AVEVA (Schneider Electric) > Case Studies > Tata Power Uses AVEVA PRiSM Predictive Asset Analytics Software

Tata Power Uses AVEVA PRiSM Predictive Asset Analytics Software

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Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Analytics & Modeling - Real Time Analytics
  • Functional Applications - Remote Monitoring & Control Systems
  • Sensors - Utility Meters
Applicable Industries
  • Renewable Energy
Applicable Functions
  • Maintenance
Use Cases
  • Predictive Maintenance
The Challenge

- Avoid asset failures and reduce equipment downtime 

- Identify subtle changes in system and equipment behavior 

- Gain advanced warning of emerging equipment issues 

- Monitor the health and performance of critical assets fleet-wide in real time 

- Improve maintenance planning y Enable knowledge capture to optimize information sharing between plant personnels

The Customer
About The Customer
Established in 1915, Tata Power is one of the largest integrated power companies in India with a significant international presence. The company has an installed generation capacity of 8,750 MW in India, with another 9,100 MW under development. Tata Power
The Solution

AVEVA® PRiSM Predictive Asset Analytics to help:

- Reduce unscheduled maintenance 

- Move from reactive to proactive maintenance y Quickly analyze large amounts of asset data for accurate equipment condition assessments

- Share information between groups to get the right information to the right people at the right time

- Reduce complexities in the process and technology of Tata Power fleets

Data Collected
Existing machinery sensor data
Operational Impact
  • [Process Optimization - Predictive Maintenance]

    Early warning identification of equipment problems, days weeks or months before failure.

  • [Efficiency Improvement - Asset Monitoring]

    Dynamic insights and deep-dive diagnostics for equipment behavior changes.

  • [Cost Reduction - Maintenance]

    Better maintenance planning and cost control.

Quantitative Benefit
  • Estimated cost savings are $270,000 USD.

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