The US Navy has announced a new US$5m (£3.8m) contract, which will see it deploy robotics across several sites to inspect ships for damage and gather data to build digital models of vessels.
This data will accordingly be fed back to a software platform enabled by artificial intelligence (AI).
Overall, the robots are expected to increase the speed and quality of maintenance processes for US Navy surface ships, including amphibious assault ships.
Data collected will be used to create structured data sets to support the organisation’s move towards more predictive maintenance planning in the future.
In March this year, the US navy deployed a hull-scaling robot for the first time on an amphibious assault ship, as well as an additional Arleigh Burke Class destroyer.
According to the US Government’s Accountability Office, the Department of Defense spends US$90bn (£68.6bn) a year on ensuring that ground systems, ships, aircraft and other associated infrastructure is combat-ready through scheduled maintenance or repair work when needed.
However, in December 2022, it published a report that recommended the US Navy introduce predictive maintenance practices; the solutions deployed through the new contract are designed to help implement predictive processes across certain US Navy operations.
The contract is with shipbuilding company Huntington Ingalls Industries and Gecko Robotics, which will supply the AI platform for data collection and analysis.
Navy data suggests that using robotic assessment technologies and AI-driven data collection reduces lead time and work hours associated with maintenance cycles, while also increasing the availability of data and finding defects missed through traditional methods.
What’s more, for one Navy asset, traditional methods captured 100 data points while the AI platform reportedly captured more than 4.2 million.