Weibull in Excel: when it helps and when it misleads
A Weibull plot is a way of looking at life data — times to failure, or times to a defined event — to see whether a single wear-out or infant-mortality story is even plausible, and to estimate a characteristic life and a slope (the shape parameter). In Excel, that usually means a carefully prepared data set, a median-rank or similar plotting position, and a fit you can show. The Weibull Analysis Toolkit is built for that workflow.
When it helps
It helps when you have a reasonably clean set of similar items, a defined failure mode, and enough events (and suspensions) to see a pattern. It can support an interval discussion, a spare-part conversation, or a decision that a mode is still in a random-failure regime where a time-based restoration is a poor bet.
When it misleads
It misleads when the data mix several failure modes, when n is tiny, when “as-bad-as-old” repairs are treated as good-as-new lives, or when a straight line is forced through a clearly curved plot. A precise β to two decimal places is not a finding if the underlying sample cannot support it. In those cases, a simple rate λ = n/T, with an interval, is the more honest tool — and it is the one the funding method uses by default.
If you are setting PM intervals, a Weibull fit is an input to a discussion, not a substitute for auditing the program or for a P-F argument on a predictive task.