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Distributed Plant Data for Improved Predictive Maintenance

[+] Author Affiliations
John B. Kalanik

InStep Software, LLC, Chicago, IL

Walter Walejeski

Diagnostic Technologies & Associates, Inc., Wheaton, IL

Paper No. IJPGC2002-26038, pp. 237-245; 9 pages
  • 2002 International Joint Power Generation Conference
  • 2002 International Joint Power Generation Conference
  • Scottsdale, Arizona, USA, June 24–26, 2002
  • Conference Sponsors: Power Division
  • ISBN: 0-7918-3617-7 | eISBN: 0-7918-3601-0
  • Copyright © 2002 by ASME


The power industry generates more data than any other. The trick is collecting all of this data, down to the sub-second, storing it and making it accessible — in real time — to those who need it, when they need it for advanced decision making. This includes everyone from those on the power plant floor and executive offices to the buyers and sellers of power. Clearly integration is critical. Increasingly, utilities and large corporate power users are learning how to harness that data to capture true value. This is especially important when deregulation and rising utility costs are putting power generating companies under a microscope, forcing them to be accountable to their boards, stockholders and the public. Power generators are increasingly relying on data historians to gather information in real-time for performing trend reporting, predictive maintenance functions and optimizing overall operational efficiency.

Copyright © 2002 by ASME



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