Challenges and Opportunities in Big Data

Originally delivered Aug 8, 2018
Source: AIChE
  • Type:
    Archived Webinar
  • Level:
  • Duration:
    1 hour
  • PDHs:

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Big Data promises opportunities for diagnostic, prognostics and decision making. But with it comes challenges that first must be resolved. Learn more in this webinar.   

In 60 minutes, explore four Big Data challenges you are likely to face in your plant and how they can become opportunities for better diagnostic, prognostics and decision making. Examine the challenge of extracting information from high-order tensor data structures, which arise from spatially resolved photoluminescence, spectral imaging and color video. Delve into the complexities of integrating information from process flowsheet structure, casual relationships between variables and real-time sensor data. Look at managing the effects of uncertainties, disturbances, faulty sensors, a variation in operator practices and machine dirt. Plus, address nonlinear dynamic operating conditions of simultaneous discrete and continuous nature such as startup, shutdown and product changeover. Be equipped by the end of the webinar to solve these four challenges and more and fully utilize and find value in Big Data.

  • Big Data: What are the opportunities?
  • Four different types of challenges you’ll encounter
  • Extracting information
  • Integrating information

Richard D. Braatz

Richard D. Braatz is the Edwin R. Gilliland Professor at the Massachusetts Institute of Technology (MIT) where he does research in process data analytics, design, and control of advanced manufacturing systems. He received MS and PhD from the California Institute of Technology and was the Millennium Chair and Professor at the University of Illinois at Urbana-Champaign and a Visiting Scholar at Harvard University before moving to MIT. He is the senior author of the textbook Fault Detection and Diagnosis in Industrial Systems. He has consulted or collaborated with more than 20 companies...Read more

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