Does zero recorded escapes prove zero probability?

No, the Wilson upper bound remains positive for a finite cohort. Undiscovered events can also make recorded escapes understate the underlying frequency.

Is the interval an exact 95% guarantee?

No, Wilson is an approximate score interval under the stated binomial assumptions. Exact binomial methods may be required for sparse-data decisions or mandated statistical plans.

Can I enter defects instead of escaped units?

No, count each affected unit once even if it has several nonconformances. Multiple defects per unit require a different event-count model.

Does meeting the target authorize flight hardware release?

No, the target supports process monitoring only. Apply the governing inspection, disposition, qualification and release requirements independently of this statistical summary.

Aerospace & Defense Manufacturing calculator

Aerospace Observed Escape Rate Calculator

Measure recorded escapes within a defined released-unit cohort. Enter unique escaped units, reviewed released units and a process monitoring target.

What this calculator does

Estimate the recorded escaped-unit proportion and an approximate 95% Wilson interval for a comparable released cohort.

Formula used

p = escaped units ÷ released units; n = released units; observed rate (%) = p × 100
Wilson center = (p + z² ÷ (2n)) ÷ (1 + z² ÷ n)
Wilson halfwidth = z × sqrt(p(1 − p) ÷ n + z² ÷ (4n²)) ÷ (1 + z² ÷ n)
Wilson bounds (%) = (center ± halfwidth) × 100; z = 1.959963984540054
Target margin = target percentage − Wilson upper bound

Inputs explained

Released Units in Reviewed Cohort: Distinct released units with the same defined follow-up and review window.
Units With Recorded Escapes: Distinct cohort units with a confirmed nonconformance found after release.
Process Escape Rate Target: Your monitoring target for this recorded escaped-unit measure.

How to use the result

Best suited to recorded escape trend Review, closed cohort statistical review.
Wilson bounds approximate 95% coverage; use exact binomial methods when sparse-data coverage is critical. Undiscovered escapes and unequal follow-up can bias the observed rate. Neither the rate nor its interval establishes flight release or qualification.

Current U.S. benchmarks

Steel mill PPI stands at 381.162 (BLS, Aug 2026), up 23.4% from a year earlier. New factory orders are up 8.5% year over year (Census).
The U.S. has 11,691 transportation equipment establishments employing about 1,682,910 workers (Census County Business Patterns, 2023).

Common questions

Does zero recorded escapes prove zero probability? No, the Wilson upper bound remains positive for a finite cohort. Undiscovered events can also make recorded escapes understate the underlying frequency.
Is the interval an exact 95% guarantee? No, Wilson is an approximate score interval under the stated binomial assumptions. Exact binomial methods may be required for sparse-data decisions or mandated statistical plans.
Can I enter defects instead of escaped units? No, count each affected unit once even if it has several nonconformances. Multiple defects per unit require a different event-count model.
Does meeting the target authorize flight hardware release? No, the target supports process monitoring only. Apply the governing inspection, disposition, qualification and release requirements independently of this statistical summary.

Last reviewed 2026-10-06.