
A foundational element of probability and statistics is counting. How many ways could something occur? A simple example is a pass or fail criteria, thus when evaluating a product there are two possible outcomes. [Read more…]
Your Reliability Engineering Professional Development Site
Author of CRE Preparation Notes, Musings", NoMTBF, multiple books & ebooks>, co-host on Speaking of Reliability>/a>, and speaker in the Accendo Reliability Webinar Series.
This author's archive lists contributions of articles and episodes.
by Fred Schenkelberg Leave a Comment
A foundational element of probability and statistics is counting. How many ways could something occur? A simple example is a pass or fail criteria, thus when evaluating a product there are two possible outcomes. [Read more…]
by Fred Schenkelberg 7 Comments
In those situations where we sample without replacement, meaning the odds change after each sample is drawn, we can use the hypergeometric distribution for modeling. Great, sounds like statistician talk. So, let’s consider a real situation. [Read more…]
by Fred Schenkelberg 2 Comments
Let’s say the results of software testing averaged three defects per 10,000 lines of code. The criteria for release is 90% probability of 5 or fewer defects per 10k lines.
If this product ready for release?
The Poisson distribution is appropriate here as it is useful for modeling defects per unit, count per area, or arrivals per hour. If the data, in this case, the defect count per lines of code to be modeled by the Poisson distribution, the probability of an occurrence (defect in this case) has to be proportional to the interval (lines of code in this case). Also, the number of occurrences (defects) per interval must be independent (more on statistical independence in another post). [Read more…]
by Fred Schenkelberg 17 Comments
The lognormal distribution has two parameters, μ, and σ. These are not the same as mean and standard deviation, which is the subject of another post, yet they do describe the distribution, including the reliability function. [Read more…]
by Fred Schenkelberg 11 Comments
The other day I got a question about the difference between ALT and HALT. There was some confusion probably because of the similar words in the acronym. ALT is Accelerated Life Test, and HALT is Highly Accelerated Life Test. [Read more…]
by Fred Schenkelberg 7 Comments
Failure mode and effects analysis, or FMEA, is a tool for the identification and prioritization of possible ways a product or process can fail. The intent is to use that information to make improvements to the product or process.
I think of FMEA (and related processes like FMECA, dFMEA, etc.) as structured brainstorms that provide a means to focus on what’s important. [Read more…]
by Fred Schenkelberg Leave a Comment
The reliability goal is a key element across the entire product lifecycle. From product definition to determining warranty to judging performance, knowing the goal in clear terms sets the stage for a successful product.
Reliability in engineering terms is the probability of satisfactory product performance within a defined environment over a stated duration. [Read more…]
by Fred Schenkelberg 5 Comments
There a few different ways to sample a lot (or group) of material to determine if it has an acceptably low failure rate (or proportion that are considered ‘bad’). The following is an example of the sequential sampling method, which happens to be rather efficient by generally using the fewest samples for the same risk protection. [Read more…]
by Fred Schenkelberg 2 Comments
First the Question:
Fred,
Early in the FMEA lecture you worked through a homework problem and you mentioned that a cdf may not be linear (hence the reason for giving three points in a reliability goal). Can you give an example of two of things you’ve seen with non-linear cdf’s? I’ve only done limited reliability testing at this point, but everything I’ve done and every example I’ve ever seen have had linear cdf’s.
Thanks,
John
And, my response: [Read more…]
by Fred Schenkelberg Leave a Comment
EAM & CMMS Systems, 10 times more data in the system or 10 time less done with the data available?.
A nice short article about the problem of data, data, too much data.
by Fred Schenkelberg Leave a Comment
The CRE_Errata_9-26-2011_revised document is in pdf format and contains a couple of typos noted by John Cooper in the Indiana Council CRE prep materials – he has taught the CRE Prep course for Ops A La Carte and is a pretty good teacher and a CRE. [Read more…]
by Fred Schenkelberg 2 Comments
Recently a colleague sent me a published copy of the first CRE exam. Scanning through the document suggests that a few things have changed and many have not changed at all. I often comment my enjoyment of the reliability engineering profession, as it doesn’t change too fast and even I can keep up. [Read more…]
by Fred Schenkelberg 3 Comments
A reliability block diagram (RBD) for a product that has no redundancy or complex use profile is often very simple. A series system (reliability wise) implies that any one part or element of the product that fails the entire product fails. One might ask if an RBD is even necessary. [Read more…]
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…]