Computer Vision in Maintenance: The 'Eyes' of the Smart Factory (2026 Guide)

We have spent the last decade wiring our factories with sensors. We measure temperature, vibration, amperage, and pressure.
Yet, when a machine stops, the most common question is still: "What happened?"

The sensors show "Motor Overload." But they don't explain why the motor overloaded.

Was it a mechanical seizure? Or did a cardboard box get stuck in the intake?
Sensors feel the pain, but they cannot see the injury.

In 2026, Computer Vision is filling this gap. It provides the "Visual Intelligence" that PLCs and IoT sensors lack.

By integrating cameras into your maintenance software, you turn "Guesswork" into "Evidence."

Here is how Fabrico uses Computer Vision to uncover the invisible causes of downtime.

Why Sensors Are Not Enough

Traditional condition monitoring listens to the internal components of a machine. This is excellent for predicting bearing failures.
But in high-speed manufacturing (Packaging, Food & Bev, Automotive), failures are often External:

• A flap on a box sticks out.

• A guide rail vibrates loose.

• An operator places a part slightly off-center.

No vibration sensor in the world will detect a "Stuck Flap." Only a camera can see it.

The Fabrico Solution: "Inefficiencies Zoom-In"

We don't expect you to hire a team of data scientists to build custom vision models. Fabrico makes visual intelligence practical today.

1. The "Instant Replay" (Root Cause Analysis)

Fabrico integrates cameras directly into the OEE Timeline.

• The Buffer: The camera continuously records a loop (e.g., keeping the last 5 minutes).

• The Trigger: When the machine’s PLC signals a "Stop," Fabrico permanently saves the video clip from that moment.

• The Insight: The technician opens the downtime event on their tablet and watches the video. They see the exact moment the jam occurred. They know exactly where to put the wrench.

2. Solving the "Micro-Stop" Mystery

The biggest killer of OEE isn't the major breakdown; it's the 200 micro-stops that happen every shift.
Operators usually ignore them or log them as "Minor Stop."

• The Vision Advantage: With Fabrico, you can review a montage of all 200 stops.

• The Pattern: You might notice that 90% of the stops happen when the "Red" raw material is used versus the "Blue."

• The Fix: You realize it's a material quality issue, not a machine tuning issue. You save the maintenance team hours of unnecessary adjustment.

3. Ending the "Blame Game"

Production blames Maintenance ("The machine is broken"). Maintenance blames Production ("You loaded it wrong").
Video evidence is objective.

• Scenario: A machine crashes.

• Video Evidence: The clip clearly shows an operator bypassing a sensor.

• Resolution: The issue is addressed through Training, not Repair. The Maintenance team is not sent on a wild goose chase.

The Future: From Recording to Detecting

Right now, Fabrico helps you See (Visual Record).
As we collect this data, we are building the foundation for AI Detection.

• Today: You watch the video to find the jam.

• Tomorrow: The Fabrico Agent will watch the video stream in real-time and alert you: "Warning: In-feed accumulation detected. Slow down the conveyor."

By installing the visual infrastructure today, you are "AI-Proofing" your factory for the next wave of automation.

Comparison: Diagnostic Tools

The Fabrico Framework: The Visual Diagnostic Loop

1. Monitor: Cameras overlook critical bottleneck assets.

2. Capture: PLC triggers the recording of downtime events automatically.

3. Review: Technician watches the "Zoom-In" clip before starting the repair.

4. Resolve: The fix addresses the root cause (e.g., "Align Rail"), not just the symptom (e.g., "Clear Jam").

Conclusion: Turn on the Lights

You wouldn't drive a car with your eyes closed, relying only on the sound of the engine. Why run a factory that way?
Computer Vision gives your maintenance team eyes.

See what you've been missing.

[Request a Demo] and ask to see the "Inefficiencies Zoom-In" feature.