From Diagnostics to Predictive Analytics - an Evolution in Total Asset Management

Developed by: AIChE
  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Spring Meeting and Global Congress on Process Safety
  • Presentation Date:
    March 31, 2014
  • Duration:
    30 minutes
  • Skill Level:
  • PDHs:

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From Diagnostics to Predictive Analytics – An Evolution in Total Asset Management

Asset owners of critical power generation and oil & gas production equipment are faced with the eternal challenge of increasing machinery availability and performance while reducing energy consumption and maintenance costs and ensuring that the risk of failure is eliminated.  Machinery diagnostics engineers with the Bently Nevada team have decades of experience in the application of machinery protection, monitoring and diagnostics and are integral to enabling asset owners realize goals listed above.  Now, they are increasingly transitioning towards helping organizations be more proactive through the application of predictive analytics enabled by similarity based modeling technologies.  The result is a combination of insight and foresight into systems and processes delivering unparalleled value.

This paper presents the most successful machinery monitoring and diagnostic methodologies applied in industry today, and lays out the foundation of techniques based on predictive data models, uniquely designed for individual equipment.  Advisory capabilities such as equipment health and performance threats, asset KPIs, sensor problems and data infrastructure issues as well as collaborative support from remote experts are all presented.  The paper also outlines various modeling and analytics technologies and reveals the essence of the robust similarity based modeling engine embedded in SmartSignal, a platform for the future, and concludes with case studies documenting tangible results from such implementations.




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