Understand whether a repair produced a durable result
A closed work order records completion. Reliability analysis asks what happened afterward: whether the symptom returned, how long the unit remained in service, and which conditions changed the outcome. Start by connecting serial-numbered equipment, repair events, test results, and subsequent returns.
Compare equipment under comparable conditions
Group records by equipment model, configuration, failure mode, operating conditions, and prior repair history. A component with more failures may also have more operating hours. Keep exposure and observation periods visible before comparing results.
Choose measures the evidence can support
- Repeat repair rate: units with a qualifying repeat divided by repaired units with sufficient follow-up. Define the symptom and return window first.
- Time to recurrence: elapsed time between return to service and a qualifying failure. Distinguish calendar time from operating time.
- Downtime: time equipment is unavailable, with waiting, diagnosis, parts, and verification recorded separately where possible.
- Failure frequency: compare failures against operating exposure only when that exposure is known and consistently recorded.
Incomplete histories and units still operating at the end of an observation period can bias simple averages. Record those limits rather than treating missing data as evidence of success.
Turn a pattern into a reviewable decision
Review recurring symptoms and repair sequences with technicians. Identify the evidence for a suspected failure mechanism, the alternative explanations, and the test that could distinguish them. Then measure whether a change improves the next cohort.
BenchSight repair analytics connects prior attempts and outcomes for that investigation. Start with one failure class and a measurable service decision.
Start with one service problem
Discuss the records you have, the decision you need to improve, and how you will measure the result.
Discuss your workflow