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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.
Hypothesis testing previously discussed (link to past posts) generally considered samples from two populations. Maybe the experiments explored design changes, different component vendors, or two groups of customers. Occasionally you may find data that has some relationship between the samples, or where the samples are from the same population. Paired (or matched) data involves samples that are related in some meaningful way. [Read more…]
Statistics is the language of variation. Everything varies, and we use variance (σ2) to describe the spread of the data. For any experimental work aimed at making improvements, whether in the design, manufacturing process or field performance, there are two ways to make improvements. Move the center of the distribution, or reduce the spread of the data. [Read more…]
This is also called the “p test”
When comparing proportions that are from a population with a fixed number of independent trials and each trial has a constant probability of one or another outcome (Bernoulli experiments) then we can use a p test. p is the probability of success, and 1-p is the probability of failure. Caution: stay consistent once you define success otherwise, like me, you’ll have a bit of confusion. n is the number of trials. [Read more…]
The design of a product includes the arrangement of all of the product elements. When considering the reliability of a system, the arrangement matters. Many systems are arranged serially. This means that with the failure of any one element, the system will not work. See the article on Series Systems for more details. [Read more…]
Design of Experiments (DoE) and the Analysis of Variance (ANOVA) techniques are economical and powerful methods for determining the statistically significant effects and interactions in multivariable situations. DoE may be utilized for optimizing product designs, as well as for addressing quality and reliability deficiencies. Within the DoE framework, the practitioner may explore the effects of a single variable or analyze multiple variables. [Read more…]
The Failure Reporting and Corrective Action System (FRACAS) is a closed-loop process whose purpose is to provide a systematic way to report, organize and analyze failure data. Implementation of a FRACAS has increasingly become commonplace within an industry. The requirement for implementation of some type of FRACAS within a DoD program was first established in 1985 with MIL-STD-2155. However, in 1995 that standard was reestablished with no changes to content as a handbook, MIL-HDBK-2155, and was recommended as guidance. Today, multiple software solutions exist that provide all the functionality required of a FRACAS. [Read more…]
After the system has been drawn in block diagram form, subsystem and component reliability goals and targets are established. This is a common practice in the development of complex systems, particularly when different design teams or subcontractors are involved. Reliability allocation involves setting reliability objectives for components or subsystems in order to meet a system reliability objective and should occur in the initial stages of design or prior to designing major system upgrades. [Read more…]
Creating a product or maintaining equipment is actually about our ability to manage risk. The various risks are outlined below, and there are more to consider. This summary covers the basics related to reliability. [Read more…]
This is a two part series where I outline the basic elements of creating and supporting a reliability program. [Read more…]
This is a two part series where I outline the basic elements of creating and supporting a reliability program.
For Reliability Engineers to converse with one another and with non-technical people in an organization, it is necessary for the language of reliability to be widely understood. These terms form the backbone of a working vocabulary and should be well understood by Certified Reliability Engineers.
Availability: Fraction of time that a system is usable. Steady state Availability = MTBF/(MTBF+MTTR) [Read more…]
A continuous distribution is useful for modeling time to failure data. For reliability practitioners, the Weibull distribution is a versatile and powerful tool. I often fit a Weibull when first confronted with a life dataset, as it provides a reasonable fit given the flexibility provided by the distributions parameters. [Read more…]
It is not enough to have a good mind; it is more important to use it well. — Descartes
Learning and Value
Over the past week, I’ve received a couple of questions about the pursuit of a graduate degree in reliability engineering and about preparing for the CRE. One question was particularly interesting – how will a reliability engineering graduate degree or CRE help my career? [Read more…]
In another post, I started the discussion about variability and interquartile range. This is part 2 of that discussion and will focus on variance.
With rare exception, most distributions or groups of data require more than one parameter (or statistic) to fully describe both the location and spread (scale and shape) of the group of data. Is the data clumped tightly about some value, or spread out over a wide range. [Read more…]
This week I received a question from the ASQ Librarian concerning a person’s question about one of the CRE Question bank questions. It was a nice two-part question concerning a hypothesis test of a sample means value and degradation.
Here’s the question as sent over for consideration. [Read more…]
