Your Reliability Engineering Professional Development Site
Find all articles across all article series listed in reverse chronological order.
Dear friends, we are happy to release this DFMEA Part-1 video. In this video, we have tried to explain how to plan and prepare for DFMEA. Hope you find it interesting and useful. Your feedback welcome!
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If you work in manufacturing, quality, or engineering, you’ve probably heard the term “Design of Experiments,” or DOE. Maybe you’ve even helped collect data for one without fully understanding what was going on behind the scenes. That’s okay. DOE is a sophisticated statistical method, but even if you’re not the one crunching the numbers, understanding the big ideas behind it can make you a more effective technician, engineer, or manager.
At its core, Design of Experiments is a structured statistical approach to testing. It helps us understand how different inputs (or factors) affect an outcome (or response). Whether you’re adjusting a process to improve tensile strength, dialing in machine settings to reduce defects, or figuring out which supplier provides the most consistent material, DOE helps answer one big question: What settings or conditions will give me the result I want?
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Article by Mike Freier
Manufacturing is an essential step in a new product launch that requires a thoughtful strategy. In this stage, teams define a manufacturing strategy, create a development schedule, and built units to test.
We measure results. We measure profit, shipments, and reliability.
The measures or metrics help us determine if we’re meeting out goals if something bad or good is happening, if we need to alter our course.
We rely on metrics to guide our business decisions.
Sometimes, our metrics obscure, confuse or distort the very signals we’re trying to comprehend.
Here are five metric based mistakes I’ve seen in various organizations. Being aware of the limitations or faults with these examples may help you improve the metrics you use on a day to day basis. I don’t always have a better option for your particular situation, yet using a metric that helps you make poor decisions, generally isn’t acceptable.
If you know of a better way to employ similar measures, please add your thoughts to the comments section below. [Read more…]
The allocation of samples for different tests during the design validation stage in the automotive industry can vary depending on the specific requirements of the product and the risks associated with its failure. However, based on the general practice of using a total of 30 samples for design validation, we can provide a hypothetical allocation for the different tests. It’s important to note that these numbers are illustrative and should be adjusted based on the actual testing needs, regulatory requirements, and industry standards.
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Because of the nature of Moore’s law, anything that an extremely clever graphics programmer can do at one point can be replicated by a merely competent programmer some number of years later.
John Carmack – Software Engineer
A number of years ago, several of us at Institute of Electrical and Electronic Engineers (IEEE) wondered what are the people implications of what is commonly called Moore’s Law. The 2020 edition of this book (pre-COVID) focused on AI and technology disruption.
Story: Gordon Moore was one of the founders of Intel Corporation. Moore’s Law states the number of transistors that can fit into a computer chip doubles every 18 months to two years. Moore’s Law expanded to include any tech area where the rate of change doubles in two years or costs half as much.
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An example of an Accuracy Controlled Enterprise ACE 3T (Target – Tolerance – Test) Procedure with reliability standards to install taper spherical roller bearings on adaptor sleeves in Plummer blocks with taconite seals for 30mm-250mm diameter conveyor shafts
Machine performance is totally dependent on human beings. To address the problem of human error causing equipment failure, an Accuracy Controlled Enterprise sets best practice quality standards and uses 3T Target-Tolerance-Test work task quality control that assures high quality workmanship for high reliability results. Their work procedures are standardised so everyone follows the same methods to produce the same results, their training teaches people how to do craftsmanship work that creates outstandingly reliable plant and machinery. They create the reliability they want and as a result achieve operational excellence.
Dear friends, we are happy to relaese this video on Fault Tree Anlayis FTA). FTA is an important technique used in reliability engineering. Hope you find the video interesting! Link to our video on Binomial distribution
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How do you determine the right interval for a Condition Based Maintenance (CBM) task? It all comes down to the P-F Interval—the time between when a Potential Failure Condition is detectable to when the failure occurs.
In this video, I break down how to set CBM task intervals correctly using a simple example. The Failure Mode is: “Filter clogs due to normal use.” I’ll explain that CBM task intervals aren’t based on Criticality, MTBF, or the Useful Life, but instead on how quickly failure occurs once a Potential Failure Condition is detectable.
Learn how to properly identify and set your CBM task intervals to keep your equipment running reliably
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How effective are the repair tasks you conduct on your equipment?
This article looks at quantifying the effectiveness of corrective maintenance, typically an unplanned repair on an asset. Unplanned repairs are undesirable because the asset loses its function and cannot produce what is required often leading to loss of revenue. Yet, this advent is inevitable because assets are subject to degradation over time.
The effectiveness of a repair relates to the condition in which the asset is restored to after a repair. But also how long it will operate until the next repair, Evaluating the effectiveness of the repair will provide the asset operator with a decision making tool. Can we do something different if the repair effectiveness is unsatisfactory? Or do we have to replace the asset as it is failing too frequently?
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Article by Mike Freier
In the last blog post, we discussed why Design for Excellence (DfX) is important to your business. Building on several important concepts, this blog will focus on the Product Development phase and discuss how incorporating Agile principles can improve and accelerate your hardware product development process.
[Read more…]In the world of engineering reliability, there is a crucial aspect that spans various domains, the two fields that often get confused due to their similar names. While site reliability engineering (SRE) and hardware reliability engineering are both aimed at ensuring the dependability of systems, they focus on vastly different areas and employ distinct methodologies.
Let’s explore the key differences between these two disciplines and delve into the history behind the SR naming convention.
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My wife and I moved to a new home last year. We have yet to organize our tools.
The bedroom and kitchen are now organized. We, for the most part, can find the sweater or pan that we’re seeking.
No so for our tools in the shop. We have an assortment of hand tools for painting, home maintenance, yard work, and woodworking. In our previous home, we had the tools on pegboards, on shelves, in cabinets. We could find the right tool for the job at hand quickly. We’ve avoided the tool aisle at the hardware store recently, as we were sure we had the tool we need in the jumbled mess in our garage already. Still haven’t found it, though.
Have you noticed the number of statistical tools available? It’s like visiting a well-stocked tool store. There are basic tools like trend charting and advanced tools like proportional hazard models. Let’s explore the available tools a little so you can quickly find the right tool for the question or problem you are facing today.
[Read more…]Many ideas grow better when they are transplanted into another mind than the one where they sprang up. Oliver Wendell Holmes
In this article, I will outline how to evaluate an FMEA against the FMEA Quality Objective for FMEA Team. I’ll include relevant information from the chapter in the FMEA Preparation series called “Assembling the Correct FMEA Team.”
Today’s Gremlin – “lube it wrong”, is a leading cause of machinery breakdown. 60% to 80% of all bearing failures are due to lubrication related problems. Wrong lube, too much lube, too little lube, contaminated lube, degraded lube, overheated lube and even poor lube selection can all lead to premature failures of bearings. Put a tiny bit of dirt into a hydraulic system and watch it fail quickly.
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