A Weibull fit is more than a curve — its shape parameter tells you whether you're seeing infant mortality, random failures, or genuine wear-out. Here's how I read one before trusting any conclusion drawn from it.
Read post →Engineers love a Weibull plot, but the plot itself isn't the point — the shape parameter, β, is. That one number quietly tells you which failure regime you're actually in, and it should change how you respond long before you quote a single number to anyone.
When β is less than 1, the failure rate is decreasing over time — classic infant mortality. The fix usually isn't replacement; it's screening, burn-in, or hunting down a process defect at the source.
A β near 1 means a roughly constant failure rate: failures are effectively random. Scheduled replacement buys you almost nothing here, because a new unit is no less likely to fail tomorrow than the one you pulled.
Once β climbs above 1, the rate is increasing — wear-out. This is the one regime where preventive replacement finally earns its keep, and where a sensible maintenance interval can be read straight off the curve.
So before you quote an MTBF or set a maintenance interval, read the shape first. The same average lifetime can hide three completely different stories, and only one of them is fixed by swapping parts on a schedule.
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