
Cluster Analysis and Applications
This webinar provides an accessible introduction to the principles and methods of cluster analysis and presents applications
Reliability Engineering Basics, Statistics, Accelerated Testing, Program Assessment and Improvement. Listen in on in depth discussions held during the live monthly Accendo Reliability webinar series. We explore topics ranging from reliability engineering basics, statistics, accelerated life testing, program assessment and improvement. Catch up or review past events below.
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This webinar provides an accessible introduction to the principles and methods of cluster analysis and presents applications

Compare RPN vs. Action Priority in our insightful webinar. Learn which risk assessment method best fits your organization.

AI and Reliability Engineering podcast episode with speaker Enrico Belmonte Artificial Intelligence is rapidly transforming engineering workflows, but its true impact may not be where many people expect. AI is increasing engineers’ learning speed, analytical capability, and productivity. Reliability engineering has traditionally required years of experience, deep statistical understanding, and…

From a statistical perspective, this is a clear ‘fingerprint’ of failures that are entirely dependent on maintenance.

Let’s examine the different ways one can listen, when it’s useful, and how to become a much better listener.

In this podcast let’s explore common types of capacitors, MLCC and Electrolytic, their basic construction, and how they may fail.

Let’s talk about the differences and how you can play an effective role as both a manager and a leader focused on improving reliability.

The basics of decision tree modelling and consider a simple demonstration of its application to assess imminent failure in automobiles.

This webinar shows you how to model switching (and other complex) systems using Monte Carlo Simulation in Excel with a perfect model.

Let’s explore how to work with suppliers to ensure the supplied items will meet or exceed your reliability expectations.

This webinar gives you 10 reasons why you should do FMEAs and FMECAs properly – and use AI to accelerate the process to amazing results.

Let’s explore what warranties are and are not, plus why they even exist. How are the terms of a warranty set, and by whom?

Let’s explore how a group’s culture affects its ability to create a reliable product or system. It’s part how we talk about reliability, what tasks, and tests we do.

The intent of any failure analysis is to understand the problem well enough to craft and implement short and long-term solutions.

‘parts count reliability prediction’ is awful. And in this webinar, we will explain why. If this intrigues you, enjoy this episode.

Let’s explore a few of the limitations, checks, and options when taking a look at some data. Checking assumptions and more.

Bugs are so common that we know how most of them happen. So we can work out what went wrong to allow that bug to happen.

Let’s explore the range of options available to estimate the life of an item, plus the pros and cons of each method.

Let’s explore when and how to identify which types of environmental testing should be done so that they add value.

So if you want to find out what reliability actually is (no equations) … this webinar is for you! - it's not MTBF, BTW

Let’s examine the success testing approach, the assumptions, benefits and faults. Plus, what other options you may have available

perhaps you want to estimate the reliability of something that is supposed to last a long time, but don’t have a lot of time to test.

Explore the framework to assess equipment reliability for air fin coolers and ensure operational excellence in process plants.

Ever heard of the MTBF? A lot of people have. But not many people (truly) understand what it is.

Let’s explore why derating is important, the difference it can make, and a few methods to implement derating with your design team.

Weibull probability plotting is perhaps the most widespread data analysis tool used in reliability and quality engineering.

Product requirements that have the most impact on customer needs should be considered in your design failure modes and effects analysis (DFMEA)

Reliability engineers are often taught about ‘cut sets.’ But we rarely use them. Many reliability engineers don’t know what they are.

Fundamentals of Metric Monitoring podcast episode with speaker Fred Schenkelberg Following along the idea stated by Lord Kelvin, “…when you can measure what your are speaking about, and express it in numbers, you know something about it…”, we have organizations measuring reliability performance. Not that measuring something is managing it, those are two different activies. […]

Want to understand the only way you should be generating confidence when it comes to reliability engineering?

Let’s discuss a couple of easy ways to accomplish reliability allocation or apportionment then examine a valuable way to use this tool.

Understand the lognormal distribution and its correlation to the bell curve. Harness this understanding to make crucial decisions.

We examine using our knowledge and the knowledge of others to streamline the testing or avoid it altogether.

Let’s explore the range of considerations when designing an ORT to optimize the ORT’s ability to identify field problems efficiently.

Let’s explore the concept of a delta phase and how to implement it in your organization. Plus, how to implement it in various product types.

Electronic component manufacturers use the term ‘Failures in Time’ of ‘FITs’ to describe the reliability of their products. But what is a FIT?

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

Understand the difference (if any) between FMEAs and FMECAs? … and How can you make an FMECA work for you?

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

Learn how fault trees can be used for conducting root cause analysis in this informative webinar from Accendo Reliability.

Let’s examine a few principles and tips so you can learn and master what you desire to learn and master.

Some of you might have heard of the ‘3 Parameter Weibull distribution.’ But what makes this different and (sometimes) helpful?

Let’s explore the basics of conducting Pareto Analysis, plus a few different ways to create and modify the plots.

You need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering.

Let’s examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests.

This is where taking a breath and understanding our product before we build the wrong thing fast can really helpful.

Let’s explore the steps necessary to obtain valid and valuable process capability ratios. Then, let’s examine how to use this information.

Sometimes the equations we need to model reliability are just so complicated that we simply avoid them. Let's use Monte Carlo instead.

Statistical control charting (SPC) is a method for monitoring and determining whether a process is in control or stable.

Greg will discuss the critical architecture and design practices that need to be considered in AI product development and deployment.