Asset runway is how long until a piece of equipment crosses an action threshold, together with what is driving it there and what waiting costs. A duration, a cause and a cost, delivered together. SENTRIX Runway™ is the number the platform produces.
A number with no reason and no cost attached is just another dashboard tile. Three things ship together or none of them do.
How long. The runway window — a range, not a date. Ranges here are ensemble spread across the model committee, and calibration is still in progress, so we do not call them confidence intervals. We also do not publish a single date. A single date is false precision, and when the asset arrives two months early the precision is what you remember.
What is driving it. Which mechanism is consuming the life — thermal, cycling depth, a rising internal resistance, a duty profile heavier than the asset was specified for. Without the cause there is nothing to act on.
What waiting costs. The platform prices the delay using your own inputs — your replacement cost, your outage cost, your labour rates. The arithmetic is shown and labelled illustrative. We do not publish savings figures, because your numbers are the only ones that matter and we do not have them until you do.
State of health (SOH) tells you where a battery is right now, as a percentage of its original capacity. Runway tells you how long before it crosses the threshold where you have to do something. SOH is a position. Runway is a forecast.
Every battery management system on the market already reports SOH. It is a standard reading and it is genuinely useful — but it is a rear-view mirror. Knowing a pack sits at 87% tells you nothing about whether that is six months of comfortable headroom or the last quarter before a cliff. Two packs at the same SOH, worked differently, are not the same asset.
The pivot is the whole point. SOH is the on-ramp because it is the number your team already trusts and already has. Runway is what you get when you ask the next question.
Remaining useful life (RUL) is the duration on its own. Runway is the duration plus the reason and the cost of waiting. RUL tells a reliability engineer how long is left. Runway tells an operator what to do about it and what the decision is worth.
RUL is the right term in a technical paper and we use it in ours. It is the wrong term in a budget meeting, because it stops exactly where the decision starts. The gap between the two is not modelling — it is everything that has to be attached to a forecast before someone will act on it.
On the utility side the equivalent vocabulary is the asset health index (AHI), a composite condition score for transformers and substation equipment, described in the CIGRE technical literature. Same shape of problem, same gap between a score and a decision.
Power transformers averaged 128 weeks of lead time — about two and a half years — and generator step-up units 144 weeks, in Wood Mackenzie's second-quarter 2025 survey, reported by POWER Magazine in January 2026. If an asset has eighteen months of runway and the replacement takes thirty, the decision was already late when you found out. That is not a maintenance problem. It is a procurement problem that maintenance data could have caught.
Most owners do not know their runway. They know their lead times, because procurement tracks those. The two numbers have never been on the same page.
Start with the data you already have →Lead-time figure is third-party and citable. Runway figures come from your own assets.
Days depend on how hard the asset is worked. The same battery reaches the same threshold in half the calendar time under a heavier duty profile. Cycles are the honest unit, so cycles are what we quote.
Where a calendar figure is genuinely more useful — and in a budget conversation it usually is — we convert, but never silently: “640 cycles, roughly 14 months at current duty.” The qualifier is not a hedge. Drop it and the number quietly becomes a promise about a workload nobody agreed to.
Mapping your actual duty profile is the first thing the assessment phase does, and it is the reason the same model produces different calendar answers for two sites running identical hardware.
It says so. When inputs are missing or stale, the platform abstains and reports no runway rather than filling the gap. The abstention appears as a result in its own right, with the reason: no runway stated — inputs stale.
This is deliberate and it is the part we would defend hardest. A model that always answers is a model you cannot trust on any individual answer, because you have no way to tell the confident calls from the guesses. Ours declines, visibly, and tells you which input let it down — a sensor, a connection, or the asset itself.
The willingness to say nothing is the reason the other numbers are believable.
A committee of models forecasts the asset’s trajectory from the signals it already produces, re-anchoring to measured state every time new data arrives. The spread across that committee is the range you see.
Which modelling technique wins is decided per asset class by test, not by preference. Physics-informed models where the physics earns its place; statistical models where it does not. We have run both across three asset classes and the answer is not the same every time — and where the simpler model won, we published that too.
Public reference data underpins the validation work, principally NASA’s battery reference program and MIT/Stanford commercial-cell datasets. Degradation and lifetime context draws on published work from NREL and the U.S. Department of Energy.
See the evidence, including the misses →A read-only assessment produces the first runway figures on your own data, before any hardware conversation. You see the record; you decide what it is worth.
Choir™ Corp