In our continuing introductory look at industrial & facilities maintenance basics, this article will provide an introduction to conditions-based maintenance, or CBM.
At root, CBM is a maintenance strategy focused on determining the correct time to perform maintenance on equipment and machines.
To learn more about this, please read the article below and be sure to let us know if you’ve got any questions.
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When using conditions-based maintenance, an organization monitors the actual, real-time conditions of a physical asset and performs maintenance on that asset only when the monitoring discovers indicators that the performance of the asset is decreasing or that a failure will occur shortly.
So conditions-based maintenance is different than planned maintenance, when maintenance occurs at pre-planned, regular intervals.
There are a variety of ways to check the conditions of the asset to determine if maintenance is required. These methods include visual inspections, non-invasive measurements, through analysis of performance data, and scheduled testing of the asset. Monitoring techniques may include oil analysis to find the number and size of particles in the oil and use that as an indicator of machine degradation, the use of infrared camera for temperature analysis, vibration analysis, acoustic analysis to detect leaks, ultrasonic analysis, and sensors on assets to monitor things like flow, pressure, and temperature.
There are also options as to when the conditions are monitored. In some cases, such as a visual inspection, it can happen periodically. In other cases, such as when sensors are used, it can be continuous.
The benefit of using conditions-based maintenance is that you will (ideally) perform maintenance before a break-down or significant reduction in operation but not too early and often, as you might with planned maintenance.
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Jeff Dalto, Senior Learning & Performance Improvement Manager
Jeff is a learning designer and performance improvement specialist with more than 20 years in learning and development, 15+ of which have been spent working in manufacturing, industrial, and architecture, engineering & construction training. Jeff has worked side-by-side with more than 50 companies as they implemented online training. Jeff is an advocate for using evidence-based training practices and is currently completing a Masters degree in Organizational Performance and Workplace Learning from Boise State University. He writes the Vector Solutions | Convergence Training blog and invites you to connect with him on LinkedIn.
