AI Case Study

US Army plans to test machine learning for predictive maintenance on combat vehicles

The US Army is testing the ability of machine learning to analyse data from combat vehicle sensors to proactively determine maintenance procedures and schedules.

Industry

Public And Social Sector

Security

Project Overview

The US Army has selected to Uptake Technologies to "employ artificial intelligence to flag failing vehicle parts before they break down in combat." Uptake Technologies has a $1 million contract agreement to test its technology "on a few dozen vehicles before they decide whether to scale it up for broader use. Uptake’s artificial intelligence will be applied to deployed Bradley M2A3 combat vehicles, an armored infantry transport vehicle manufactured by BAE Systems, a British defense contractor with a U.S. office in Arlington."

Reported Results

Planned; results not yet available. However: "Officials are taking a cautious approach at first. In the three years since its founding, Uptake has accumulated an impressive docket of industrial customers, including Boeing, Caterpillar and an undisclosed national trucking firm. But it is yet to be tested on military vehicles, leaving the Army in uncharted territory."

Technology

Function

Operations

Field Services

Background

The US Army has received "criticism in recent years for spending profligately on expensive new hardware such as the F-35 Joint Strike Fighter while older, more practical vehicles fall into disrepair". Additionally, "military leaders have been outspoken about the need to apply advanced artificial intelligence to the military’s operations, but efforts to forge partnerships with Silicon Valley tech firms have been fraught with difficulties."

Benefits

Data

Signals from from pre-existing sensors on the combat vehicles