INDUSTRIAL MAINTENANCE

Industrial systems fail in silence—until they don’t. The goal isn’t just to react faster. It’s to see the fault before it exists.

At DOOGG, we’ve moved beyond CMMS systems that rely on historical averages and scheduled replacements. Those models assume equipment is homogeneous. Reality disagrees.

Consider a motor with a 1% defect in its stator windings. Standard maintenance logs won’t catch it. But the harmonic signature in its current draw will.

In one engagement, we partnered with electrical engineers who analyzed spectral distortions in motor power signals to predict bearing wear, coil degradation, and imbalance—weeks before mechanical symptoms appeared.

This isn’t “AI.” It’s physics-aware software: raw sensor data → signal processing → deterministic thresholds → actionable insight.

We integrate these advanced diagnostics directly into operational workflows: • No black-box models
• No generic dashboards
• Just clear, auditable rules tied to physical reality

DOOGG actively collaborates with researchers and domain specialists—not to “apply AI,” but to embed deep expertise into maintainable systems.

Because in regulated environments, reliability isn’t a metric. It’s a requirement. And understanding why a prediction was made is as critical as the prediction itself.