Predictive operations have been rapidly adopted in the commercial sector, with successful use case showing significant improvements in industrial operations, saving millions of dollars per year as a result. The technology has now reached a high level of maturity and the defense sector is ready to leverage it, as evidenced by recent deployments.
An example: in August 2019 it was announced that the US Air Force had completed a successful Phase I evaluation of machine-learning technology using Falkonry’s LRS system. During this first phase, critical operational -ata problems were explored within the Air Force community, which led to STRATCOM’s Joint Warfare Analysis Center (JWAC) decision to go forward into Phase II of the project. This announcement was significant because it means JWAC is now able to analyze massive amounts of operational data and discover patterns at unprecedented scale, which enables real-time inferencing.
The Air Force and other military branches have many assets (think aircraft, vehicles, etc.) as well as multiple facilities and data centers that they monitor for security and efficiency. Leveraging predictive operations allows decision-makers to adopt a condition-based maintenance schedule. They can detect, predict and explain conditions preceding equipment failures, which can significantly reduce unexpected periods of downtime in a military environment, just as business owners do in the industrial space.
To learn more, read "From the factory to the battlefield" from Smart Industry.
