
This is provided courtesy of Amanda at
Egerton Consulting Ltd
Visit our website at www.egertonconsulting.co.uk
<They have a great newsletter and worth subscribing. Fred> [Read more…]
Your Reliability Engineering Professional Development Site
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by Fred Schenkelberg 2 Comments

This is provided courtesy of Amanda at
Egerton Consulting Ltd
Visit our website at www.egertonconsulting.co.uk
<They have a great newsletter and worth subscribing. Fred> [Read more…]
by Fred Schenkelberg 33 Comments

Let’s say we have a product that most often fails for one major component. Let’s say a fan (it could be anything, and while I don’t have anything against fans, it’s easy to picture).
Ok, this fan has a data sheet with the classic reliability claim of 50,000 hours MTBF. For those that know about my disdain for MTBF (www.nomtbf.com) rest assured I’m not going to get into it here. The basic approach for estimating the number of failure during any [Read more…]
by Fred Schenkelberg 3 Comments
A part of the preparation for the ASQ CRE is experience and education. These, in my simple way of thinking, means applying what you have learned to solve problems and provide value. Reliability engineering is about two questions: [Read more…]
by Fred Schenkelberg 5 Comments

Hi Fred,
I would take this opportunity to ask the reliability guru about bathtub curve for hardware reliability. I am running 27 units for life test for a million cycles around 555 hours. I have one failure at 300,000 cycles, and the rest of the units are running fine. Would this be classified as an early life failure? Also, how do I make a determination of when the early life failure time interval ends and constant failure rate starts in this example based on failure rate of remaining units? Thanks. [Read more…]
by Fred Schenkelberg 2 Comments

Update:
I forwarded the note below to QCI for comment and asked if they have an errata available. They do.
The QCI errata is posted on [the] website. [Read more…]
by Fred Schenkelberg 4 Comments

Reading a datasheet to determine a reliability value may take some investigative work. Whenever I see a fit rate based on failure-free testing, I am curious about how they did the testing and the calculations. [Read more…]
by Richard Coronado 2 Comments

During design and development, Reliability Engineers often receive reliability parameters in many forms. The most common reliability parameter is the mean time to failure (MTTF), which can also be specified as the failure rate (this is expressed as a frequency or Conditional Probability Density Function (PDF)) or the number of failures during a given period. [Read more…]
by Fred Schenkelberg 5 Comments

Speaking reliability-wise, parallel, means any of the elements in parallel structure permit the system to function. This does not mean they are physically parallel (in all cases), as capacitors in parallel provide a specific behavior in the circuit and if one capacitor fails that system might fail.
In this simple drawing, there are n components in parallel and any one component is needed for the system to function. [Read more…]
by Fred Schenkelberg 1 Comment
The annual salary survey done by American Society for Quality (ASQ) is summarized in the December 2011 issue. And, the good news is a CRE certification provides approximately a $21k salary premium over those in similar positions without the certification. Based on Table 2. salary premiums for certification holders in the article, Land the Big One, indicated the largest premium is [Read more…]
by Fred Schenkelberg 1 Comment

Each piece of gear used in rock climbing has the potential to be the weakest link. Often, based on accident reports, it the human decisions or lack of focus that is the most difficult to improve.
Ropes, anchors, harness, and carabiners and another equipment all have to work in the event of a fall. The design of each piece of equipment is to meet and hopefully exceed any possible load. And, to maintain the needed strength over years of harsh outdoor use. [Read more…]
by Fred Schenkelberg Leave a Comment

Reaching for a goal may include taking some risks. In reliability testing, we are often limited by the number of samples available for testing. And, in the case where time is available or the acceleration factor is high we can take advantage of testing longer. [Read more…]
by Fred Schenkelberg 2 Comments

One of the most often asked questions of reliability professionals (or statisticians) is related to how many samples for a test? This typically is not an easy question to resolve without some work and knowledge of the testing in question. We are often asked anyway, and expected to have an answer.
While not the most often asked question on the CRE exam, you might see something related. Budget planning, prototype counts, test equipment sizing, etc. all need an estimate for sample size. [Read more…]
by Fred Schenkelberg 3 Comments

Diverging from reliability statistics for a post or two, let’s consider one way which R(t), reliability at time, t, is useful during the design phase of a product. Apportionment is the breakdown or allocation of reliability goals or objectives to elements within the product.
Overall, the product’s reliability is just one number, and it represents what the customer will experience with the product. During design, we often work on subsystems and components. Having a meaningful way to describe the reliability requirements that also assists the team to meet the overall product goal, is, well, useful. [Read more…]
by Fred Schenkelberg 5 Comments

“Statistics is the language of variation.” I’m sure that is a quote by someone, not me, though. It is true. Statistics is all about variation. In this post let’s explore some of the ways statisticians talk about data and specifically the amount of dispersion in the data. [Read more…]
by Fred Schenkelberg 1 Comment

This is hopefully completely a review. The mastery of basic statistical terms is important as many of the questions on the CRE are statistical in nature and rely on your understanding the terms. Let’s simply review the terms, and do let me know if you have any questions.
Let’s take a random sample from a population. Given a [Read more…]