Fundamentals of Ongoing Reliability  Testing

podcast episode with speaker Fred Schenkelberg

Ongoing Reliability Testing (ORT) is a class of product testing that aims to identify potential field reliability issues after product launch and before customers experience failures. Typically, done using a rotation of samples directly from production and using expected use conditions/stresses, the testing balances many factors to be of value.

ORT works well to monitor an ongoing production process subject to variation. If that variation impacts reliable performance, then a well-designed and implemented ORT should identify the issue.

Let’s explore the range of considerations when designing an ORT to optimize the ORT’s ability to identify field problems efficiently. We will also discuss the various tradeoffs that impact sample size, the use of accelerating stresses, and more.

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Fundamentals of Early Field Results

podcast episode with speaker Fred Schenkelberg

At least one group called this the ‘Delta Phase.’ It is the period shortly after launching a product and provides a unique opportunity to reduce future field failures and improve customer satisfaction dramatically. The idea is to aggressively identify and resolve any field issues identified by your customers.

There are a couple of ways to implement the Delta Phase with your product launch. Yet, it requires creating a team from the design/development team that has the authority and capability to implement design changes quickly.

Let’s explore the concept of a delta phase and how to implement it in your organization. Plus, let’s examine a few situations that make significant short and long-term reductions in the field failure rate.

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What’s Wrong with Using ‘FITs’ to Measure Electronic Component Reliability?

podcast episode with speaker Chris Jackson

Every industry has its own way of characterizing reliability metrics. For example, the ball bearing industry uses the metric ‘B_10’ to represent the time by which they expect 10 % of all ball bearings of a specific type to fail. Electronic component manufacturers use the term ‘Failures in Time’ of ‘FITs’ to describe the reliability of their products. But what is a FIT? And how can you use it to measure reliability? Did you know that many electronic manufacturers advertise ‘FIT values’ that imply a mean time to failure of over 1 000 years? If you are involved in electronic component reliability, then join us for this webinar!
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Fundamentals of System Effectiveness

podcast episode with speaker Fred Schenkelberg

System or Operational Effectiveness is comprised of three elements. An early definition included capability, reliability, and availability. Another early definition included availability, dependability, and capability. In essence, can the system do what it’s supposed to do? Is it ready when needed? And is it able to work without failure long enough?

Let’s examine system effectiveness and its factors or elements in more detail. Then, examine an example or two so you can apply this concept to your situation.

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What’s the Difference Between FMEA and FMECA?

podcast episode with speaker Chris Jackson

And the answer is not ‘the letter C.’ A FMEA is a group activity that follows a logical (and time-proven) structure to effectively ‘brainstorm’ what are called ‘corrective actions’ for existing or likely problems in design and manufacture of products. Production teams that comprise designers, engineers, technicians and manufacturers typically have a wealth of existing knowledge and understanding of the product being developed. But some people will tell you that an FMECA is not an FMEA. And many government agencies, in particular, demand FMECAs over FMEAs. Interested to understand the difference (if any) between FMEAs and FMECAs? … and How can you make an FMECA work for you? Join us at this webinar!
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Fundamentals of Reliability Goals

podcast episode with speaker Fred Schenkelberg

Goals, objectives, milestones, targets, whatever you call them, just have a clear one. Setting a reliability goal is easy. Get a few people together for a short discussion and in less then 10 minutes you can craft a meaningful reliability goal.

Let’s explore the elements that make up a reliability goal. Plus, the range of inputs you can use to define each element. Plus, some best practices when establishing goals.

Finally, simply setting a goal adds value to your organization – if it is a complete and practical goal. Estimating or measuring that value can be tricky, so let’s discuss a few ways you may quantify the value of a goal.

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Using Fault Trees to Conduct Root Cause Analysis (RCA)

podcast episode with speaker Chris Jackson

What is a ‘root cause’ of failure? It is something that you did (or didn’t) do that ultimately resulted in failure. It’s not corrosion (that’s a physical process that follows the laws of nature that you can’t change). It’s not a porous seal that allows moisture to enter your product to cause corrosion (that’s a defect or fault that you or your team made happen). Root Cause Analysis (RCA) is the process where we systematically work out what things we did or didn’t do that allowed failure to occur, and Fault Trees are often very helpful in finding this root causes. If you want to learn more about RCA or how fault trees can help RCA, join us for this webinar.
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Fundamentals of a Professional Development Plan

podcast episode with speaker Fred Schenkelberg

Professional development is not about pursuing a degree or title. It’s about what you can do with your knowledge. Of course, that is my opinion. Some seek credentials that may lead to a new position or opportunities. Some seek knowledge without intending to use it – education for education’s sake.

Whatever the motivation, we should approach learning meaningfully. Set objectives, do the homework, get feedback or coaching, and establish a routine to continue to hone your knowledge. Whether you want to learn something out of curiosity or master a topic to accomplish a task, you can plan to use your time efficiently.

Let’s explore how to improve your ability to learn and continue to learn throughout your career. As reliability engineers, there seems to be a never-ending list of concepts, failure mechanisms, novel materials, etc., that we can and should know about. With so many options for professional development, let’s examine a few principles and tips so you can learn and master what you desire to learn and master.

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What is the ‘3 Parameter’ Weibull Analysis

podcast episode with speaker Chris Jackson

Some of you might have heard of the Weibull distribution. It is an uncannily accurate way of describing many of the ways components fail. It can model things that wear-in where failure is caused by pre-existing damage and defects in a fraction of products. The Weibull distribution can also model things that wear-out we failure is caused once enough damage has accumulated. And some of you might have heard of the ‘3 Parameter Weibull distribution.’ But what makes this different and (sometimes) helpful? We are always wanting to improve the way we model things, including failure processes. So, to see if the ‘3 Parameter Weibull Distribution’ can help you … join this webinar!
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Fundamentals of Pareto Analysis

podcast episode with speaker Fred Schenkelberg

Pareto Analysis is a simple yet powerful tool that provides a visual way to help focus on the most critical tasks. The idea that 80% of your field failures come from 20% of the failure mechanisms is one way we can focus on the vital few instead of the insignificant many.

Let’s explore the basics of conducting Pareto Analysis, plus a few different ways to create and modify the plots. Of course, we’ll talk about some potential problems and pitfalls to avoid.

Bring your questions and success/failure stories using this tool. There should be plenty of time for a discussion.

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Understanding (how bad) the Exponential Distribution (is)

podcast episode with speaker Chris Jackson

We often use probability distributions to help us characterize the likely values a random variable will have. This includes the random variable we call ‘time to failure’ or TTF, which is how long something works before it fails. Failure is a random process, but just because it is random, doesn’t mean it’s unpredictable. Products that wear-in will have vastly different probability distributions for TTF when compare do products that wear-out. So you need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering. But we often see in textbooks and standards the ‘exponential distribution’ simply being assumed as a ‘good’ TTF probability distribution. But is it? And what happens when it isn’t … but you use it anyway? Join this webinar to find out!
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Fundamentals of Hypothesis Testing

podcast episode with speaker Fred Schenkelberg

Let’s make a comparison. Let’s check our product’s key characteristics against specifications, compare vendor life data, or compare the newest design changes to prior performance. We can and should do comparisons well using the appropriate statistical approach.

Let’s examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests. Plus how to best use these tools and when to set them aside and explore another approach.

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Using FMEA (or Functional) Block Diagrams to Understand Your Item

podcast episode with speaker Chris Jackson

Many engineers rush to design or build something that we think is ‘awesome’ or at least ‘proves a concept.’ But this often means we build something that we like (not necessarily what our users like) or doesn’t work (because we didn’t realize that have sensitive electronic components near hot exhaust manifolds would be a problem). This is where taking a breath and understanding our product before we build the wrong thing fast can really helpful. A FMEA or functional block diagram can really help us visualize what different parts of our system do, and how they interact. They also help us identify the basic, interface and additional functions that separate an ‘average’ product from an ‘industry leading’ product. If this is something you think you or your team can benefit from, join us for this webinar.
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Fundamentals of Process Capability

podcast episode with speaker Fred Schenkelberg

Calculating and interpreting the process capability ratios is the easy part. Getting valid results takes more work and thinking. Knowing that the process is capable is only one use of this information. We should also use the information contained in these ratios to inform product design tolerance. [Read more…]

Using Monte Carlo Simulation
to Make Hard Reliability Analyses Easy

podcast episode with speaker Chris Jackson

Sometimes the equations we need to model reliability are just so complicated that we simply avoid them, or use other equations that are simpler but model the wrong thing (see some of my earlier webinars!). But it doesn’t have to be this way. Monte Carlo simulation is so simple that anyone who has access to Microsoft Excel can use it. What this means is that we don’t need to use complicated equations (like those use to model things like switching systems) and instead can use Microsoft Excel to help us get approximate (but really accurate) answers. Sound interesting? Join us for this webinar!
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