Your Reliability Engineering Professional Development Site
We’ve collected data and it’s time for the analysis.
As you may recall, in the last article on Planning a Taguchi L4 Array Experiment, we drafted a set of four prototypes. The specific arrangement of factors and levels will now allow us to analyze each factor separately.
The intent is to find the optimal level or setting for each factor, plus which is the most important factor. [Read more…]
In deciding what industry you want to work as a reliability engineer, it is always good to have an understanding of what functional responsibilities you are expected to execute as a part of the job function.
You should always carefully review the job description then compare your knowledge acquired through training and on-the-job experience and ask yourself if you are capable of performing functions required without additional training.
Furthermore, we need to consider our technical limitations and at the same time be aware that the job description provided may not exclusive represents all the tasks you are expected to perform. [Read more…]
Tim and Fred discuss the tendency to look for quick answers when analyzing quality failures, often overlooking the true root cause which may have more to do with internal culture.
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One of the simplest ways to learn design of experiments, DOE, is to just give it a try.
The Taguchi DOE approach uses orthogonal arrays. This subset of the possible approaches to DOE simplifies the process to create and analyze experiments.
Let’s plan a simple experiment using the Taguchi DOE approach. [Read more…]
It’s been almost a year since launching Accendo Reliability. It’s been fun, exciting, and weekly.
Love it and really enjoy helping you answer questions, get stuff done, and master reliability engineering.
Since my wife and I just bought a house (out playing Pokemon Go when we stopped for an open house – and a week later our offer was accepted). Now we’re preparing to move ourselves to our new home.
There is a lot involved. [Read more…]
When we understand how something fails, we can create a mathematical model of the effect of stress or load on the time to failure behavior.
The model may take different forms, yet it is the ability to related the conditions surrounding the use of a device to its eventual demise that is essential. The specifics include a molecular level of detail in some cases.
Physics of Failure models focus on the particular relationships between stresses and materials. [Read more…]
Not much. You need just enough field failure data to identify the root cause and determine if and how to resolve the problem.
Field data will accumulate even if your program works diligently to prevent failures.
The actions taken before the reported failure will frame when you need to take action.
Gathering failure data and evaluating the trigger points for action is a reactive approach. This approach means you will only respond to problems.
You will also likely not spot the important emerging issues before they become significant problems. [Read more…]
As with strength-strength analysis, derating is a means to design robust systems.
Derating is an intentional process applied to every component of a product to reduce the opportunity of a component witnessing more stress than it is capable of withstanding.
The additional robustness also reduces the amount of damage the stress may impart, thus prolonging the life of the component. [Read more…]
The component choice an electrical engineer starts with the functional requirements of the circuit. Another consideration is the rated values of the specific component selected.
Derating guidelines provide information to compare the component rated values to select stresses or conditions. The intent is to assist the engineering team to select robust enough components for the application.
Robust here implying the component within the circuit will operate for a suitable length of time. [Read more…]
The ASQ CRE Exam is daunting.
While you may desire to become certified, you also know the CRE body of knowledge is broad. The exam is 150 questions in four hours that may tax your ability to achieve a passing score.
There is a lot to know in reliability engineering. Your journey of learning really never ends. [Read more…]
Data and the analyses that use the data can be tricky to manage at best, let along extremely difficult.
In this last post of the series on using the maintenance data you have, Fred and James will answer many of the common questions asked about data and the analyses. [Read more…]
By the time a product fails in the field, the design team is focused on the next design.
They are looking to the future and not looking for field reliability feedback. We know that each failure contains valuable information.
We, as reliability professionals, often work to create as much useful information concerning failure modes and mechanisms as possible. We want to improve the design.
Yet, what happens when the design team has moved on to the next project? When the expertise to effectively make changes to the design to improve product reliability performance is no longer paid to work on the previous design?
What can you do to engage the right people to implement the necessary changes?
Here are a few ideas that I’ve seen used to effectively make good use of field failures to create meaningful field reliability feedback. [Read more…]
Establishing a reliability goal for a project is often done early.
You may already know the reliability goal guides the entire development and supply chain team.
Yet, what is the actual value of setting a reliability goal?
As seen in the previous articles, you can easily use the data you already have to conduct a meaningful analysis. This includes Weibull, Crow-AMSAA or a Mean Cumulative Function analysis.
Digging into a well manage dataset promises to reveal insights, trends, and patterns that will help improve the line, process, or plant.
Creating a plot or calculating summaries is pretty easy with today’s tools. Yet, are you doing the right analysis or are the various assumptions valid?
One critical step in the data analysis process is making sure you are doing a valid and appropriate analysis. [Read more…]
The definition of reliability includes four elements.
One of them is the intended environment where the device or system will experience a range of stresses.
The knowledge of where and how an item will operate enables:
