Your Reliability Engineering Professional Development Site
This is part of a short series on the common distributions.
The Uniform distribution is a univariate continuous distribution. This short article focuses on 7 formulas of the Uniform Distribution. A common application is as a non-informative prior. Another application is to model a bounded parameter. The uniform distribution also finds application in random number generation. [Read more…]
This is part of a short series on the common life data distributions.
The Poisson distribution is a discrete distribution. This short article focuses on 4 formulas of the Poisson Distribution. It is also known as the rare event distribution. It has application in a homogeneous Poisson princess and with renewal theory. [Read more…]
In most organizations being a reliability engineer is a lonely position. I like to think we’re so effective that one or just a small team is all any an organization needs.
As with any engineering position, we have specialized training and skills. We view the world and problems just a little differently than others. Then we use statistics, which tends to future isolate us from our peers.
For over 50 years there have been professional societies focused on supporting the professional education of reliability engineers. For nearly as long there have been trade journals and newsletters. Longer for technical journals and other scientific and engineering organizations and journals. [Read more…]
This is part of a short series on the common life data distributions.
The Pareto distribution is a univariate continuous distribution useful when modeling rare events as the survival function slowly decreases as compared to other life distributions. This short article focuses on 7 formulas of the Pareto Continuous Distribution also known as the Pareto distribution of the first kind (there are three kinds, apparently). [Read more…]
The quality triangle is an admission that every project has design constraints. Note that reliability is rarely listed directly within the triangle, yet reliability does impact each element of the triad.
In a world where the design team is beset with numerous design for X priorities, understanding how reliability related to the top three and most common set of constraints is imperative.
For any set of priorities, you should be able to convey how addressing reliability performance in the design and assembly process impacts those priorities. Addressing reliability can improve quality, reduce the risk of launch delays, and reduce the cost of a product. All this and improve customer satisfaction as well.
Let’s explore a few ways you can connect reliability priorities to the common quality triangle priorities. [Read more…]
We make decisions every day. Our project teams and organizations have many individuals making decisions every day. Most of these decisions have little to do with product reliability, yet a surprising number of design, marketing, production, and customer care decisions that have a direct impact on product reliability performance.
As a reliability professional, do you work to make better decisions? Do you work to enable the individuals designing, producing, marketing, etc your organization’s products to make better decisions concerning reliability?
If not, why?
Let’s outline a few ways to estimate the value to you and your organization to improve decision making concerning reliability. [Read more…]
This is part of a short series on the common life data distributions.
The Binomial distribution is discrete. This short article focuses on 4 formulas of the Binomial Distribution.
It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]
This is part of a short series on the common life data distributions.
The Birnbaum-Saunders distribution is a univariate continuous distribution. This short article focuses on 7 formulas of the Birnbaum-Saunders Distribution. This distribution was designed to model the Miner’s rule, thus allowing for non-constant fatigue cycles through accumulated damage.
If you want to know more about fitting a set of data to a distribution, well that is in another article.
It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]
This is part of a short series on the common life data distributions.
The Beta distribution is a univariate continuous distribution. This short article focuses on 7 formulas of the Beta Distribution.
If you want to know more about fitting a set of data to a distribution, well that is in another article.
The Beta function is not used to describe life data very often yet is used to describe model parameters that are contained within an interval. For example given a probability parameter constrained from 0 ≤ p ≤ 1 the use of the Beta distribution is well suited to model such a parameter.
The Beta distribution is also known as a Pearson Type I distribution. [Read more…]
This is part of a short series on the common life data distributions.
The Logistic distribution is univariate continuous distribution. This short article focuses on 7 formulas of the Logistic Distribution.
If you want to know more about fitting a set of data to a distribution, well that is in another article.
It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]
This is part of a short series on the common life data distributions.
The Normal distribution is a continuous distribution widely taught. It is commonly used to describe items, measurements, or time to failure data when there are many additive perturbations that comprise the results. This short article focuses on 7 formulas of the Normal Distribution.
If you want to know more about fitting a set of data to a distribution, well that is in another article.
It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]
Reliability engineering includes delivering bad news. This piece of equipment will fail soon, this design won’t survive outdoor use.
We start early with engineering judgment on design weaknesses. Continue by organizing groups to evaluate and comment on what will likely fail. We test, prod, poke and force failures to occur. Then we tally the actual performance and compare that to the what we hoped.
We are the bearers of bad news all too often.
So how do you avoid the stigma attached to that bad news? [Read more…]
This is part of a short series on the common life data distributions.
The Lognormal distribution is a versatile and continuous distribution. It is similar to the Weibull in flexibility with just slightly fatter tails in most circumstances. It is commonly used to describe time to repair behavior. This short article focuses on 7 formulas of the Lognormal Distribution.
If you want to know more about fitting a set of data to a distribution, well that is in another article.
It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]
Engineers solve problems. We optimize solutions.
Engineering starts with a question. The work of engineering is answering those questions. Can we create an antenna with enough range? How can we make a safe autonomous driving car? How much can a delivery drone carry if it has a range of 100 miles?
Reliability engineers are no different. We ask questions and work to answer them. To solve the problems in the pursuit of providing our customers reliable solutions.
In general, there are only a few types of questions a reliability engineer addresses: What will fail, when, and what is the impact of a failure.
The answers are used to design reliable products, optimize supply chains and assembly processes, refine warranty accruals, and identify significant business risks. [Read more…]