Your Reliability Engineering Professional Development Site
This discussion draws on over 150 reliability program assessments. Let’s discuss the findings, key lessons, and best practices.
Let’s start the discussion on how to think about improving your reliability programs both at the specific project and across the organization.
Thinking about the value of each task and how it will benefit achieving personal, business, and customer objectives are key.
ᐅ Play Episode
I do not like procurement organizations.
It is like saying you don’t like lawyers. I don’t know all procurement engineers or managers, so understand my statement is a grand generalization. It’s not the people I don’t like, it’s a common behavior that I’ve witnessed countless times that I do not like.
Procurement organizations tend to look for ways to reduce cost by purchasing less expensive components or materials. This is often done with little regard to the impact on product reliability.
Why is this? And what can we do as reliability professionals to change this behavior? [Read more…]
Beyond understanding what will fail (failure mechanisms) we need to know when a system will fail. Both kinds of information can be found in a variety of sources.
Unlike the stock market where we are regularly warned that past performance does not indicate future performance; in reliability engineering past performance is the best predictor of future performance. [Read more…]
The other day a student said they are asking for failure dates, not failure rates. That is a marked improvement when requesting information for the many sources of reliability information. It is not sufficient though.
Also ask for the type of failures expected or encountered during the testing or observation. [Read more…]
Have you ever wished your organization would work together to achieve a reliable product? Not just a few individuals and a heavy reliance on the reliability team to focus on highlighting and fixing reliability issues.
Some organizations tend to react to reliability issues. Prototype testing and field returns continue to surprise the team. The worst organization fall into finding someone to blame. Better organizations set to work to understand the problem and quickly resolve the issue. Some have better ‘fire departments’ than others.
Responding quicker is not really the best way to deal with reliability. [Read more…]
We rely on data to make decisions, to reveal patterns or trends, to learn about our systems and world. Data has many forms and sources. Reliability data may provide what will fail and/or when a device will fail. [Read more…]
Is it possible to foresee all reliability issues before a product launch?
No.
I don’t think so. Can we minimize surprises from field failures?
Yes.
The number of potential failures is often unknown.
Reliability engineering has value. It can improve product reliability, increase uptime, and drive customer satisfaction, for example.
Here are a couple of stories based on real situations that resulted in significant value for the organization.
Here’s an overview of the non-parametric test to evaluate if a set of samples have the same variance. If the variances are equal they have homogeneity of variances.
Some statistical tests assume equal variances across samples, such as analysis of variance and many types of hypothesis tests. It is also assumed for statistical process control purposes to determine stability (often done with range (r chart) or standard deviation (s charts). [Read more…]
How does one become a reliability engineer?
How does one create a career based on reliability engineering?
In my experience, I have seen several paths and have observed a number of key traits that make for a successful career.
This discussion examines the traits of successful reliability professionals from different industries.
The combination of those profiles and my experience with coaching dozens as they built their careers has provided a unique insight into the key traits that separate a rewarding from an unfulfilling career in reliability engineering.
ᐅ Play Episode
A contingency table, as in the chi-squared test of independence, reveals if two sets of data or groups are independent or not. It does not reveal the strength of the dependence. The contingency coefficient is a non-parametric measure of the association for cross-classification data. [Read more…]
“The language we use matters.” Wayne Nelson
How we talk about reliability does matter. It sets expectations and influences decisions. We talk about reliability as it is important to our customers and our business. The successful operation of the equipment in a plant permits the production of products. The successful operation of the product satisfies the needs and expectations of our customers.
The chi-square ( $- \chi^2 -$) test provides a means to determine independence between two or more variables. In this case, it works for count data.
Contingency table or row and column (r x c) analysis are other common names for this analysis. It is useful when comparing results from different treatments or processes. [Read more…]
Years ago a client asked for help in reducing the amount of reliability testing they did for each project. They had a sense that some of the testing wasn’t useful. What they want to know was how to select the appropriate testing and be sure they wouldn’t miss anything important.
There are two basic approaches when addressing product reliability: Reactive or Proactive. Neither is right or wrong.
The reactive approach has the limitation of responding to failures that occur during prototyping, production and customer use.
The proactive approach focuses on preventing product design, assembly, and use issues before they have the opportunity to create a product failure.