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Prep notes for ASQ Certified Reliability Engineer exam ISSN 2165-8633
The idea of the CRE Preparation Notes series is to provide you short practical tutorials on all the elements that make up the ASQ CRE body of knowledge. The articles provide introductionary material, basics, how-to’s, examples, and practical use guidance for the full range of reliability engineering concepts, terms, tools, and practices.
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You will find the most recent tutorials in reverse chronological order below. Below each article is the section and specific clause of the CRE Body of Knowledge that tutorial addresses. Click on those tags to find other articles on the same topic. To the right on the sidebar, there is a listing of the 7 major categories in the body of knowledge - it's a quick way to find groups of articles on each specific area. You can also use the search function to locate articles, podcasts, or tutorials on specific topics.
In system modeling and fault tree analysis (FTA) we use a set of similar calculations based on Boolean logic, the AND and OR gate probability calculations. Within FTA, the AND and OR gates are just two of many possible ways to model a system. Within system modeling, often reliability block diagrams (RBD) we model parallel and series elements of a system.
In order to do these basic calculations, we need to consider a few assumptions then proceed to the math.
Not all risks the same. Some are minor with little consequence, while others are not. Every organization or reliability program facings a plethora of risks and being able to communicate the range of identified risks is helped by using a risk matrix.
The risk matrix is a simple two-dimensional grid that lays out on one access the expected consequence of risk, from minor to catastrophic. The other axis has the likelihood or occurrence of the risk becoming realized, ranging from rare too certain.
The boxes within the grid then contain classifications ranging from low to extreme, which provide a prioritization to address the risk in some fashion. Low-risk items are those with rare occurrences and insignificant consequences. The other end of the spectrum are extreme risks that are almost certain to occur and have catastrophic results. [Read more…]
When confronted with a stack of data, do you think about creating a histogram, too? Just tallied the 50th measurement of a new process – just means it’s time to craft a histogram, right?
There isn’t another data analysis tool as versatile. A histogram (bar chart) can deal with count, categorical, and continuous data (technically, the first two graphs would be bar charts). It like a lot of data yet reveals secretes of even smaller sets. A histogram should be on your shortlist of most often graphing tools. [Read more…]
The way we learn, prove our worth, and the nature of work are all changing. Professional societies are struggling to adjust to these changes. Universities and employers likewise are experimenting and exploring new ways to operate.
Over the past few months, I’ve received about a dozen inquiries on how to prepare for the ASQ Certified Reliability Engineer (CRE) exam in order to obtain the ASQ CRE certification. Many also asked if I had a course available. Thus, I decided to run a live course (learn more at the live course page – note: if you see this after the course start date we’ll have a sign up for those interested in future classes). [Read more…]
Sometimes we just need a simple plot of a few data points. When there is scant data a histogram or box plot just is not informative. This is a great use for a one dimensional scatter plot, dot plot, or a what is called a strip chart in R.
The basic idea is to see where the data lines along a line. For example, let say we have 20 times to first failure. A table of numbers is not all that helpful. We could explore using a cumulative distribution plot (Weibull analysis), yet it would be difficult to fit a distribution with so little data.
Let’s turn to a strip chart to get a look at the data. [Read more…]
In a meeting the other day, the presenter was talking about a range of different failures for the product in question. She talked about each issue, a bit about the failure analysis, yet didn’t reveal which failures occurred more or less often.
She did provide a handout with a listing of the problems in order of the product field age and listing of the failure name (component or system involved). So, I grabbed a piece of paper to create a frequency table so I could quickly determine which problems occurred more often than others. [Read more…]
The clever Dr. John Snow mapped cholera cases during the epidemic of 1854 on a street map of the area. This type of mapping now called a measles chart, or defect location check sheet, or defect map, is useful when exploring the effect of location data.
The name measles chart may have come from the habit of using an image of drawing of a product and adding small red dots to signify defect locations.
In brainstorming, you may face a large number of unique ideas even after affinity diagraming. Multi-voting is a great tool to gain consensus on the top priority ideas with your team.
For less than 10 or so items we could use a rank ordering method, yet that method becomes cumbersome when there are a lot of items to prioritize. There are a couple of ways to conduct multiple-voting. Mastering this technique will help your team quickly focus on what is truly important. [Read more…]
Received a question from a reader this morning that will make a nice tutorial.
A box contains 27 black and 3 red balls. A random sample of 5 balls is drawn without replacement. What is the probability that the sample contains one red ball?
So here’s my thinking and two ways to solve this problem. Instead of red and black balls in an urn type problem, which is pretty abstract, let’s say we know 3 bad parts are in a bin of 30 total parts.
Also called the Ishikawa or fishbone diagram, the cause and effect diagram is a graphical tool that enables a team to identify, categorize, and examine possible causes related to an issue. The intent is to expose the most likely root causes for further investigation.
This diagram is part of a complex failure analysis process when there are many potential causes for the problem or condition. Similar to a brainstorm session about the problem, this graphical tool provides a bit of structure and may prompt additional potential causes.
The Ishikawa diagram is one of the seven basic tools of quality control. [Read more…]
Sometimes a process doesn’t happen one step at a time. Sometimes, a problem we’re trying to solve has many moving and interacting elements.
Mind Mapping is a technique to capture those scattered thoughts, those non-linear processes, those myriads of interactions and dependencies. It’s a tool that is useful for brainstorming, organizing, and problem-solving. [Read more…]
There are two common uses for a check sheet. First, to summarize historical data, or second, to collect observations. A byproduct of creating a check sheet is team agreement on definitions of categories and observation procedures.
The investment is minimal other than thinking about how you want to view the data, and what data to collect. [Read more…]
When you have a scattering of ideas or suggestions, you can use affinity diagrams to organize and group them.
Affinity diagraming is a simple way for an individual or (better) a group to quickly gather and organize a large number of disparate concepts, ideas, suggestions, etc. It is a natural activity after a brainstorming session. [Read more…]
Did you know that best idea to solve a problem is often not the first one?
We all have plenty of bad ideas, hunches, guesses, and flawed ideas. That is ok. We also have great ideas and elegant solutions, too. The trick is exploring all those ideas to find the best ones.
One technique to draw out and capture many ideas is called brainstorming. You most likely have heard of and used this tool already. Let’s review a few key elements that make for excellent brainstorming results. [Read more…]
The Friedman test is a non-parametric test used to test for differences between groups when the dependent variable is at least ordinal (could be continuous). The Friedman test is the non-parametric alternative to the one-way ANOVA with repeated measures (or the complete block design and a special case of the Durbin test). If the data is significantly different than normally distributed this becomes the preferred test over using an ANOVA.
The test procedure ranks each row (block) together, then considers the values of ranks by columns. The data is organized in to a matrix with B rows (blocks) and T columns (treatments) with a single operation in each cell of the matrix. [Read more…]