Vexron Machine Intelligence · VMI series
VMI-2
Vexron Machine Intelligence. Multi-asset prognostics and remaining-useful-life estimates.
Overview
Vexron Machine Intelligence
VMI-2 is the next model in the VMI series, currently in development and testing. It builds on VMI-1's fault detection with prognostics: estimating how much useful life a component has left and how that changes under different operating loads. It is being trained to reason across coupled assets, where one machine's condition affects another, rather than treating each asset in isolation.
Not yet generally available. VMI-2 is in active development and testing. Talk to us if you want to be part of early validation, or explore VMI-1 and EVA-1, which are live today.
Capabilities
What it does.
Remaining useful life
Estimates time-to-failure ranges for monitored components, not just a present-tense fault flag.
Multi-asset awareness
Models how load and condition propagate across coupled equipment in the same process.
Load-aware forecasting
Adjusts life estimates for how hard the machine is actually being run, not a nameplate assumption.
Use cases
Where it earns its keep.
Maintenance planning
Scheduling interventions around estimated life instead of worst-case fixed intervals.
Spare-parts forecasting
Giving stores a forward view of which components will need replacing and roughly when.
Process-line risk
Understanding which asset in a coupled line is the real constraint on uptime.
Also explore
Related models.
FAQ
Common questions
About VMI-2 specifically. For pricing and a fit assessment for your factory, talk to our team.
VMI-1 detects and classifies faults in the present. VMI-2 adds prognostics: it estimates how much useful life a component has left and how that changes under different operating loads. It also reasons across coupled assets rather than treating each machine in isolation.
Not yet. VMI-2 is in development and testing. If you want to be part of early validation, talk to our team; in the meantime VMI-1 is live and covers fault detection today.
It is a forecast of how much operating time a monitored component has before it is likely to fail, expressed as a range rather than a single date. It lets maintenance be scheduled around real condition instead of worst-case fixed intervals.