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Fred Schenkelberg — Thought Leader

Author of CRE Preparation Notes, Musings", NoMTBF, multiple books & ebooks>, co-host on Speaking of Reliability>/a>, and speaker in the Accendo Reliability Webinar Series.


This author's archive lists contributions of articles and episodes.

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Building and Using Pareto Charts

Building and Using Pareto Charts

You may have heard of the 80/20 rule. The idea is that 80% of the wealth is held by 20% of the population. As an Italian economist, Vilfredo Pareto made this observation that became generalized as the

Pareto Principle: 80% of outcomes are due to 20% of causes

For field returns, for example, we may surmise that 80% of the failures are due to 20% of the components, for example. This principle helps us to focus our work to reduce field failures by address the vital few causes that lead to the most, or most expensive, failures. [Read more…]

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Acceleration Factors with Examples

Acceleration Factors with Examples

Acceleration Factors with Examples

podcast episode with speaker Fred Schenkelberg

Carefully considering the acceleration factor (AF) is essential when conducting an accelerated life test. Like warp drives shortening the distance, accelerated life tests (ALT) attempt to shorten time. Think of the warp factor and acceleration factor as being similar, well, sort of. [Read more…]

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One Does Not Simply Do Reliability

One Does Not Simply Do Reliability

Some time ago when talking with someone I just met, the conversation turned to what we did for a living. I mentioned being a reliability engineer, and his response: “Oh, yes, we do reliability”. Curious, as I’m not sure that I ‘do reliability’, we then talked about what he meant.

The conversation revealed that they had a list of tasks that they accomplished for each product under development. They did tests and reviews of the results. A lot of testing. They did FMEA and HALT. He believed the engineers did derating or stress/strength calculation. He didn’t know about process stability with vendors or internal manufacturing lines.

They did stuff, which meant they did reliability.

[Read more…]

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Sample Size for Hypothesis Testing of μ

Sample Size for Hypothesis Testing of μ

A common question when setting up a hypothesis test is concerning sample size. An example, might be: How many samples do we need to measure to determine the new process is better than the old one on average?

While this seems like a simple question, we need a bit of information before we can do the calculations. I’ve also found that the initial calculation is nearly always initiated a conversation concerning the balance of sample risks, the ability to detect a change of a certain size and the constraints concerning the number of samples. [Read more…]

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The Value of a Great Question

The Value of a Great Question

Some time ago, earlier in my career, I worked for a wonderful boss. She would stop by my office on occasion and ask ‘what’s new?’ or “how’s it going?’ Just a check-in. I often let her know about the current vexing problem I was struggling with at the moment.

The funny thing is she never directly solve the problem for me. She certainly could have. Instead, she would ask a couple of questions that always helped me to find the solution. This happened with problems concerning dealing with a difficult person, strange material properties, motivating change within a group, or finding someone that could design and run a computational fluid dynamic model for me.

It was her questions the helped. She did this in meetings, in presentations, and when she swung by my office for a chat. [Read more…]

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The Power of a Sample

The Power of a Sample

We use a sample to estimate a parameter from a population. Sometimes the sample just doesn’t have the ability to discern a change when it actually occurs.

In hypothesis testing, we establish a null and alternative hypothesis. We are setting up an experiment to determine if there is sufficient evidence that a process has changed in some way. The Type II Error, $-\beta-$ is a measure of the probability of not concluding the alternative hypothesis is true when in reality it is true.

The power, $-1-\beta-$, reflects the ability of the sample to correctly lead us to the conclusion that an actual change has occurred when in reality it actually has. [Read more…]

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Type I and Type II Errors When Sampling a Population

Type I and Type II Errors When Sampling a Population

In hypothesis testing, we set a null and alternative hypothesis. We are seeking evidence that the alternative hypothesis is true given the sample data. By using a sample from a population and not measuring every item in the population, we need to consider a couple of unwanted outcomes. Statisticians have named these unwanted results Type I and Type II Errors. [Read more…]

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Is SPC Part of the Reliability Toolkit?

Is SPC Part of the Reliability Toolkit?

Statistical process control, SPC, is a set of tools to enable monitoring the stability of a process. SPC is also the first step to checking process capability with measures such as Cpk. Many consider SPC a quality or manufacturing tool. Yet, having and maintaining a stable process is also essential to creating a reliable product. Let me explain why. [Read more…]

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Three Approaches to Accelerated Life Testing

Three Approaches to Accelerated Life Testing

Three Approaches to Accelerated Life Testing

podcast episode with speaker Fred Schenkelberg

We can make a guess, some assumptions, or conduct an experiment. In fact, we use engineering judgment, and prudent assumptions to create our experiments that lead to understanding time to failure information. Accelerated life testing, ALT, is one of the most complex and important types of experiments we conduct. It involves samples, failure mechanisms, stress, measurements, and statistics. [Read more…]

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Single Sample Z-test Hypothesis Testing for Mean with Known Variance

Single Sample Z-test Hypothesis Testing for Mean with Known Variance

In the situation where you have a sample and would like to know if the population represented by the sample has a mean different than some specification, then this is the test for you. Oh, you also know, which is actually rather rare in practice, the actual variance of the population you drew the sample. [Read more…]

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Reliability Questions and Decisions

Reliability Questions and Decisions

Very few reliability decisions are made by reliability engineers. Yet, reliability engineers are asked many questions concerning reliability. How reliable will this design be for customers? How will the system likely fail? How many failures should we expect next month?

How you answer these and the many other questions received does impact the reliability of your product or system. The information provided those that ask reliability related questions, with useful and practical information, can make better decisions which improves reliability performance.

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