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Many maintenance organizations around the world are reactive. They experience excessive breakdowns, low productivity, and high maintenance costs. To break this reactive cycle, a common solution organizations implement is Condition-Based Maintenance; however, this strategy rarely works. They pay for CBM solutions but get the results of a run-to-failure strategy. Here’s how to avoid that.
To help a new culture take root, we must stimulate our team members in unique ways to differentiate ourselves from the daily monotony of information being supplied to them. One exciting way that Joel Levitt, President of Springfield Resources, found of creating engaging content about preventive maintenance is through his original comic book.
Similar to business models, which are frequently assessed to improve their strategy, modern maintenance organizations are constantly evaluating their processes. This not only avoids negative business consequences, but eliminates the potential risk to people, the environment, and the products that are deeply impacted by equipment reliability.
Join industry expert John Ross in his Maintenance Minute video as he explains the most difficult part of FMEA, RCM and PMO – determining the failure modes.
Join Rafe Britton and Blair Fraser as they delve into the state of the manufacturing industry today, some of the exciting technologies they're keeping an eye on, and common threads that contribute to industry success.
All too frequently, the need for improved reliability becomes apparent. While the most common strategy for addressing this is to make physical changes that increase an asset’s Mean Time Between Failure (MTBF), that approach requires time, engineering and money, all things typically in short supply.
Unplanned downtime can be a major headache for plant operators and engineers, causing production losses and reduced profits. Predictive maintenance with machine learning offers a way to prevent downtime by identifying potential equipment failures before they occur.
The latest digital vibration transmitters provide critical machine health data for process monitoring and vibration analysis. When vibration analysis is performed regularly, developing faults are identified early, and predictive maintenance can be scheduled during planned downtime without impacting production.
We hear a great deal about what is happening in the condition monitoring space regarding the Industrial Internet of Things (IIoT) and other digital transformation strategies. The results promised from utilizing machine learning (ML) and artificial intelligence (AI) as a form of condition monitoring have encouraged many organizations in a variety of industries to put data science to work for them.
In this competitive industry, the difference between surviving and thriving comes down to asset failure and optimized maintenance practices.