Managing Asset Performance

Obtaining a single, unified view of overall Asset Health, Status and Performance is challenging:

Data Disparity: Data is isolated across islands of information with no common understanding.

Data Aggregation: Aggregating disparate data usually results in data swamps with little consistency and reference-ability across assets, operations and processes.

Data Organization: Organizing data into canonical forms and standards is manual, time consuming and usually fit for purpose.

Data Analysis and Visualization: Nounified view – single pane of glass - to visualize and present the variety of data.

Data relevancy: Identifying important and relevant data is usually ad-hoc, reactive and resource intensive.

Data Availability: Assets with out sensors or online condition monitoring – difficult to collect health and condition information – manual tasks.

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  • VENDOR
  • CUSTOMER
  • 1) GE for GE.

    2) GE for those looking into GE services.

    3) GE as a thought leader in industry, setting standard and precedent.

  • SOLUTION
  • Value by providing integrated performance data in the right context to identify opportunities for improvement based on facts:

    Asset Centric: Connect and integrate with multiple data sources to and relate it to your assets.

    Digital Transformation-Enable edge to cloud and multiple data source connectivity: Cloud-ready for APM, Predix , or third part data access.

    Data Modeling and Mapping and Organization: Automated AI driven integration, organization, and modeling of a variety of disparate data types to a canonical model.

    Complex Event Processing: Use analytics to identify relevant data and events. Develop and execute strategies, actions and recommendations, based upon historical and dynamic data, which is obtained by monitoring conditions in real time. Core foundational tools like Queries, Graphs, GIS Mapping, Benchmarking and advanced search to view and find the right information fast.

    Accelerate Time to Value: Real time view of asset health status, provides pro active asset risk analysis and KPI’s.

  • DATA COLLECTED
  • Big data collected for analytic optimization.

  • OPERATIONAL IMPACT
  • Impact #1

    Achieve less unplanned downtime by predicting equipment issues before they occur.

    • Predictive analytics
    • Case and collaboration management
    • Knowledge management
    • Root cause analysis
    • Reliabilityanalysis
    Impact #2

    Ensure asset integrity and compliance by monitoring changing risk conditions.

    • Hazard analysis
    • Safety lifecycle management
    • Risk based inspection
    • Inspection management
    • Thickness monitoring
    Impact #3

    Optimize across availability, reliability, risk, and costs through intelligent asset strategies.

    • Reliability centered maintenance • Failure mode and effects analysis • Strategy management
    • Strategy library
    • Lifecycle cost analysis
    • Financial and risk simulation
  • QUANTITATIVE BENEFIT
  • Benefit #1

    Anytime, anywhere, unified view of your assets’ current state, and health.

    • Machine & Equipment Health
    • Connectivity
    • Data management
    • EAM integration
    • Condition monitoring
    • Data analysis and visualization • Criticality analysis
    • Event management
    • Recommendation management • Benchmarking
  • SOFTWARE
  • INDUSTRIES
  • Other
  • FUNCTIONS
  • Other
  • ENABLED CAPABILITIES
  • CONNECTIVITY PROTOCOLS
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