Your Reliability Engineering Professional Development Site
Let's have an in-depth discussion during the live webinar series events: Reliability Engineering Basics, Statistics, Accelerated Testing, Program Assessment, and Improvement. Catch up or review past events below.
To attend an upcoming live event, visit the Live Events section of the site, which lists the available upcoming webinars. Recordings are available via recorded videos or audio only via the podcast show.
Find one that looks interesting and register for the event. You will receive login directions and reminders prior to the event. Plus you will be able to join the discussion during the event.
You may already know my position on MTBF.
If not, do not use MTBF at all, ever, in any form. So what should we use instead?
I suggest using reliability, the probability of success over a specific duration.
Let’s discuss what will work for you.
Early and often during product development, the team needs to know the expected reliability performance of the current design. The values provide information to make decisions.
We can create meaningful estimates. Or not.
Selecting as a supplier for components or subsystems involves many aspects, including the desired reliability performance.
Once selected, the ability of the supplier to provide items that meet or exceed the reliability requirements relies on their understanding of the requirements and operational conditions related to the specific item within the system.
It also relies on the supplier’s knowledge of their own design and manufacturing processes as it relates to reliability performance.
A common request of reliability professionals is to design a set of reliability tests.
Many rely on standards, such as 85°C / 85%RH, to determine if a system is reliable, yet the standards do not provide a means to translate the results to your specific situation.
When components fall outside specs, the chance for quality and reliability issues increases.
Let’s explore some design and manufacturing cases where effectively using statistical process control will enhance your product’s reliability performance.
A tolerance specification is how we communicate the allowance for part variation.
Variation happens, and when it is within what we expect, great. Otherwise, quality and reliability issues ensue. Let’s explore how to set tolerances to improve reliability properly.
Let’s understand the process data, stability, and design constraints in an attempt to find a balance to create meaningful tolerances.
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We work on projects to improve reliability.
There may not be the field data immediately available. Let’s explore how you can improve the overall program while delivering on your project.
Specifically, what’s with cost and procurement?
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How do you use the Weibull Distribution?
It’s just one of many useful statistical distributions we must master as reliability engineers.
Let’s explore an array of distributions and the problems they can help solve in our day-to-day work.
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Looking for an inexpensive and powerful data analysis tool?
R is free. R is an open source statistical programing language.
Let’s explore R’s many capabilities concerning reliability statistics from field data analysis, to statistical process control.
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Mastering the statistical tools related to reliability engineering allows you to master reliability.
Identifying, characterizing, understanding, predicting, and improving reliability all require statistics. Let’s discuss how it works and what will work for you.
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Every project and program includes reliability engineering.
This may be obvious with a structured program and reliability plan or may be unspoken. The product or system will have some level of reliability performance whether or not anyone is overtly working to achieve a reliability goal.
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There are many reasons to use accelerated testing and just as many ways to conduct the testing.
Matching and balancing cost, risk, and results takes some skill.
Let’s talk about the key elements to consider so you select the best approach for your test.
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We often want to know if our product will work as expected in our customer’s environment.
Creating an environmental test plan that clearly shows weaknesses and strengths should be part of your program for each product.
Let’s explore the steps and resources you should consider when creating an environmental test plan for each product.
We will discuss why using standards or even the plan from the last program may not provide you meaningful information.
Understanding how your product responds to your customer’s environment provides the information for your team to make improvements and improve product reliability.
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Reliability and test planning takes time and it’s easy to use the plan worked out for the last program.
Yet this doesn’t consider the new risks or technology or use conditions that impact product reliability.
If you find resistance as you propose improvements to the reliability plan or to the test plan, what can you do to gain acceptance?
If the source of resistance that what we did last time worked, why change, then what steps can you take to secure support for the needed changes?
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Each product development project is different.
Different features, customers, use cases, and expectations. Let’s discuss how to build a custom reliability program that fits your specific situation.
“Insanity: doing the same thing over and over and expecting different results.”
– attributed to Albert Einstein, basically describes many organizations’ reliability project plans.
The idea that a set of activities will effectively address all of the reliability risks of a new design is too common across industries.
Why is this?
Let’s explore recognizing the current situation and which activities provide the most value.
The focus should be on creating a product that meets customer and business expectations with the lowest risk and cost.
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