We talk about reliability because it matters. The ability to estimate reliability allows us to make design and development decisions. The ability to monitor reliability allows us to adjust the design, suppliers or expectations about a product. Continue reading Why do we talk about reliability?
Each of us have seen product life or component reliability claims on product literature or data sheets. We may even have received such claims stated as goals and been asked to support the claim with some form of an experiment. Standards bodies from ANSI, BSI, ISO, IEC, and others from around the world provide standard methods for testing products. This includes product life testing in some cases. Continue reading Question use of reliability testing standards
In light of the International Day of Failure, Oct 13th, let’s consider failure from a reliability engineer’s point of view. We work to understand and avoid product failures. When a product fails to deliver the desired performance attribute it is tossed away, returned, replaced, repaired, or tolerated. This may occur before or after the value of the product has been achieved. Continue reading International Day of Failure
Reliability, maintainability, availability, or the ‘ilities’ are common in our language with reference to products, services, equipment, and people. Joe is regularly available for the meeting; We can count on (depend or rely) Sara to finish the report on time; My car starts every morning without fail; and many more. What is meant with these concepts and specifically how do we manage achieving and sustaining business objectives related to these ‘ility’ concepts? The purpose of this short paper Continue reading What is Reliability
Kirk Gray, Accelerated Reliability Solutions, L.L.C.
In all aspects of engineering we only make improvements and innovation in technology by building on previous knowledge. Yet in the field of reliability engineering (and in particular electronics assemblies and systems), sharing the knowledge about field failures of electronics hardware and the true root causes is extremely limited. Without the ability to share data and teach what we know about the real causes of “un-reliability” in the field, it is more easily understood why the belief in the ability able to model and predict the future of electronics life and MTBF continue to dominate the field of electronics reliability Continue reading What will Advance Reliability Engineering?
Some many years ago I ran across a data sheet for a cooling fan (used to cool a desktop computer, for example) that listed the fan’s life as 50,000 hours MTBF. The big bold lettering was on the data sheet and was the only use of bold on the entire data sheet. One couldn’t miss it. The computers we used these fans within had a one year warranty, plus were expected to operate for a home computer user for about 5 years. Thus, we would expect the fan to also operate for five years without failure. Continue reading Datasheet MTBF
The term Bayesian Reliability Analysis is popping up more and more frequently in the reliability and risk world. Most veteran reliability engineers just roll their eyes at the term. Most new reliability engineers dread the thought of having to learn something else new, just when they are getting settled in the job. Regardless, it is a really good idea for all reliability engineers to have a basic understanding of Bayesian Reliability Analysis.
This series explains Bayesian Reliability Analysis and justifies Continue reading What’s All the Fuss about Bayesian Reliability Analysis?
Most of us have seen reliability specified using a requirement like the following:
The Zeus 5000 SUV shall have an MTBF of 144,269.5 miles with a 90% confidence.
Some readers may not have seen reliability requirements specified in any other way. What they have always seen has read something like: The widget shall have an MTBF of X with a Y% confidence. This reliability requirement structure is rather ubiquitous Continue reading The Worst Reliability Requirement
Just answered a question on where to find reliability engineering training on basics and statistics. There are plenty of options and below I’m listing just where to find the many, many options available to you. Continue reading 5 Reliability Training Options
Most reliability engineers are familiar with the life cycle bathtub curve, the shape of the hazard rate or risks of failure of a electronic product over time. A typical electronic’s life cycle bathtub curve is shown in figure 1. Continue reading Why The Drain in the Bathtub Curve Matters
| the following is a discussion on the sister Linkedin NoMTBF Group recently. It was and may continue to be a great discussion. Please take a look and comment on where you stand? Do you some form of the Arrhenius reaction rate equation in your reliability engineering work?Join the discussion here with a comment, or on the Linkedin group conversion.
Fred |
Hello, can anyone advise me how to calculate temperature acceleration factor for a complex system including cards, RF elements, cables, motors and moving parts? Is the Arrhenius model valid for such systems, or there are more precise models? Thank you! Continue reading Acceleration factors
Just a short post to point to a newly added paper to the reference section. A few years ago I recalled seeing a paper that studied the difference to expect between various parts count methods and actual results. Continue reading Parts count variation
Giving a presentation last week and asked if anyone uses an 85/85 type test, and a couple indicated they did. I then asked why?
The response was – just because. We have always done it, or it’s a standard, or customers expected it. The most honest response was ‘I don’t know’.
They why is the test being done? Who is using the information for a decision? What is the Continue reading What should we use instead of MTBF?
I’ve often railed on and on about the inappropriate use of MTBF over Reliability. The often cited rationale is, “it simpler”. And, I agree, making simplifications is often required for any engineering analysis.
It goes to far when there isn’t any reason to knowingly simply when the results are misleading, inaccurate or simply wrong. The cost of making a poor decision based on faulty analysis is inexcusable. Continue reading Use the right fit