostics’ technology has applicability for over 150 000 floating assets and can be used on a multitude of machinery.
Real-time diagnostic data shows machinery’s state of health
Reduces crew time used on machinery inspection
Prevents wasteful replacement of still-functional parts