The business of reliability management is to keep equipment up and running or available to run while managing the costs to operate and maintain it. Companies have made significant investments in condition-monitoring instrumentation and information infrastructure, but each firm will have a unique point of diminishing returns. Some companies have established centralized collaboration centers and have re-engineered their work processes in order to break through this diminishing- returns barrier. Others that are not yet ready to make the full change can apply five critical success factors observed in established collaboration centers that have demonstrated reliability-performance improvements:

  1. Putting equipment operating condition into context. Dynamic equipment requires views of mechanical condition in the context of the overall process. This applies both to rotating equipment and to processing equipment.

  2. Managing data by exception. The blizzard of data now available requires machine learning and management by exception to reduce data into usable information.

  3. Using both predictive analytics and deep diagnostics as complementary technologies that operate in different timeframes. Deep diagnostics include vibration signature analysis and cylinder performance analysis, while predictive analytics employs pattern recognition algorithms to detect minor events and anomalies.

  4. Communicating observations, diagnoses, recommendations, and learnings through collaboration tools. Such tools add value on multiple fronts that include knowledge transfer and equipment-specific learning such as Root Cause Analysis.

  5. Managing the findings in an asset-management system or collaboration system. This provides feedback for further improvement.

A case-study example that uses predictive analytics will demonstrate these concepts, beginning at event detection and extending through diagnostics, collaboration, field action, and information consolidation.

The direct deliverable is time: time for engineers to focus where they add most value, time to plan equipment outages that might otherwise have been unplanned, and time to produce oil and gas that might be lost to unplanned downtime.

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