Content By Fred Schenkelberg

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By: Fred Schenkelberg

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.

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By: Fred Schenkelberg

If you have been a reliability engineer for a week or more, or worked with a reliability engineer for a day or more, someone has asked about testing planning. The questions often include, “How many samples?” and, “How long will the test take?” No doubt you’ve heard the sample-size question.

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By: Fred Schenkelberg

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.

Fred Schenkelberg’s picture

By: Fred Schenkelberg

Spending too much on reliability and not getting the results you expect? Just getting started and not sure where to focus your reliability program? Or, just looking for ways to improve your program?

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By: Fred Schenkelberg

A fault tree analysis (FTA) is a logical, graphical diagram that starts with an unwanted, undesirable, or anomalous state of a system. The diagram then lays out the many possible faults, and combinations of faults, within the subsystems, components, assemblies, software, and parts comprising the system that may lead to the top-level unwanted fault condition.

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By: Fred Schenkelberg

When products were crafted one at a time, the design and manufacturing processes were often done by the same person. For example, a craftsman would design and build a chest of drawers or a carriage. Some trades would employ apprentices to learn the craft, which also included design.

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By: Fred Schenkelberg

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.

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By: Fred Schenkelberg

Concurrent engineering is a common approach that pairs developing the product design and its supporting manufacturing processes through the development process. There are several reasons why this is a good idea.

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By: Fred Schenkelberg

The planning of environmental or reliability testing becomes a question of sample size at some point. It’s probably the most common question I hear as a reliability engineer: How many samples do we need?

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By: Fred Schenkelberg

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.

The blame game

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.