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Reactive maintenance (fix-on-failure) halts production, stresses spare-parts inventory and forces emergency labour costs. Periodic maintenance leads to needless part replacements and missed faults. Predictive maintenance lets you intervene exactly when the machine actually needs it.
At Digital Bridge we instrument your critical machines with sensors, process the data in real time and use an AI model to predict the probability of failure. Your team gets warned weeks in advance and can plan maintenance.
Vibration, temperature, current and oil-quality sensors are mounted on critical equipment (motors, pumps, compressors, bearings, gearboxes). Wireless or wired connectivity options are available.
Sensors continuously stream data at the configured sampling rate. After edge-gateway pre-processing, data is pushed to the cloud or local server. A local buffer covers internet outages.
Once the baseline (normal-state) profile is established, the AI model detects deviations. Vibration spectrum changes, bearing-frequency anomalies and temperature rises are combined to estimate fault category and time-to-failure.
When thresholds are exceeded, the maintenance team gets an email, SMS or app notification. If a CMMS is integrated, a work order is created automatically.
Less unplanned downtime
Lower maintenance costs
Less spare-part stock
Earlier warning before failure
You can launch a pilot on 1–3 critical machines in your factory. In the first 30–60 days you'll see concrete metrics for the system's value, then scale it across the plant.