Simura reads your simulator's full repair history and turns it into a six-month failure forecast - then our engineering team sources the spare parts before they're needed.
Most FSTD maintenance is reactive: a component fails, the sim goes AOG, and the part takes weeks to arrive. The failure signals were usually in the history all along.
Critical failures ground the device mid-programme, with knock-on effects across the training schedule.
Legacy simulator components can take weeks to source once a fault is confirmed - time the device spends offline.
Resets and cleans clear the symptom but leave the root cause, so the same fault keeps returning.
The same process runs on any simulator's maintenance record. It ends not with a chart, but with the physical spare part staged before you need it.
We connect securely to your maintenance ticketing system - the log your engineers already fill in - and continuously synchronise the complete servicing history, ticket by ticket.
An interactive console turns years of tickets into a clear picture: which device struggles with which system, how long faults take to close, and where parts get stuck in sourcing.
The model ranks every system by how often it fails, how recently the rate has changed, how critical the outcomes are, and the direction of travel - then projects the next six months for each device.
This is where Simura is different from a dashboard. Our engineering team turns the forecast into a provisioning plan and sources the parts - so the component is on your shelf before the failure, not weeks after it.
Every projection is traceable to the tickets behind it - so your engineers can trust the recommendation, not just read it.
Parts are ordered against a forecast, not a breakdown - cutting the wait from weeks to zero when the fault hits.
The model surfaces systems that keep being reset rather than repaired, so the recurring fault is finally closed out.
Fewer unplanned AOG events means the device stays available for the programme it was built for.
Send us a little about your fleet and we'll walk you through a forecast built on your own maintenance data.