Is It Time to Implement Changes to Your Predictive Maintenance Program?

Posted by RDI Technologies on May 18th, 2021

Without reliable predictive maintenance (PdM) programs, facilities around the world would endure countless costs associated with unexpected downtime, labor, and avoidable repairs and replacements. Predictive maintenance, at its core, is about addressing problems and maintenance needs before they have an impact. Every process needs refinement, have you considered issues within your predictive maintenance workflow? It might be time to audit and optimize your facility’s program. Here are four signs to notice.

You Lack Real-Time Insight

Things can change fast in a production facility. One hour the system runs seamlessly, then later in the afternoon, you need to shut an asset down to perform unexpected maintenance or repairs. A seamless, consistent predictive maintenance routine can help you avoid these unexpected repairs, allowing you a chance to schedule them ahead of time. It all starts by gaining access to real-time data. If you don’t have the ability to see motion, movement, and vibrations in real time, it’s time to optimize your system and upgrade your PdM technology.

Technology Is Holding You Back

A predictive maintenance program is only as good as the people behind it and the technology they use. Your team is on top of it, but are you using the best technology available? Modern vibration analysis equipment provides real-time data on the condition and movement of your critical assets. From inspecting individual components to seeing how each asset interacts with the next, contactless vibration analysis equipment is the future of predictive maintenance. Many facilities employing it already notice significant gains in time, ease of use, and consistency.

You Spend Too Much Time on Predictive Maintenance

Wasted time is detrimental to any facility. While you shouldn’t ever feel the need to rush through your maintenance process or miss any steps, it shouldn’t disrupt other aspects of the operation. A streamlined predictive maintenance program complete with the latest vibration monitoring equipment can help you see problems before they occur and deploy your maintenance team to solve them before time-intensive downtime needs to happen. If you value uptime, investing in a streamlined predictive maintenance program is a must.

Your Facility Is Growing

The more assets you have in your facility, the more important your predictive maintenance program becomes. You must optimize it to be as effective, future-proof, seamless, and user-friendly as possible. When you increase the number of assets that your team works with, you add points of failure. New team members may be working with machines and processes they’re unfamiliar with while they’re training, so you need protections against human error in place. These factors point to the need for a better, streamlined predictive maintenance program. Invest in quality equipment that amplifies motion from afar so you can gather real-time data on the condition and movement of your critical assets.

About RDI Technologies

With the release of the leading-edge Iris product platform, RDI Technologies effectively revolutionized the machine condition monitoring and testing space. The Iris M™ vibration analysis and monitoring platform is powered by Motion Amplification®, making it a high-precision machine condition monitoring solution. That Motion Amplification technology delivers crucial insights into the condition and the reliability of critical assets. It does so by rendering otherwise invisible vibration, displacement, and movement in those critical assets visible in real time. Additionally, the Iris products can be installed for predictive maintenance or testing that either runs continually or at specified intervals. Monitor the condition of your critical assets and test results with Iris technology platform from RDI Technologies.

Learn more about the Iris M™ platform at https://rditechnologies.com/

Original Source: https://bit.ly/3frCbOn

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RDI Technologies
Joined: March 17th, 2020
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