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InStep Software Discusses Predictive Analytics for Nuclear Industry in New White Paper - Predictive asset monitoring for increased nuclear equipment reliability - InStepSoftware.com
InStep Software Discusses Predictive Analytics for Nuclear Industry in New White Paper

 

PRZOOM - /newswire/ - Chicago, IL, United States, 2014/06/30 - Predictive asset monitoring for increased nuclear equipment reliability - InStepSoftware.com.

   
 
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The United States alone invests more than $7 billion per year for maintenance and upgrades of nuclear power reactors, according to the World Nuclear Association.

In a new white paper, InStep Software shares how nuclear power plant operators can implement a predictive asset monitoring strategy designed to help plants achieve efficiency, reliability and performance goals. The paper explains how centralized, advanced analytic capabilities allow nuclear facility operators and engineers to maintain and optimize the performance and health of an entire fleet of assets through early warning notifications and fault diagnostics.

It goes on to cover how predictive asset monitoring software supports standard equipment reliability processes and leads to immediate and compound benefits, such as increased situational awareness, extended equipment life, lowered maintenance costs, reduced unscheduled downtime and increased asset utilization. InStep’s predictive asset monitoring solution, PRiSM, uses advanced pattern recognition to identify subtle changes in system behavior that are often the early warning signs of equipment health and performance problems. The software alerts staff in real-time of anomalies in equipment operation in addition to advanced fault diagnostics for identifying the source of the issue.
“The ability to predict and circumvent equipment failures and proactively plan maintenance is invaluable in the nuclear power industry,” said John Kalanik, president of InStep Software. “PRiSM catches small deviations in equipment operation and produces early warnings that have led to millions of dollars in avoided costs and unnecessary downtime for our customers.”

PRiSM is used by some of the largest nuclear power generation fleets in the world, including Exelon, to reduce unscheduled downtime and improve equipment performance and reliability. Download the complete white paper from the Instep Software website to learn more about predictive asset monitoring of nuclear generation fleets.

About InStep Software, LLC

InStep Software (instepsoftware.com) is a leading provider of real-time performance management and predictive asset analytics software products and solutions. InStep’s software products extend the investment in modern control, monitoring and smart devices by collecting, archiving, displaying, analyzing and reporting the information provided by these systems. Many of the world’s most successful companies use InStep’s software products to actively manage and analyze the rapidly growing amount of real-time operational, asset health and regulatory related information.

 
 
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InStep Software Discusses Predictive Analytics for Nuclear Industry in New White Paper

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Contact: Candice Hudson - InStepSoftware.com 
312-894-7837 chudson[.]instepsoftware.com
 
PRZOOM / PRTODAY - Newswire Today disclaims any content contained in this article. If you need/wish to contact the company who published the current release, you will need to contact them - NOT us. Issuers of articles are solely responsible for the accuracy of their content. Our complete disclaimer appears here.
IMPORTANT INFORMATION: Issuance, publication or distribution of this press release in certain jurisdictions could be subject to restrictions. The recipient of this press release is responsible for using this press release and the information herein in accordance with the applicable rules and regulations in the particular jurisdiction. This press release does not constitute an offer or an offering to acquire or subscribe for any InStep Software, LLC securities in any jurisdiction including any other companies listed or named in this release.

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