Remaining-life validation cutoff

The remaining-life validation cutoff is the information boundary used when reconstructing a forecast of remaining useful life at a particular issue time. Observations available by that time can enter the forecast; subsequent observations can establish the eventual end-of-life criterion crossing for scoring it. Keeping these roles separate prevents data leakage from turning a retrospective calculation into an apparently successful prediction.

For an original example, suppose a test reaches its specified endpoint at cycle100 and a forecast is evaluated as if issued at cycle60. The reference remaining life is40 cycles, known only after observing the later endpoint. Constructing a predictor that returns $100-t$ because the complete test record already reveals100 produces zero remaining-life validation error by construction. That is not evidence that the endpoint was predictable from the first60 cycles.

Preprocessing has the same information constraint. A trailing three-sample average $z_t=(x_{t-2}+x_{t-1}+x_t)/3$ uses observations available at $t$. A centered average $z_t^{\prime }=(x_{t-1}+x_t+x_{t+1})/3$ needs a future observation. The centered average can be legitimate with a declared one-sample reporting delay, but then its forecast issue time is $t+1$, not $t$. Parameter fitting, normalization and selection among candidate models also belong inside the information boundary.

NASA's battery-aging records provide a physical example of the required distinction: they contain measured discharge current, terminal potential and temperature, together with a capacity-loss aging endpoint and run-to-failure histories.^[ref] A validation experiment can reveal only the prefix through its chosen cutoff to a prediction method, save the forecast, and subsequently compare it with the endpoint in the withheld suffix.

A fixed model trained on other complete histories can be evaluated on a new component's prefix. A method that updates online must instead document which new observations have become available before each forecast. In either case, preserving the cutoff, endpoint definition and assumptions about future operation makes the resulting remaining-life validation error interpretable. Pooling all prediction times into one score can conceal a violation at a particular cutoff.