Readiness is a sustainment problem
How much of a fleet can move on a given day comes down to spares availability, maintenance throughput, and supply lead times. Reactive, fail-then-fix maintenance forces cannibalisation and unplanned downtime, and readiness becomes a daily scramble for parts.
Predict the fault, pre-position the part
The measure that matters is the mission-capable rate, the share of time an asset can perform at least one assigned mission. The GAO readiness reviews show how often fleets fall short of their goals.
Condition data, vibration, oil quality, usage profile, flags component wear weeks ahead, and demand-sensing forecasts the spares to have ready.
Where the ERP closes the loop
On Hudace, maintenance, parts, and supply share one platform, so a predicted fault becomes a maintenance window in a low-tempo period and a spare ordered before it is needed. Xenon AI recommends the maintenance and the procurement; sustainment officers authorise.
In a classified or controlled context, data residency and model governance are hard constraints, built in rather than bolted on.
The numbers to watch
Track availability and the sustainment chain that drives it.
Mission-capable rate
Time an asset can perform a mission / total possessed time. The headline readiness number.
Operational availability
Uptime including logistics and admin delay. The fuller availability picture.
MTBF
Mean time between failures. Rising means assets run longer between interventions.
Spares fill rate
Demands met from stock / total demands. Low fill is what forces cannibalisation.
See higher readiness on Hudace
Talk to our team about predicting faults and pre-positioning spares on one platform.