Predictive Asset Maintenance for Utilities

New economic and regulatory forces are requiring utilities to rethink ways to prevent asset failures and optimize maintenance cycles. We approach the problem by providing software and services to help you:

• Reduce downtimes by using enterprise business intelligence capabilities to gain near-real-time insight into the performance of sites and assets, enabling maintenance engineers to react and solve issues quicker at every level.
• Optimize maintenance cycles using advanced optimization algorithms and solvers to expand maintenance cycles without jeopardizing asset uptimes or risking failures.
• Reduce unscheduled maintenance with predictive and near-real-time performance alerts that enable maintenance teams to fix issues during already-scheduled maintenance outages and choose the right time to replace degrading assets in a planned and more cost-efficient way.
• Improve root cause analysis using state-of-the-art analytics and predictive data mining capabilities to:
  • Drive continuously improved reliability, equipment efficiency and quality.
  • Identify the real drivers of performance issues out of hundreds or even thousands of measures and conditions.
  • Determine and initiate the best corrective action.
• Gain greater visibility into maintenance issues with a maintenance data model that captures large volumes of data regardless of format or source – from legacy to modern MES, ERP, CMMS and other systems – then transforms, standardizes and cleanses the data to prepare it for analysis.

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Only SAS delivers the entire scope of analytic and predictive capabilities that utilities need to ensure peak asset performance and minimal downtime. With SAS, you get:

• Data integration and management. Combine sensor data – which forms the basis for predicting asset failures – with inspection, maintenance, historical, inventory and warranty data, etc., into a single database for monitoring, model development, root cause analysis and reporting.
• Predictive modeling. Because asset characteristics vary widely and performance thresholds change over an asset's life cycle, SAS provides best-in-class data mining so you can predict asset performance accurately, before problems occur.
• Integrated reporting/business intelligence. Access the latest information on key maintenance and reliability performance indicators and drill down to performance trends through a Web-based interface, without having to be an expert in statistics.
• An integrated analytical workbench. A highly visual workbench lets engineers better understand complex assets and data mining techniques (e.g., pattern analysis) to more easily identify root causes and precursors that lead to problems.
• Model management. Ensure peak performance throughout an asset's life cycle by:
  • Automatically monitoring the accuracy of scores of predictive models.
  • Issuing alerts once a threshold indicating poor prediction quality is reached.
  • Tracking actions from model development through retirement for audits.

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