  Cross-border security is of topmost priority for societies. Economies lose
billions each year due to counterfeiters and other threats. Security
checkpoints equipped with X-ray Security Systems (NIIS-Non-Intrusive Inspection
Systems) like airports, ports, border control and customs authorities tackle
the myriad of threats by using NIIS to inspect bags, air, land, sea and rail
cargo, and vehicles. The reliance on the X-ray scanning systems necessitates
their continuous 24/7 functioning being provided for. Hence the need for their
working condition being closely monitored and preemptive actions being taken to
reduce the overall X-ray systems downtime. In this paper, we present a
predictive maintenance decision support system, abbreviated as PMT4NIIS
(Predictive Maintenance Tool for Non-Intrusive Inspection Systems), which is a
kind of augmented analytics platforms that provides real-time AI-generated
warnings for upcoming risk of system malfunctioning leading to possible
downtime. The industrial platform is the basis of a 24/7 Service Desk and
Monitoring center for the working condition of various X-ray Security Systems.

Machine Learning