How to Scale Predictive Maintenance Without Hiring a Team of Vibration Experts

Posted by Nick Schiltz on June 25

Certified vibration analysts are few and far between, and most industrial sites operate without one. As predictive maintenance becomes more critical, a lack of in-house expertise creates a real bottleneck for scaling these programs across facilities.

Traditional approaches depend on specialists to set routes, capture vibration data, and interpret waterfall plots. But that model breaks down fast when you’re monitoring dozens of assets or trying to replicate success across multiple plants.

GraceSense™ flips the script. With wireless sensors, built-in defect classification, and browser-based dashboards, you can monitor your assets plant-wide—no analyst required. This post shows you:

  • Why conventional predictive maintenance stalls at enterprise scale
  • How automated condition monitoring removes the “analyst bottleneck”
  • A step-by-step plan for rolling out sensors, alerts, and workflows with limited resources
New to the topic? Start with our Ultimate Guide to Condition Monitoring for core concepts and definitions.

Why Predictive Maintenance Is Hard to Scale

Expertise Is Expensive

Recruiting or training a CAT-II or CAT-III vibration analyst takes years and comes with a six-figure price tag. Maintaining their software, hardware, and certifications adds long-term costs before you even collect your first waveform.

Manual Data Collection Slows Everything Down

Traditional route-based programs rely on handheld devices and monthly inspection rounds. Each plant produces massive volumes of raw vibration data that still require manual post-processing. The more assets you monitor, the bigger the backlog.

Inconsistent Deployments Across Sites

Even companies with strong reliability teams struggle to scale programs uniformly. Differences in sensor types, alarm thresholds, and inspection frequency create fragmented data, making benchmarking across plants nearly impossible.


The Shift to Automated Condition Monitoring

GraceSense removes these barriers by automating the most resource-intensive parts of vibration analysis. It uses:

  • Wireless VBTx Sensors collect vibration and temperature data using a tri-axial accelerometer with sampling rates up to 25.6 kHz.
  • 19 Predefined Fault Models that compare extracted features against common failure patterns like imbalance, misalignment, and bearing wear
  • A Browser-Based Maintenance Hub that turns alerts into maintenance actions and gives your team a centralized view of asset health

Instead of routing handhelds and manually reviewing spectra, technicians receive alerts like “Stage-2 bearing wear—repair within 10 days” right in their dashboards. No vibration degree required.

Learn more in our post on the benefits of remote continuous vibration monitoring.


 

What Is Automated Defect Classification?

Automated defect classification is a rules-based process that identifies known fault patterns in rotating equipment, eliminating the need for a vibration analyst. Instead of relying on human interpretation of raw FFT plots, GraceSense™ handles the heavy lifting through a streamlined, sensor-to-alert workflow.

It begins with the VBTx sensor, which directly captures acceleration and temperature data from the asset. An onboard edge processor extracts key vibration features such as FFT and velocity. These features are then transmitted to the cloud, where the GraceSense platform compares them against 19 predefined fault models for common issues like bearing wear, imbalance, and misalignment.

When a match is found, the system generates a plain-language alert and routes it to the Maintenance Hub, where it can automatically trigger a work order. The result is fast, consistent diagnostics that any technician can act on, no spectrum reading required.

Want the fundamentals? Read about the 5 elements of condition monitoring.


How to Scale Predictive Maintenance With Limited Resources

  • Use Plug-and-Play Devices: GraceSense VBTx sensors magnetically mount to rotating equipment and connect wirelessly to Grace gateways—no rewiring or PLC modifications are required. QR code pairing enables them to be deployed quickly.
  • Centralize Data with Dashboards: The GraceSense Maintenance Hub serves as your single source of truth. Assets are color-coded by health status, and alerts are automatically tied to equipment history, vibration trends, and recommended action windows.
  • Empower Generalist Maintenance Teams: You don’t need a vibration analyst to interpret spectra. GraceSense delivers fault names and severity levels directly in the interface, and can integrate with your CMMS to auto-generate work orders.

More detail in our post on continuous vibration monitoring.


Is Automated Predictive Maintenance Right for You?

Check your plant against this list:

  1. No certified vibration analyst on staff
  2. Multiple facilities with varying maintenance practices
  3. Critical rotating equipment (fans, pumps, gearboxes)
  4. Downtime costs exceed $5,000/hour
  5. Corporate goals include reducing maintenance spend

If you checked three or more, GraceSense is likely your fastest path to ROI.


Ready to Get Started?

  • Book a demo to see automated defect classification in action
  • Learn about our pilot kit (includes 4 sensors, 1 gateway, and software—no additional cost for year one)
  • Brush up on the basics in our Ultimate Guide to Condition Monitoring
  • Register for our upcoming webinar below

You don’t need a team of certified analysts—just the right tools. GraceSense makes plant-wide vibration monitoring practical for any facility, regardless of size or staff.

July 15th Social Media Post_2506

We’re unpacking these five condition-monitoring pitfalls—and the GraceSense™ fixes—in a live, slide-free webinar: “Stop the Surprise Shutdowns: Five Condition-Monitoring Pitfalls (and the GraceSense Fix) – 2025 Reliability Podcast.” Join our reliability pros for a deeper dive, real-time Q&A, and a practical pilot roadmap.

Save your seat here ➜ Webinar Registration


Stay SAFE, and have a GREAT week!

Nick_Sig

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