The same anomalous figure carries different meanings at different stages of a product’s lifecycle.

2026-10-21 14:19:16Gesrepair / Technav

When a service center sees rising failure counts, a growing backlog of work in progress, or lengthening turnaround times, the first question is usually whether the number counts as abnormal. Reliability engineering’s answer is that you first need to know which stage of its lifecycle the product is in, because the same number points to different causes at different stages.


I. The Hazard Function Describes the Direction of Risk

Reliability engineering uses the hazard function to describe the instantaneous failure rate of a component or system at any point in time, on the condition that it has not failed up to that point. Because it is conditioned on survival, this metric shows how risk changes over time, rather than the cumulative probability of failure within a fixed period.

The shape of the function itself explains the failure mechanism:

  • Constant hazard rate: failures occur randomly in a steady way that is independent of age, such as random electrical transients.
  • Increasing hazard rate: components gradually age with use, which is wear-out failure.
  • Decreasing hazard rate: products with latent defects fail quickly, and the survivors become increasingly reliable.

Combined, these three trends form the familiar bathtub curve: a falling failure rate early on, a roughly flat middle, and a rise at the end.


II. Causes in the Three Phases and Observations from the Repair Side

Based on two sources, the following summarizes the trend, common causes, and typical situations seen in repair for each phase of the bathtub curve.

PhaseFailure Rate TrendCommon CausesRepair-Side Observations
Early failureDecreasingDead on arrival, manufacturing errors, material defectsCases reported by customers also include misuse or improper installation, but manufacturing defects cannot be ruled out
Useful lifeRoughly constantEnvironmental stress or load exceeding the strength of the weakest componentFailures are usually predictable and stable; manufacturers want this phase to be as low as possible
Wear-outIncreasingComponents reach end of life through aging and wearLifespan is often stated in product datasheets, such as the rated number of key presses


III. The Same Anomaly Must Be Read in Different Directions at Different Phases

According to the phase definitions above, a rise in failure volume is more likely to point to design, process, or material problems in the early phase, usually reflects component aging in the wear-out phase, and in the useful-life phase calls for a re-examination of the operating environment and load. The practical recommendation from the repair side is that for dead-on-arrival cases in the early phase, a failure analysis report should be requested from the repair center to serve as the basis for raising defect and warranty claims with the manufacturer.

This also means a number at a single point in time cannot support a judgment. To determine which phase a batch of products is in, you need at least each unit's shipment date and usage time; without complete records, it is impossible to tell which type of anomaly it is.


IV. Failure Rate Is Not the Same as Risk

The failure rate measures only how fast failures occur and does not reflect their consequences. In safety-related fields, each failure mode is additionally assigned a consequence level, and risk is determined jointly by failure rate and severity: a high failure rate with minor consequences may still be acceptable, while a low failure rate with severe consequences may not be. Common uses of failure rate analysis include warranty cost estimation and optimization of maintenance scheduling and inspection intervals, and the boundaries between phases usually have to be estimated from field data before being applied to warranty policy and maintenance scheduling.

In addition, replacing the weakest component with a new part during the wear-out phase can "reset" the equipment's curve and extend its service life, which is the reliability value of repair.


Conclusion

The failure rate curve provides a framework for interpretation: a number alone does not explain the cause, and the phase it falls in determines whether it points to design, the usage environment, or aging. For a service center, fully preserving shipment and usage times and distinguishing failure phases is what allows an anomalous number to answer "why", not just "that it happened".


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