Your Reliability Engineering Professional Development Site
The title is a Statistician’s Lament. “Design of Experiments (DoE) is the design of any task that aims to describe or explain the variation of information under conditions that are hypothesized to reflect the variation.” [Wikipedia] Are you using DoE to design reliability tests? What do PH, GMDH, and |D|-optimality have to do with design of DoE of reliability tests?
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We always tell and listen to stories—anecdotes, encounters, best practices, near misses, memories, etc. We also influence how we interpret the world through the stories we tell ourselves. Plus, we often work to alter the stories others have in their head as we work to improve reliability.
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Isn’t it enough to estimate the age-specific field reliability functions for each of our products and their service parts? Of course we quantify uncertainties in estimates: sample uncertainties and population uncertainties due to changes or evolution. That’s information to forecast service requirements, recommend spares, optimize diagnostics, plan maintenance, warranty reserves, recalls, etc. What else could we possibly need or do?
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Accendo Reliability is a platform for you to share your knowledge and experience with your peers.
Thought Leader
Author of Inside FMEA articles, FMEA Resources page, and multiple books, co-host on Speaking of Reliability
Thought Leader
Author of Reliability in Emerging Technology, and co-host on Speaking of Reliability, and speaker in the Accendo Reliability Webinar Series.
Thought Leader
Author of CRE Preparation Notes, Musings, NoMTBF, multiple books & ebooks, co-host on Speaking of Reliability, and speaker in the Accendo Reliability Webinar Series.
Thought Leader
Author/Editor of CERM Risk Insights articles and multiple books, co-host on Speaking of Reliability, and speaker in the Accendo Reliability Webinar Series.
Thought Leader
Author of Maintenance and Reliability articles, multiple ebooks, and host of Rooted in Reliability, co-host on Speaking of Reliability.
Thought Leader
Author of Plant Maintenance, Maintenance Management, and Life Cycle Asset Management.
Thought Leaders have shared a significant number of articles and/or episodes, plus have a high number of comments.
Thought leaders consistently provide content and answer your questions.
Active contributors that are sharing their experience, insights, and knowledge with you.
Active Contributor
Author of Metals Engineering and Product Reliability articles and Metal Conversations podcast.
Active Contributors have continued shared their knowledge for over six months.
Active Contributor
Co-author of The Reliability Experience articles and co-host of Practical Reliability.
Active Contributor
Co-author of The Reliability Experience articles and co-host of Practical Reliability.
Active Contributor
Author of Accelerated Reliability articles and Next Generation HALT and HASS, plus, co-host on Speaking of Reliability.
Active Contributors have consistently shared their knowledge for over six months.
Active Contributor
Author of Integral Concepts articles and offers Design of Experiments course.
Active Contributors have consistently shared their knowledge for over six months.
Active Contributor
Author of Everyday RCM articles and videos and offers Foundations of RCM course.
Active Contributor
Author of The Manufacturing Academy articles offers Reliability and Quality Engineering Statistics, An Introduction to Reliability and Quality Engineering, Process Capability Analysis, Root Cause Analysis and 8D Corrective Action Process, and Return on Investment Analysis for Manufacturing courses.
Active Contributor
Author of Integral Concepts articles, and offers Reliability Analysis Methods, SPC & Process Capability, and Measurement System Assessment courses.
Active Contributors have consistently shared their knowledge for over six months.
Let’s welcome those just starting to share their knowledge here:
New Accendo Reliability contributors have stepped up to share their knowledge with you.
A listing of past contributors that are no longer active, yet their content is still great.
Thanks to all that have helped to make Accendo Reliability
the resource that it is today.
Good reliability requirements are going to drive our design decisions relating to the concept, the components, the materials, and other stuff. So, the moment to start defining reliability requirements is early in the design process. But, what makes a well-defined reliability requirement? There are five aspects it should cover: do you know what they are?
We’ll describe what makes a good reliability requirement and examples of common (but not good) requirements.
What can we do without reliability function estimates? FMEA? FTA? RCA? RCM? Argue about MTBFs and availability? Weibull? Keep a low profile? Run Admirals’ tests? Look for a new, well-funded project far from the deliverable stage?
Ask for field data; there should be enough to estimate reliability and make reliability-based decisions, even if some data are missing. Field data might even be population data!
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Through daily inspections, cleaning, and lubrication practices we can measure, prevent, and restore deterioration to our equipment. The expectation is that a team is put together made up of maintenance, operations, and leadership employees to roll out strategy beginning with one piece of equipment. They will implement the following 7 steps:
(This is chapter 5 of User Manual for Credible Reliability Prediction – Field Reliability (google.com), cleaned up and typeset for AccendoReliaiblity Weekly Update.)
The nonparametric maximum likelihood estimator for an M/G/∞ self-service time distribution function G(t) extends to nonstationary, time-dependent, Poisson arrival process M(t)/G/∞ systems, under a condition. A linearly increasing Poisson rate function satisfies the condition. The estimator of 1-G(t) is a reliability function estimate, from population ships and returns data required by generally accepted accounting principles.
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Mature organizations seeking a competitive edge are familiar with the term Reliability Centered Maintenance (RCM). A maintenance philosophy encompassing predictive, preventative, and maintenance, RCM uses defined processes to find latent or hidden failure modes, customizing maintenance processes to maximize system performance. Most understand that the RCM philosophy enhances equipment availability through improved reliability, increasing annual earnings before interest, tax, and amortization (EBITDA). Yet, some businesses fail to understand that equipment availability comprises two crucial inputs, not one. Equipment reliability, yes, but also equipment maintainability. [Read more…]
Chris and Fred discuss the whole idea of ‘demonstration testing’ … and how it may be ‘chronically’ overused or at least misunderstood. Heard of ‘demonstration testing’ and need to learn more?
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The ASQ Reliability Division (RD), copyrighted the 2003 monograph “Credible Reliability Prediction” (CRP) but lost all copies circa 2014. I pestered the RD to let me republish CRP, because people asked “How do I make credible reliability predictions?” Copyright reversion to authors is accepted practice when a publisher no longer supports a document.
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ASQ Reliability Division published “Credible Reliability Prediction” (CRP) in 2003. Harold Williams, Reliability Division monograph series editor, wrote, “[CRP] …delineates statistical methods that effectively extend MTBF prediction to complex, redundant, dependent, standby, and life-limited systems… This is the first text that describes a credible method of making age-specific reliability predictions…. This monograph presents insights and information inspired by real applications and [still] not covered in contemporary reliability textbooks.”
Chris and Fred discuss the different words we often use (and misuse) in reliability engineering. ‘Reliability’ has been used for hundreds of years to describe different concepts of ruggedness, robustness, strength, timeliness, trustworthiness and so on. But – reliability has a specific definition within reliability engineering. There are plenty of other examples of how words we use in reliability engineering can have multiple meanings – even when we think they don’t!
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“Component D” had some failures in its first 12 months. How many more would fail in 36-month warranty? ASQ’s Quality Progress Statistics Roundtable published the data and Weibull analysis. The data included left-censored failure counts collected at one calendar time. The Weibull analysis included actuarial failure forecasts. This article describes nonparametric alternatives to Weibull and quantifies extrapolation uncertainty. The nonparametric forecasts are larger than the Weibull forecasts. Alternative extrapolations of nonparametric failure rates from data subsets quantify uncertainty. [Read more…]
“There is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success than to take the lead in the introduction of a new order of things, because the innovator has for enemies, all of those who have done well under the old conditions, and luke-warm defenders in those who will do well under the new.”
– Niccole Machiavelli
This quote is appropriate when we seek a paradigm shift towards a proactive culture, after spending our careers trained to become the best ‘react-ors’ or responders, we can be. I encourage you to read this lengthy article to the end for a surprise and to ask you a couple of questions about your experience with reliability. [Read more…]
