Weibull Analysis

Weibull analysis fits failure-time data to a Weibull distribution to reveal whether failures are dominated by early defects, random events or wear-out, and to estimate characteristic life. It turns sparse failure records into actionable reliability insight.

The Weibull distribution is flexible: its shape parameter (beta) indicates the failure pattern — below one for infant mortality, around one for random failures, above one for wear-out — while the scale parameter gives the characteristic life at which about 63% of items have failed. Reliability engineers use it to set optimal replacement intervals, justify maintenance strategy and forecast spares, often working from only a handful of failure and suspension records.

Related terms

Bathtub Curve · Mean Time Between Failures (MTBF) · RCM (Reliability-Centred Maintenance)