Advances in Asset Health Monitoring and Predictive Analytics

Source: AIChE
  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Spring Meeting and Global Congress on Process Safety
  • Presentation Date:
    April 11, 2016
  • Duration:
    30 minutes
  • Skill Level:
    Intermediate
  • PDHs:
    0.50

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Big data is a hot topic in many commercial and industrial applications, and it also applies to the operation of refineries and petrochemical plants through the use of sensor data to improve operations. Online data from sensors, often wireless, can be analyzed and used to provide plant operators with the actionable information to make timely decisions for improving asset reliability and efficient operations.

Big data from sensors can be analyzed by a variety of commercially available software programs, each of which can evaluate sensor data for abnormal operation and provide alerts. Properly trained operations are invaluable in this process, as they not only act on information from predictive analytics software, but often make decisions on their own based on sensor data.

Online data from sensors has been available for decades, but a transformation is now taking place due to the low cost and quick installation time for wireless sensors when compared to their wired counterparts.  The term pervasive sensing describes the application of wireless sensors to areas which were formerly too expensive to monitor with wired instruments, leading to the creation of big data.

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AIChE Member Credits 0.5
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