Continuous Data Mining to Sustain Advanced Process Control and Process Capability

Source: AIChE
  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Spring Meeting and Global Congress on Process Safety
  • Presentation Date:
    April 30, 2013
  • Duration:
    30 minutes
  • Skill Level:
  • PDHs:

Share This Post:

Multiple factors can affect the performance of advanced controls.  These may be due to changes associated with the instrumentation, regulatory controls, or the process itself.  If not detected and diagnosed, the effect can be a partial loss of benefits, or in the worst case, the complete loss of benefits due to the controls being switched off.   It is therefore important to monitor not just control-specific metrics, but also process measurements and process metrics (KPIs) that may not directly be used by the advanced control system.  This presentation will describe a “big data small footprint” approach to statistically analyzing large amounts of historian data to determine when significant changes occur, and identifying candidate variables to facilitate cause and effect determination.  Plots and reports are automatically generated for control engineers, process engineers, and instrumentation technicians.   A benefit of the approach is bringing these groups together to solve problems and ensure process objectives are met.  Examples are presented to highlight the approaches and statistical techniques used.

Once the content has been viewed and you have attested to it, you will be able to download and print a certificate for PDH credits. If you have already viewed this content, please click here to login.



Do you already own this?



AIChE Member Credits 0.5
AIChE Members $15.00
AIChE Fuels and Petrochemicals Division Members Free
AIChE Undergraduate Student Members Free
AIChE Graduate Student Members Free
Non-Members $25.00