A conversation the other day involved how or why someone would use the mean of a set of data described by a Weibull distribution.

The Weibull distribution is great at describing a dataset that has a decreasing or increasing hazard rate over time. Using the distribution we also do not need to determine the mean time between failures (MTBF)—which is not all that useful, of course.

We establish reliability goals and measure reliability performance. Goals and measures can be related; however, they’re not the same, and neither do they serve the same purpose.

Recently, I’ve seen a few statements that seem to confuse the role of statistical confidence when establishing a goal. Thus, I’d like to relate how I think about the difference between goals and statistical confidence, along with how they are related.

What if all failures occurred truly randomly? Well, for one thing the math would be easier.

The exponential distribution would be the only time to failure distribution—we wouldn’t need Weibull or other complex multi-parameter models. Knowing the failure rate for an hour would be all we would need to know, over any time frame.

Why do so many avoid confronting the reality of failure? In plant asset management, we are surrounded by people who steadfastly don’t want to know about nor talk about failures. Yet failure does happen; let’s not ignore this simple fact.

Unlike a murder mystery, failure analysis (FA) is not a game of whodunnit. The knee-jerk response to blame someone rarely solves the problem, nor does it create reliability in the workplace.