Your Reliability Engineering Professional Development Site
There is a type of error when conducting statistical testing that is to work very hard to correctly answer the wrong question. This error occurs during the formation of the experiment.
Despite creating a perfect null and alternative hypothesis, sometimes we are investigating the wrong question. [Read more…]
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.
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…]
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…]
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…]
In a recent blog post, Seth Goin discussed the need for ongoing investment to maintain infrastructure. Whether a road or building or even your own skills, it takes regular care to avoid system failures or obsolesce. [Read more…]
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…]
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…]
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…]
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…]
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.
Carl and Fred discussing the principles of teaching reliability, whether it is sharing knowledge to a small number of people or formally instructing a larger group of engineers. ᐅ Play Episode
In system modeling and fault tree analysis (FTA) we use a set of similar calculations based on Boolean logic, the AND and OR gate probability calculations. Within FTA, the AND and OR gates are just two of many possible ways to model a system. Within system modeling, often reliability block diagrams (RBD) we model parallel and series elements of a system.
In order to do these basic calculations, we need to consider a few assumptions then proceed to the math.
An immediate purpose is to earn a living. You also may suggest the work is to improve the reliability of the product or system. Reduce downtime, reduce warranty, increase profit, etc.
That is fine for the overall purpose of reliability engineering work, yet in the day to day work, the specific task level, what is the purpose behind what we do?
One of the things I like about reliability engineering is the field has a stable set of tools and approaches with an ever-changing set of challenges. The process of conducting an FMEA or Root Cause Analysis hasn’t changed much over time. Meanwhile, with the advent of new designs, materials, assembly techniques, and higher customer expectations, we continue to face interesting problems. [Read more…]