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Prep notes for ASQ Certified Reliability Engineer exam ISSN 2165-8633
The CRE Preparation Notes series provides you with short practical tutorials on all the elements that make up the ASQ CRE body of knowledge. The articles provide introductory material, basics, how-tos, examples, and practical use guidance for the full range of reliability engineering concepts, terms, tools, and practices.
Keep your knowledge fresh by regularly reviewing topics and tools that make up reliability engineering.
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You will find the most recent tutorials in reverse chronological order below.
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…]
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…]
This is part of a short series on the common life data distributions.
The Exponential distribution is popular and useful in isolated situations. It has some nice features and flexibility that support it’s popularity. This short article focuses on 7 formulas of the Exponential 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 Gamma distribution is routinely used to describe systems undergoing sequences of events or shocks which lead to eventual failure. Also used to describe renewal processes. This short article focuses on 7 formulas of the Gamma 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 Weibull distribution is both popular and useful. It has some nice features and flexibility that support its popularity. This short article focuses on 7 formulas of the Weibull 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…]
On occasion, we want to estimate the reliability of an item at a specific time.
Maybe we are considering extending the warranty period, for example, and want to know the probability of no failures over one year instead of over the current 3 months.
Or, let’s say you talked to a bearing vendor and have the Weibull parameters and wish to know the reliability value over 2 years.
Whatever specific situation, you have the life distributions parameters. You just need to calculate reliability at a specific time. We can do that and let’s try it with three distributions using their respective reliability functions: exponential, Weibull, and lognormal. [Read more…]
Identifying risk is an important first step. It is not sufficient though.
Taking steps to deal with risk is an essential step. Knowing about and thinking about risk is not the same as doing something about risk.
Risk will occur. Some good, some bad. Some minor, some catastrophic. Your ability to mitigate risk allows you to proactively acknowledge and accommodate risks. Let’s talk about four different strategies to mitigate risk: avoid, accept, reduce/control, or transfer. [Read more…]
Planning and Implementing a risk management framework is an admirable accomplishment. Now make sure it is running well and will do so into the future.
As with any process, there will be opportunities to make improvements. By monitoring and reviewing your program you will find what is working well and what is not. [Read more…]
With the advent of ISO 31000 and other ISO standards suggesting organizational risk management practices, your organization may have or soon will implement a risk management plan. Reliability of your products, systems, or assets is an element of the organization’s risk profile.
As reliability professionals, your knowledge and skills are a natural fit within any risk management plan. You may focus exclusively on the reliability performance-related risks You may find the skills and tools to identify and mitigate risks play an important role beyond just reliability performance.
Large and small organizations face risks. The lines of communication differ as do the context, culture, and management practices between any two organization. The implementation of a risk management plan has to fit your organization.
Here are few general guidelines and practical considerations when implementing your organization’s risk management plan. [Read more…]
The uncertainty concerning the future performance of a product or system is a risk to the customer and supplying organization. A product that fails too often or in an unsafe manner may require repair, replacement, or a recall.
A product’s performance including its reliability performance reflects on the organization that designs, builds, and sells the product. A poor reliability performance is no longer a risk to that individual product, rather it is a risk to the product line and organization as well.
Reliability professionals have long been involved with identifying and mitigating risks. The increased emphasis on enterprise risk management through standards such as ISO 31000 require reliability professionals to consider the larger risk management framework and how reliability related risks fit within the larger context. [Read more…]
The risk management framework in ISO 31000 provides a flexible approach to create the right program for your organization. The document doesn’t provide advice or wisdom, so you have to supply that yourself.
The details of the risk management program or specific framework in your organization includes policies, procedures, analysis, and reporting, yet it also has to work within the context of your organization.
Based on the work of Greg Hutchins in ISO 31000: Enterprise Risk Management here are four considerations to supplement your wisdom as you design and implement your program. [Read more…]