Your Reliability Engineering Professional Development Site
Find all articles across all article series listed in reverse chronological order.
Ryan Chan of UpKeep authored a new book in which he presents some very smart concepts around information management. Here’s a video of a group discussion of those concepts and the launch. Participants include Ryan Chan (author of “Asset Operations”), Sanya Mathura, Ramesh Gulati, Vinny Cavello, and our own, James Reyes-Picknell.
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“Man measures time by happiness or sorrow, tranquility or torture. The one is past and gone so quickly that is seldom seized and savored while the other turns the hours into days and the weeks into years”. This was written by Major Pat Reid in “The Colditz Story” and, while it comes from a time of internment at a dark time in history the same is true today.
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Reliability is something that can be created. It is the result of the standards, processes, and practices that are used. By removing causes of failures and controlling the factors that allow their creation, you proactively eliminate failure events. By eliminating failures, you deliberately create reliability. The reliability creating processes in the Plant Wellness Way EAM methodology let any operation or site reach the heights of world class operating asset reliability.
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Mediocrity can talk, but it is for genius to observe. – Benjamin Disraeli
The Inside FMEA series has completed the primary facilitation skills. The next few articles will cover special facilitation topics.
This article talks about the pros and cons of using a “scribe” to help with facilitation. [Read more…]
Many valuable lessons can be learned from the failures of risk governance in Australian banks.
The Commonwealth Bank of Australia (CBA) and Westpac Banking Corporation (Westpac), two of the largest banks in Australia had to provide Court Enforceable Undertakings in May 2018 and December 2021 respectively to the Australian Prudential Regulation Authority (APRA).
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Below is an email discussion about when Crow-AMSAA modelling can provide believable forecasts.
Suppose installed base or cohorts in successive periods have different reliabilities due to nonstationarity? What does that do to forecasts, estimates, reliability predictions, diagnostics, spares stock levels, maintenance plans, etc.? Assuming stationarity is equivalent to assuming all installed base, cohorts, or ships have the same reliability functions. At what cost? Assuming a constant failure rate is equivalent to assuming everything has exponentially distributed time to failure or constant failure rate. At what cost?
The manufacturing sector has seen a rise in competitiveness because of the introduction of Industry 4.0 technologies over the last decade. It has become important for manufacturers to stand out in the industry by optimizing their systems to be as perfect as possible. One of the factors that make a factory competitive is its reliability, and a smart factory has great opportunities to improve it using the failure data from its assets.
The smart factories created using these technologies have greater efficiency and provide valuable data about the assets which can be used to further improve plant performance. The asset failure data gathered from different assets can provide insights into the reliability of assets and how to improve it. [Read more…]
Hurricanes pose serious risks to physical assets in chemical plants and refineries. During hurricanes, plant equipment can be damaged by high winds and/or flood waters. I’m hoping your refinery has adequate protection against flooding…so let us see what risks are posed by high winds.
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The equipment needed to run a manufacturing plant is costly and expensive to replace. Furthermore, equipment downtime leads to lost production, which directly impacts profits. Replacing reactive maintenance with proactive maintenance through the implementation of CMMS software for manufacturing plants will give you more control and help you prevent equipment breakdown and failure. The benefits of CMMS software are numerous for manufacturing plants.
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The Industrial Internet of Things (IIoT) has created immense excitement and promise for industrial facilities. Having connected assets that continuously monitor their own health and feed that information back in a way that is timely and actionable will drive business outcomes and help organizations achieve loftier goals. The challenge today is that many of our assets are not yet “connected” or “intelligent,” meaning that they are not yet outfitted with the health monitoring instrumentation that provides the live, automated data feed directly to a centralized repository of data. Yes, critical assets like turbine generators, boiler feed water pumps, highly critical motors and the like are indeed outfitted with modern instrumentation and fail-safe solutions. However, in most industrial facilities throughout the world, this is a very small population of assets.
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The World Economic Forum has conducted a Global Risk Survey since 2006. This is the fifteenth survey. The responses are from 650 members of the World Economic Forum. In the preface to the 2021 Global Risk Report it is noted that: “In 2006, the Global Risks Report sounded the alarm on pandemics and other health-related risks.” (1) With this context in mind, the 2021 risk analysis “centers on the risks and consequences of widening inequalities and societal fragmentation. In some cases, disparities in health outcomes, technology, or workforce opportunities are the direct result of the dynamics the pandemic created.” (2)
This piece will review the results of the 2021 Global Risk Survey. It will also discuss some of the issues surrounding the survey.
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In the Plant Wellness Way EAM system-of-reliability methodology you set world class performance targets for every work task. You do that so the people doing the job know what world class work looks like. Then you ask them to find new, successful ways to deliver world class outcomes in the tasks they do. That way you guarantee world class success.
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In the 1960s, my ex-wife’s father set safety stock levels and order quantities for Pep Boys. He used part sales rates and the Wilson square-root formula to set order quantities.
Why not use the ages of the cars into which those parts go, to forecast part sales and recommend stock levels? Imagine you had vehicle counts (year, make, model, and engine) in the neighborhoods of parts stores, catalogs of which parts and how many go into which cars, and store sales by part number.
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