Your Reliability Engineering Professional Development Site
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…]
These days most of us are used to instant gratification – we want it now and we want it cheap! When it comes to information, entertainment, finding your way around, and communications we more or less have it all at our fingertips. It’s also available to us just about anywhere. We can even order and pay for coffee to pick up on our way from the commuter train to the office – no line ups for delays. We can book houses, rooms, hotels, airlines, vacations, and rental cars at the touch of our fingers with apps that show us the cheapest options. [Read more…]
It’s easy to become overwhelmed with the vast amount of terminology used to describe maintenance concepts. Even those who are familiar with various maintenance management terms know there is a lack of consistency among sources. This guide to maintenance management terminology serves to help teams better understand the differences between key phrases used in the industry. Browse through our maintenance glossary below. [Read more…]
Would you like the reliability of all your products and their service parts, without assumptions, in real environments, and with all premature failures, complaints, repairs, warranty expirations, preventive maintenance, changes, warranty extensions, etc.? Field reliability tells what really happens! [Read more…]
In last month’s introductory article, we discussed some of the barriers to selling not only the concept of Root Cause Analysis (RCA) but also the recommendations generated as a result of these analyses. We also laid the framework for making better predictions by generating and accessing better data—namely predicting our Mean Time between Failure (MTBF) and Mean Time to Restore (MTTR) earlier and, therefore, implementing a fix faster.
Given this background, let’s explore how we can now justify conducting a RCA and implementing the recommendations as a result of the analysis. By and far, conducting a true RCA is viewed as luxury not a necessity. Think about the objections we hear when we offer the idea of gathering RCA teams. What follows is a list of common objections to RCA accompanied by rational justifications that any manager can employ. [Read more…]
Preventing The Consequences Of A Hidden Failure From Devastating Your Organization.
Ever wonder how some of the worst industrial disasters occur? It is usually the result of multiple failures. Failure of the primary system and failure of the protective systems. Ensuring the protective system(s) are not in a failed state should be of utmost importance to any organization. But how often should we test the protective systems to ensure the required availability?
Establishing the correct frequencies of the inspection/ testing activities of these protective system(s) is critical to not only the success but safety and reputation of any organization. Too infrequently and the organization is at risk of a major incident. Too frequently, and the organization is subjected to excess planned downtime, an increased probability of maintenance induced failures and increased maintenance cost.
This article will continue the discussion on establishing the correct inspection frequency in a maintenance program. There are three different approached to use, based on the type of maintenance being performed;
This article will focus on Failure Finding Maintenance.
A protective system or device is a system or device which is designed to protect and mitigate or reduce the consequences of failure. These consequences may be safety, environmental or operational in nature. These devices or systems are designed to;
Knowing what a protective device or system is, you may see that if a pressure relief valve became corroded and seized in the closed position, it would not be evident to the operators. This is a hidden failure. A hidden failure can be defined as; a failure which may occur and not be evident to the operating crew under normal circumstances if it occurs on its own. Obviously, this could lead to significant consequences if the tank that the pressure relief valve is protecting is overpressurized. This is where failure finding maintenance comes in.
Failure-finding maintenance is a set of tasks designed to detect or predict failures in the protective systems or devices to reduce the likelihood of a failure in the protective system and the regular equipment from occurring at the same time. So how to do you determine how often the protective systems should be checked for failure? Establish the frequency using a formula.
There is a single formula that will take into consideration of all variables to establish the failure finding interval (FFI); FFI = (2 x MTIVE x MTED) /MMF
Where;
So if we use an example from RCM2, we can see how this works; The users of a pump and a standby pump want the following from the system.
Therefore the correct failure finding interval would be;
This indicates that the standby pump must be checked every two months to verify it is fully operational. If this check is not performed, the likelihood of a multiple failures increases.
Lastly, if the failure of the protective device can be caused by the failure finding task itself, there is another approach to be used, which is beyond the scope of this article.
Do you have a program in place to check your protective systems? If not, are you aware of the risk that your organization is exposed to? Take the time to determine your protective systems and establish your failure finding tasks.
Remember, to find success; you must first solve the problem, then achieve the implementation of the solution, and finally sustain winning results.
I’m James Kovacevic
Eruditio, LLC
Where Education Meets Application
Follow @EruditioLLC
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