The manufacturer sees a component once, at production. The operator sees it across its whole service life: every removal, every shop visit, every measured value on the bench, year after year. That asymmetry means airlines and MRO shops often understand a part's real failure behavior better than the OEM does. What they usually lack is the evidence in a form that carries weight. This guide shows how to build that case from your own bench data.
The Data You Hold and the OEM Does Not
The industry already runs feedback pipes from operators to manufacturers. ATA Spec 2000 Chapter 11 standardizes the exchange of removal and shop-findings records; airframers publish component performance reports benchmarking MTBUR by part number across reporting fleets; component OEMs run programs that take monthly removal data and return corrective-action feedback. And continued-operational-safety processes depend on information supplied voluntarily by operators, which is the plainest statement of where the trend data originates.
But these pipes carry events: removals, findings, hours. They do not carry measurements. The OEM learns that your fleet removed 14 units of a part last year and that 10 tested no fault found. It does not learn that the passing units' output delay has been creeping toward the CMM limit for two years. That second fact is the design-change argument, and only your bench has it.
MTBUR, MTBF, and the Gap
Two numbers frame every component reliability discussion:
- MTBF counts confirmed failures.
- MTBUR counts unscheduled removals, whether or not a fault was confirmed.
MTBUR is always the lower number, and the gap between them is mostly no-fault-found. The gap is also where the money is: purchase agreements commonly contain a guaranteed MTBUR that the operator can claim against, and rogue-unit clauses that trigger on documented repeat removals per serial number. Both claims stand or fall on the quality of the operator's own records.
Structure Tests to Produce Evidence
A reliability case needs measured values, not verdicts. Each bench test should record the value, the unit, and the limit it was judged against:
main: - name: Signal Integrity python: phases.signal_check measurements: - name: output_delay unit: us validators: - operator: "<=" expected_value: 12.0 - name: signal_snr unit: dB validators: - operator: ">=" expected_value: 40.0With every shop visit recorded this way, the part number accumulates exactly the dataset a design-change argument is built from.
Reading the Evidence
Four views in TofuPilot turn the accumulated runs into the case:
- Distribution against limits. If the fleet's values for a measurement crowd one limit rather than centering, the design margin is thinner in service than the spec assumed. A histogram of two years of inductions makes that visible in one image.
- Cpk. A Cpk below 1.0 on a CMM limit says the population does not reliably fit its own acceptance criteria. That is a number an OEM reliability engineer cannot wave away, because it is computed on their limits.
- Drift over time. A mean shifting across months of shop visits separates aging from randomness, and puts an onset date on the change. Onset dates correlate with mod status, supplier changes, and batch boundaries.
- Per-serial history. The repeat offenders, documented visit by visit. This is the direct input to guaranteed-MTBUR and rogue-unit claims, and the concrete illustration that makes the statistical case tangible.
Making the Case
A design-change proposal built this way has a standard shape: the removal and NFF history (which the OEM partly knows), plus the measurement story (which it does not). For example: this part number shows MTBUR at half the guaranteed value; 60 percent of removals test NFF on the bench; but across 200 inductions the output delay distribution has shifted 20 percent toward the CMM limit, with onset eighteen months ago; the serials past a threshold of shop visits share the same drift signature.
That is no longer "our mechanics do not trust this box". It is a dataset the OEM's own reliability process can act on: a modification, a CMM limit revision, or a warranty settlement. Export the runs behind each figure and the case ships with its evidence attached.
What Good Looks Like
An operator working this way stops being a passive reporter of removals and becomes the party at the table with the best data. Reliability reviews with the OEM start from the operator's distributions rather than the OEM's summaries. Warranty and guaranteed-MTBUR claims are filed with measurement evidence, not just removal counts. And when the OEM disputes a trend, the answer is the query, rerun in front of them.