Tata Power

The utility has already experienced a number of initial operational and maintenance improvements and has been able to manage risk, mitigate damage, and identify and correct asset performance problems continuously and in real time

Tata Power

Tata Power uses Predictive Asset Analytics software to continuously monitor the health and performance of critical assets. Tata Power uses PRiSM Predictive Asset Analytics for early warning notification of equipment problems.

Goals

  • 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
  • Enable knowledge capture to optimize information sharing between plant personnel

Challenges

  • Reduce unscheduled maintenance
  • Move from reactive to proactive maintenance
  • Quickly analyze large amounts of asset data for accurate equipment condition assessments
  • Information sharing between groups to get the right information to the right people at the right time
  • Complexities in the process and technology of Tata Power fleets

Results

  • Early warning identification of equipment problems, days weeks or months before failure
  • Dynamic insights and deep-dive diagnostics for equipment behavior changes
  • Improved equipment reliability and performance
  • Better maintenance planning and cost control
  • Knowledge capture of equipment failure modes

"We found Predictive Asset Analytics to be an effective tool in the predictive diagnostics space for detecting functional deviations and impending failures at an early stage for initiating suitable prioritized maintenance actions for enhanced reliability of critical power plant equipment."

– Praveen Chorghade, Chief - Core Technology and Diagnostics, Tata Power

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