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 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 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 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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