Reliability Analysis … now what? Part 2

podcast episode with speaker Chris Jackson

Last month’s webinar was ‘Reliability Analysis … now what?’ And we showed how to slightly ‘tweak’ all those textbook reliability analyses into USEFUL ACTIVITIES. What good is a 90 % confidence bound on reliability? What does this mean for profit? Or fleet size? Or mission success? We solved this problem using a technique based on identifying the ‘likely’ ways we can explain our data. In fact – there is a whole bunch of statistics on creating the ‘likelihood’ on an explanation of what we see. And we use this ‘likelihood’ in most statistical applications – including those USEFUL ACTIVITIES we talked about above.

But what is this ‘likelihood’? What does it mean – particularly if I am trying to analyze data and turn it into something useful? Well … finding this likelihood ‘thing’ is much simpler than it sounds. And it is an essential part of turning a random bunch of failure data points (or something similar) into something you can base a decision on.

So in this webinar, we will show what this ‘thing’ is and how to turn any type of reliability data into that likelihood. Which is the next step on your journey to providing useful information to your decision-maker? Which also means YOU become more valuable!

This Accendo Reliability webinar originally broadcast on 22 September 2020.

Reliability Analysis … now what? Part 2Christopher Jackson

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Essential Reliability Engineering Techniques

podcast episode with speaker Fred Schenkelberg

The difficult part of creating this list of essential techniques is to avoid selecting just the most common. There is an overlap between essential and those commonly used, yet essential implies a technique is crucial. Crucial on rare yet very important situations. The idea for today’s discussion is to focus on those vital few techniques that I believe every reliability engineer must master.

The techniques I’ve settled on are not specific tools in most cases, instead they are the fields of knowledge or practice. For example, instead of suggesting Weibull analysis is essential, instead, I’m suggesting that math skills are essential. With sufficient math prowess, you can do a wide range of analysis and modeling.

Your science, engineering, and math formal training will serve you well as a reliability engineer, and that is not sufficient to be successful. Not every problem involves using a math technique, although it is common. You also need to master techniques in failure analysis and experimentation. Plus, please do not forget that we work with others, thus the essential techniques of persuasion and team building are likewise vital.

Let’s discuss this shortlist of essential techniques and consider why I suggest they are essential, plus explore others that you consider essential as well.

This Accendo Reliability webinar originally broadcast on 8 September 2020.

Essential Reliability Engineering TechniquesFred Schenkelberg

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Reliability Analysis … now what?

podcast episode with speaker Chris Jackson

Let’s say that you have some ‘reliability guys’ do some reliability analysis on reliability data … and they give you some numbers. Or a plot. Or a curve. Perhaps you are the reliability guy … and you do the analysis – and then what?

How do you use that probability plot to help you make a decision? How do you use confidence bounds, ‘p’ values, standard deviations, and so on to help you make a decision? The three most important things for reliability analysis are ‘the decision,’ ‘the decision’ and ‘the decision.’ So how do you convert reliability data analysis into useful information for that decision? … uncertainty and all? This webinar is for you!

This Accendo Reliability webinar originally broadcast on 25 August 2020.

Reliability Analysis … now what?Christopher Jackson

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Practical Use of Stress-Strength Models to Develop Specifications

podcast episode with speaker Rob Schubert

Warranty returns are a great place to start for setting targets for new products. But how do you translate that to specific numbers to design to? If you know the strength of a product and the return rate, you can develop stress profiles. If you have multiple similar products, your estimates can be even better. From the profiles, targets can be developed for future products to meet, and use them to calculate the expected return rates. You can even use these profiles to estimate the impact of design changes to warranty returns.

This Accendo Reliability webinar originally broadcast on 18 August 2020.

Practical Use of Stress-Strength Models to Develop SpecificationsFred Schenkelberg

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Selecting Reliability Engineering Tools

podcast episode with speaker Fred Schenkelberg

Everything will eventually fail. I like to say that keeps us in business as reliability engineers. The trick is knowing what will fail and when. There are many potential causes for a product or system to fail. There are design flaws, supplied component latent defects, assembly damage, and unexpected applied stresses.

The key to take-away from this concept is we can learn when studying failures. We can work to prevent or delay specific types of failures. By learning about failures, we learn how to create reliable products.

Let’s discuss the concept of failures along with a few other concepts universal to reliability engineering. Understanding the foundational concepts for our work can only assist you in your work.

This Accendo Reliability webinar originally broadcast on 11 August 2020.

Essential Reliability Engineering ConceptsFred Schenkelberg

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So what is up with this ‘Bayesian’ analysis stuff

podcast episode with speaker Chris Jackson

Some of you may have heard of ‘Bayesian analysis.’ You may think this is something fancy that only universities do. Or something we never do because it is all about ‘best guesses.’ Well … neither of these things are true.

Why would you be interested in Bayesian analysis? Simple. It allows you to use EVERY PIECE OF INFORMATION you have. This can be expert judgment. Or it can be test data on a similar ‘thing.’ Or it could be combining test data for one part of your ‘thing’ combined with test data for ‘all of your thing.’

Still not excited? Those of you who have to pay for and do testing or data analysis might. Bayesian analysis may shave days, weeks, months or years of your test schedule. And a lot of money. Listen to this webinar to learn more.

This Accendo Reliability webinar originally broadcast on 28 July 2020.

So what is up with this ‘Bayesian’ analysis stuffChristopher Jackson

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The Survivorship Bias Principal

podcast episode with speaker Adam Bahret

In 1942 the US Air Force needed to figure out a way to get more of their bombers home. They were losing them at an atrocious rate. They made a study of where the returning bombers were being hit, it was a great data set. But they made a big mistake in interpreting that data. It was Abraham Wald, a mathematician, who corrected their assumptions and created the “Survivorship Bias principal.” This principle has changed the way we look at data sets and trends. It is a concept that I apply to field failure data sets regularly. More than once it has caught evidence of core issues that would have otherwise been missed.<!–more–>

This webinar will open your eyes to this important perspective. its’ so simple and has made many heroes in the data analysis world since Abraham Ward. If you analyze data or even simply manage teams who use data, then this webinar is for you. Learn how your data sets are telling you much more about your field failures than you think.

This webinar is for anyone who works with or manages programs that use data. There are no math or statistics prerequisites. We are covering a philosophy.

This Accendo Reliability webinar originally broadcast on 21 July 2020.

The Survivorship Bias PrincipalAdam Bahret

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Selecting Reliability Engineering Tools

podcast episode with speaker Fred Schenkelberg

The toolbox for reliability engineering work is large. We have tools for risk management, data analysis, failure analysis, team building, and more. We touch on material science at the molecular level then shift to assessing a vendor’s reliability program. When you use which tool is critical to your effectiveness. So, how do you determine which tool to use for a given situation?

Let’s explore a few different situations and step through the decision process to determine which tool to employ. You may need to learn how to use a new tool or set of skills, or modify how you use an existing tool, or simply apply what you already know how to do.

The selection hinges on knowing what is available, understanding the current situation, and available information, plus how well will a particular approach work in your organization. Choosing the right tool requires matching the type and complexity of the problem and the situation at hand.
Let’s discuss how to best enable you to always apply the right tool to get the best results in this interactive and practical event.

This Accendo Reliability webinar originally broadcast on 14 July 2020.

Selecting Reliability Engineering ToolsFred Schenkelberg

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The Reliability Value Map. It is a thing.

podcast episode with speaker Chris Jackson

If reliability engineering ends up costing you money, then you are doing it wrong. But chances are that someone you work for looks at reliability engineering as a black hole of costs. This needs to stop!

Reliability engineering is about creating value. Or money. Or more missions. Or safety. But you need to show how this will happen.

This is where a Reliability Value Map helps. Put simply, it is an organized chart that helps you track down every possible ‘good’ thing reliability can do for you. And how you ‘measure it’ to put it into a business case. And once you know the sources of value – the decision should become easy. Want to learn more? Listen today!

This Accendo Reliability webinar originally broadcast on 23 June 2020.

The Reliability Value Map. It is a thing.Christopher Jackson

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Overview of Life Testing in Minitab

podcast episode with speaker Rob Schubert

Many companies haven’t the resources to purchase much more expensive software specifically for reliability, but many have the quality software Minitab. Minitab itself has many reliability functions available; this presentation covers the basics, beginning with “individual distribution identification” to ensure your data fits one of the reliability models. Data is then analyzed with parametric distributions (right censoring vs arbitrary censoring). Additionally, the accelerated life testing functions are explored focusing on the interpretation of the results. This is presented with practical examples for clarity.

This Accendo Reliability webinar originally broadcast on 16 June 2020.

Overview of Life Testing in MinitabFred Schenkelberg

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What to Do About MTBF Use

podcast episode with speaker Fred Schenkelberg

While the NoMTBF movement is making progress, we still find those that seem to want to use MTBF (or MTTF). As you know, MTxx type metrics are means, they contain little information and are generally misunderstood and misused. So, what should a well-educated practitioner do?

Let’s discuss a few ways you can and should respond to requests for MTBF? How to ask vendors, or anyone, for reliability information by not asking for nor accepting MTBF. Plus, let’s brainstorm and outline a few steps each of us can do tomorrow, and every day, in order to minimize the misuse of MTBF and related measures.

This Accendo Reliability webinar originally broadcast on 9 June 2020.

What to Do About MTBF UseFred Schenkelberg

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Optimizing Servicing Intervals and Witchcraft. There actually is a difference.

podcast episode with speaker Chris Jackson

Ever wondered if your servicing intervals are ‘good’? Do you know what ‘good’ is? Are you servicing too much or too little? What happens if you service too much? Do you use some basic equations in textbooks and plug in numbers which seem too simple and basic AND you don’t understand them (all at the same time)?

If you have asked yourselves any of these questions, then this is the webinar for you. A really simple, never done this before, please join me in the discussion on what it actually means to optimize servicing intervals.

There is some basic statistics involves (… there has to be). But it doesn’t need to be that hard. And the reality is that most manufacturers don’t really know how you are going to use their product – so they always ask you to service too much. Which makes it LESS reliable. Want to learn more? Click here!

This Accendo Reliability webinar originally broadcast on 26 May 2020.

Optimizing Servicing Intervals and Witchcraft. There actually is a difference.Christopher Jackson

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To view the recorded video/audio of the event visit the webinar page. PDF of slides and article mentioned also available on the webinar page.

PDFs, CDFs, and other ‘Fs’
What the hell are they?

podcast episode with speaker Chris Jackson

Ok. They say there are lies, damn lies and statistics. And at the heart of statistics are these intimidating functions like ‘probability density functions’ and ‘cumulative distribution functions.’

They mean something – but are practically useless unless they help inform a decision. And we as engineers are supposed to know what these functions mean. But have you ever sat in a meeting or presentation where you realized there were some gaps in your knowledge? … or perhaps you felt like you were given too many charts but not enough help to make your decision?

If you want a really easy introduction or review of these functions – then check out this webinar!

This Accendo Reliability webinar originally broadcast on 28 April 2020.

PDFs, CDFs, and other ‘Fs’ — What the hell are they?Christopher Jackson

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How to Learn Reliability Engineering

podcast episode

It’s not possible to point to one moment, class, seminar, workshop, or conference where I learned reliability engineering. Not one situation, project, conversation, or meeting either. Learning reliability engineering is a journey and each is different. [Read more…]