ECLSS Development Schedule Risk Simulator

Schedule Risk Inputs

Duration uncertainty 1.0×

Monte Carlo trials 1500

Target deadline 150 d

Live Readouts

Critical path (expected)

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P50 completion

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P(finish ≤ target)

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Trials run / mean±σ

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Legend

Critical-path task (zero float) Non-critical task (has slack) Completion-time histogram bars Target-deadline marker

How it works

Each of the 11 ECLSS development tasks has an optimistic (o), most-likely (m) and pessimistic (p) duration. The single-point PERT estimate and the Critical Path Method (CPM) locate the deterministic schedule:

PERT duration:  d = (o + 4m + p) / 6
Forward pass:   ES(i) = max( EF(j) ) over predecessors j;  EF(i) = ES(i) + d(i)
Backward pass:  LF(i) = min( LS(k) ) over successors k;    LS(i) = LF(i) - d(i)
Total float:    F(i) = LS(i) - ES(i)   →   F(i) = 0  ⇒  task i is on the critical path

Real projects don't run at the single most-likely duration, so each Monte Carlo trial instead samples every task's duration from a triangular distribution built from (o, m, p), re-runs the forward pass, and records the project finish date:

Triangular sample (u ~ Uniform(0,1)):
  if u < (m-o)/(p-o):  x = o + sqrt( u (p-o)(m-o) )
  else:                x = p - sqrt( (1-u)(p-o)(p-m) )

The "duration uncertainty" slider scales the (m−o) and (p−m) spreads symmetrically around m before sampling, widening or narrowing the tails. Running thousands of trials builds the green histogram of possible completion dates below the network; the fraction of trials finishing at or before the target-deadline marker is the reported P(finish ≤ target) — the same schedule-risk technique (PERT/CPM + Monte Carlo) used in real spacecraft hardware-integration project planning.

Network: task duration (CPM) — time flows left → right
Histogram: completion-time distribution (Monte Carlo)

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