Predictive Maintenance

Predictive maintenance

Predictive maintenance algorithm is our forte. Our company leverages this data to improve both operational and technical insights of the existing processes. Simultaneously, real-time implementation of our predictive algorithms provides you with information about upcoming bottlenecks and failures.

Incumbent failure in rotating machines – pumps and compressors

Our algorithm uses pattern recognition of the data and thereafter, predicts the time of failure along with the cause of failure. Pushing the assets beyond their design limit (how) and hence, more benefits. It has developed the intelligence for cavitation, oil leakage, sensors failure, bearings failure and shaft failure. It uses vibration analysis to detect bearing failure or shaft failure by using a library of bearing codes which has the design information about the bearings. The algorithms unique ability to diagnose the cause of failure allows you to prescribe the cause of failure and its time.

Knowing the cause of failure adds to advanced planning and schedule for the repair and maintenance. Consequently, the downtime for the asset is reduced which brings more revenue.

Intelligence of our algorithm:

  1. Identifying sensor failures
  2. Predicting failure in the next time window. The time window is determined by the client, and the algorithm is accordingly customized. The time window can vary from 15 minutes to 24 hours depending on the client’s processes and requirements. The larger the time window, the lower the accuracy of the algorithm in predicting the cause of failure.

Benefits for the business:

  1. Upto 10% savings in utilities annually
  2. Upto 15% more return on investment on the asset price over its life-cycle
  3. Increased uptime of the asset operation
  4. SCRUM and Agile operation of the assets operation team.