ECLSS Preventive Maintenance Scheduler

Maintenance Strategy

Mission time speed 2.0 d/s

Weekly crew-hour budget 16 h/wk

Preventive service threshold 80%

System Status

System reliability

100%

Mission day

0.0

Failures (unplanned)

Crew-hrs this week

0 / 16

Modules

Click a rack in the 3D view to select a module.

How it works

Each module's failure risk follows a Weibull "bathtub" wear-out hazard, the standard reliability-engineering model for hardware whose failure rate rises with age since it was last serviced (seals dry out, filters foul, sorbent saturates):

hazard   h(t) = (k/λ) · (t/λ)^(k-1)
reliability R(t) = exp( -(t/λ)^k )
per-step failure chance ≈ h(t) · dt

t = simulated days since the module's last service, λ = its characteristic life, k > 1 = wear-out shape (bigger k = the hazard rises faster as the part ages). System reliability is the product of every module's R(t).

Preventive — a module is auto-serviced (age reset to 0) once its reliability drops below the threshold, but only if this week's crew-hour budget still has room. Planned service costs 2 crew-hours.
Reactive (run-to-fail) — nothing is serviced early; a module runs until it actually fails (a live draw against h(t)·dt), forcing an unplanned repair that costs 6 crew-hours and counts against the failure tally.
Crew-hour budget — resets every 7 simulated days. Spending more hours than the budget in a week shows as overtime (the readout turns amber/red) — the real trade-off every ECLSS maintenance plan has to make.
Click any rack in the 3D view (or its row in the Modules list) to select it, then Service Selected Module to repair it manually regardless of strategy.

Real-world relevance: this is the same logic that sizes ISS ECLSS spares manifests and crew-timeline budgets — deferring maintenance saves crew-hours short-term but raises the odds of an unplanned failure that costs far more time to fix.

Healthy (R ≥ 80%) Degraded (R 40–80%) Critical / failed

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