Predictive Maintenance: 8-Wk Pilot Implementation

Manufacturing & remote sites have multiple rotary equipment. Eg, Pumps, drives, gearboxes, compressors, etc. These are critical assets - failure of any one of them can cause severe disruption to the production lines, potentially even leading to line or even plant shutdown.

This is leading to O&M teams spending several million dollars annuals as part of maintenance contracts to OEMs & service providers for maintaining critical equipment. This is apart from the even higher opportunity costs incurred due to productivity losses (up to 50%)

Earlier (in Industry 3.0), it was both cumbersome and expensive to monitor the health of these equipment. Hence such machines were not given importance vis-a-vis health monitoring. But now, with AI-IoT based solutions, these activities can be more efficient & effective.

The solution from Tredence is designed to

• Facilitate comprehensive condition monitoring of all equipment in one place; that is both frugal and adaptable to different operational environments

- Deliver predictive & prescriptive alerts to the plant O&M teams, ahead of time to minimize failures thru Remaining Useful Life (RUL) and Time to Failure (TTF) estimations.

The Tredence Advantage:

• Deep learning driven AI Engine that can detect hidden patterns
• The Azure-Databricks led architecture helps process the high volume, high frequency streaming data efficiently, while optimizing cloud storage & computing costs
• Accelerated deployment to the Azure IoT-Edge, enabling high performance in offline mode