Industrial Software

Leverage IIoT to Predict Asset Failure and Reduce Cost

Technology triggers like the Industrial Internet of Things, big data analytics, mobility and workflow collaboration represent new opportunities for significant improvements in asset reliability, efficiency and safety in the power industry. The market is shifting to a holistic and operations-centric view where proactive and predictive maintenance opportunities empower front-line personnel to act before costly failures or downtime occur.

Comprehensive maintenance programs allow utilities to be more efficient and effective in their operations and maintenance processes. A progressive maintenance strategy includes a combination of preventive, condition-based, predictive and reliability-centered measures. The higher you move up the maintenance maturity pyramid the more strategic and proactive your approach becomes and the more advanced warning of equipment problems is required.

When managing a large fleet of assets across numerous sites, making sense of the streams of operational data from multiple systems and from remote sources can become an impossible task. Most utilities today are using real-time enterprise historians to consolidate disparate data sources for a more comprehensive view of plant performance. To achieve the next level of operational efficiency, companies are building on that data management foundation with condition based and predictive asset analytic solutions.  They are leveraging the existing data to further improve operations by providing early warning detection of equipment issues before they lead to failure.

Predictive Maintenance Webinar

Predictive asset analytics software solutions use continuously streaming time-series data to help organizations improve operational performance by using predictive algorithms to calculate and predict normal asset behavior. Schneider Electric’s Avantis PRiSM software is based on algorithms that use advanced pattern recognition and machine learning technology, which has been shown to provide weeks to months of early warning notification of deviations in operational performance in power plants. In a single warning notification, PRiSM has been proven to save $7 million in avoided costs at a US based power utility.

Savings Achieved with Predictive Maintentance

The end goal of implementing a comprehensive maintenance program that moves from a reactive to a proactive approach is to deliver the greatest economic return for all asset types. Using the comprehensive Enterprise Asset Performance Management solution offered by Schneider Electric, power utilities can collect, store and monitor asset health information to identify, diagnose and prioritize impending equipment problems – continuously and in real time.

Enterprise Asset Performance Management helps grid operators, maintenance teams, systems engineers and others take advantage of the massive amounts of data available today and use it to make real-time decisions that have a positive impact on asset reliability and performance. Power utilities can transform their maintenance strategies by leveraging data and technology to achieve the greatest return on every single asset.

To learn more about Enterprise Asset Performance Management from Schneider Electric, join us for a complimentary webinar hosted by PennEnergy. On the webinar, we will references success stories on how utilities are seeing tremendous ROI using predictive analytics to reduce downtime and maximize O&M expenditure. Click to register for the webinar.


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