Your Reliability Engineering Professional Development Site
First off, switches are not perfect, so this situation is hypothetical. Yet, when you are exploring adding standby redundancy and haven’t sorted out the switching mechanism, you may be purely curious about the benefits of the redundancy. [Read more…]
Mechanical systems wear out and fail eventually. The ability of a structure to support a load, move through the specified range of motion, or spin degrades with use and time. Even our joints eventually wear out.
Accelerated life testing (ALT) has plenty of literature concerning the failure mechanisms unique to electronic components and materials. This is partially due to the limited number of unique electronic components compared to the often custom mechanical designs. ALT also has value as it provides information about a system’s reliability performance in the future.
Let’s explore an example of mechanical reliability testing (an ALT) in order to outline a basic approach to ALT design and analysis. [Read more…]
Most statistics books and the CRE Primer have tables that permit you to avoid calculating the probability for common distributions. The normal distribution requires numerical methods to conduct the calculations and would not be feasible during the CRE exam. [Read more…]
Suppliers often include reliability information along with performance specifications.
We look for reliability statements as one part of the selection process to ascertain if the component is likely to have sufficient reliability.
When the vendor’s data is clearly stated and meaningful, that information saves us from potentially having to conduct our own reliability evaluations. [Read more…]
There are a number of different methods to calculate confidence intervals for a proportion. The normal approximation method is easy to use and is appropriate in most cases.
Clopper and Pearson describe the Clopper-Pearson method also called the exact confidence interval and we’ll describe it in a separate article.
There are other methods, which again will find a description in separate articles. [Read more…]
If you buy more than one of an item used in your product, you will have to deal with variability. In general, the variability from part to part is minimal and expected. Occasionally, the variability is large and causes reliability problems. [Read more…]
As with other point estimates, we often want to calculate the confidence interval about the estimate. The intent is to determine the range of reasonable values for the true and unknown population parameter. For MTBF, this no different.
It was late Friday afternoon and the phone rang. Which is rarely a good thing.
There seems to a significant spike in field failures due to one component. The initial failure analysis work reveals the issue started with a batch of parts received about two months ago and the flaw continues to appear in subsequent batches. [Read more…]
When using a sample to calculate a statistic we are estimating a population parameter. It is just an estimate and the sample due to the nature of drawing a sample may not create a value (statistic) that is close to the actual value (parameter). [Read more…]
The communication between suppliers or vendors and their customers is often using a mix of specifications and requirements.
Customers set requirements and suppliers offer specifications. When they match, or when a supplier component specifications meet the customer’s requirements, we have the potential for a transaction. [Read more…]
Control charts help us monitor and stabilize a process. A little graphics along with statistics provides a tool to identify when something has changed. Some changes are abrupt and obvious, other a little more subtle, yet the out of control signals each have approximately the same chance of alerting us to a change.
A little graphics along with statistics provides a tool to identify when something has changed. Some changes are abrupt and obvious, other a little more subtle, yet the out of control signals each have approximately the same chance of alerting us to a change. [Read more…]
As you may recall the probability density function describes the behavior of a random variable.
Like a histogram, the PDF when plotted reveals the shape of the distribution. The PDF also has the property that the area under the curve for is one. Another property is the PDF is defined across the entire sample space. [Read more…]
“Keeping the end in mind”, “working toward a common objective” and “providing a vision” are all convention management wisdom based on setting goals.
Seeing a reliability goal is one of the first tasks when creating a reliability plan.
“How good (reliable) does it have to be?”
That is answered with a reliability goal statement.
There is a lot of uncertainty concerning a reliability goal. [Read more…]
It seems that anytime we draw a sample, it should be taken randomly. Statistics books and papers regularly advise using a random sample. The adverse effect on results drawn from the experiment may hinge on the randomness of the selection of samples. [Read more…]
My introduction to reliability engineering was my boss asking me to sort out how long a new product will last in use.
The expectation was it would last for 20 years or more buried in Italian mountain concrete bridges.
My first thought was about living in the Dolomites for 20 years monitoring the performance of the product.
That was quickly dashed as my boss explained he wanted an answer in about 6 months.
Now this was a problem. How do you cheat time to learn about the expected lifetime of a something? Thus started my career in reliability engineering.
Life testing for reliability engineering helps us answer the question how long till failure occurs. Specifically, we find the chance of failure over some duration. [Read more…]
