Your Reliability Engineering Professional Development Site
Greg and Fred discuss why risk is becoming a personal issue to home owners and to all of us. They discuss aging infrastructure risk, who pays, and how to mitigate these risks.
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How do you balance customer wants with project constraints? If your customer-facing teammates are saying our customers want this, that and the other thing, which ones do we prioritize over others?
Not all features are equal in the eyes of our customers. And not all features are value-added, either.
In this episode, we delve into how to prioritize customer wants using the powerful Kano Model, a tool that maps customer satisfaction against the implementation of product features.
You’ll learn how to differentiate between essential and non-essential features, ensuring that your design truly resonates with your customers. This episode walks through the intricacies of the Kano Model’s two-by-two matrix and the different satisfaction levels represented by various lines and curves.
Too complex? We break it down. Prioritize your features based on their impact to the customer using their voice. Then, consider how well you want to implement that in your design using the Kano Model.
Get ready for practical tips and proven strategies to enhance your product’s value while managing cost, time, and design trade-offs. This episode is an introduction to the Kano Model for design.
Greg and Fred discuss quality from engineering and quality points of view. Greg is developing AI engineering applications. Greg wants to build, ship, and monetize. Fred wants to build quality in. What do you think is the right way?
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Past Good and Bad Knowledge
Chris and Fred discuss the so-called ‘bedrock documents and statistics’ that are used over and over again as if they are universally correct – even though they might have nothing to do with ‘your’ machines or systems. WHY?
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Professional development is not about pursuing a degree or title. It’s about what you can do with your knowledge. Of course, that is my opinion. Some seek credentials that may lead to a new position or opportunities. Some seek knowledge without intending to use it – education for education’s sake.
Whatever the motivation, we should approach learning meaningfully. Set objectives, do the homework, get feedback or coaching, and establish a routine to continue to hone your knowledge. Whether you want to learn something out of curiosity or master a topic to accomplish a task, you can plan to use your time efficiently.
Let’s explore how to improve your ability to learn and continue to learn throughout your career. As reliability engineers, there seems to be a never-ending list of concepts, failure mechanisms, novel materials, etc., that we can and should know about. With so many options for professional development, let’s examine a few principles and tips so you can learn and master what you desire to learn and master.
Chris and Fred discuss the three-letter acronym ‘MLE’ stands for? Well, it stands for ‘maximum likelihood estimate.’ Ever heard of it? Do you know what it means?
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Kirk and Fred discuss the impact of the Internet of Things (IoT) on maintenance and the data feedback to the manufacturer on usage and failure data.
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Our team is saying “No” to our co-work session.
We want to have a working meeting with them to get important information and make decisions. Since they declined, now we are missing an important viewpoint and source of design inputs! Plus, it could prove disastrous, later, when we have a pass/go decision on our concept designs.
In this week’s episode we talk about ways to overcome this challenge, beyond typical schedule availability. Tune in as we uncover practical strategies that make co-working sessions truly valuable which will help us in maximizing meeting value and participation.
In today’s episode, we’re exploring automated optical inspection (AOI) and x-ray inspection technology within the electronic assembly industry.
Joining us are two experts who bring a wealth of knowledge and experience to the table.
Kirk and Fred delve into the crucial topic of managing returned parts and products, even those that are functioning perfectly.
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Philip and Fred discuss some of the basic differences and similarities between these two types of statistical toolsets.
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Philip and Fred discuss a few challenges and approaches to deal with missing data.
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Greg and Fred discuss pushing the limits for personal and professional development. Greg discusses wearing a pink tutu to Oregon Country Faire and Burning Man. Fred discusses pushing the limits for product testing and product development.
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Can visualizing your data be the game-changer you’ve been missing?
Discover why plotting isn’t just a step in data analysis, but a crucial practice that can reveal uniformity, natural variations, and even potential flaws in your test methods. Learn about the importance of recognizing multiple failure modes and how to avoid common pitfalls such as mishandling outliers and making incorrect assumptions. This episode is packed with actionable advice to enhance your decision-making process.
Some of you might have heard of the Weibull distribution. It is an uncannily accurate way of describing many of the ways components fail. It can model things that wear-in where failure is caused by pre-existing damage and defects in a fraction of products. The Weibull distribution can also model things that wear-out we failure is caused once enough damage has accumulated. And some of you might have heard of the ‘3 Parameter Weibull distribution.’ But what makes this different and (sometimes) helpful? We are always wanting to improve the way we model things, including failure processes. So, to see if the ‘3 Parameter Weibull Distribution’ can help you … join this webinar!
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