This document discusses D square, a company that provides real-time decision support for production excellence. It focuses on transforming industrial data into useful information sources to support better decision making. Key topics covered include using data mining techniques like soft sensors, anomaly detection and predictive analytics. A case study is presented on developing an operator advisory system to analyze differences between operator teams and provide action advice to improve process performance.
5. Production meeting Shift logbook
ENTERPRISE RESOURCE PLANNING D square: http://www.dsquare.be
Shift handover Plant conditions
From data sinks to information sources, from iT to IT
Friday 30 March 2012
6. Production meeting Shift logbook
ENTERPRISE RESOURCE PLANNING D square: http://www.dsquare.be
Shift handover Plant conditions
PRODUCTION QUALITY EFFICIENCY MAINTENACE
PIMS LIMS ALARM EVENTS
SCADA - DCS
PROCESS CONTROL
From data sinks to information sources, from iT to IT
Friday 30 March 2012
7. From data sinks to information sources, from iT to IT
Friday 30 March 2012
8. http://www.dsquare.be
Process Process Process
watchdog logbook coach
Real-time decision support
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11. Data mining flavors
• Soft sensors • KPI prediction
• Anomaly detection • Planning and scheduling
• Adaptive control • ...
• Defect classification /
analysis / prediction
• Root-cause analysis
• Operator action advise
Data mining: science, art or magic?
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12. Data mining success criteria
• What is the question?
• Is the answer in the data?
• Involvement & expectations?
• Where is the expert?
• Is there sufficient context?
Data mining: science, art or magic?
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15. • Significant variation on the decisions taken by panel operators
• Variations in operator behavior are believed to have significant effects on
important process KPIs such as steam flow
• Expertise of senior operators may not be fully exploited to assist more
junior operators when difficult decisions need to be made
• Data of operator actions and their effects is readily available in todays data
historians.
• There is a gap between the operational and managerial level that makes it
difficult to implement performance optimal plant operation. It is
hard for managers to relate operator behavior to process performance.
• A feasibility study has indicated that potential ROI of a decision support
system is signficant
Motivation
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17. • Determined influence factors for steam loss
• Differential operator analysis
! Across teams
! Problems due to inefficient shift handover
• Implementation of an operator advisory system
(process GPS)
! Action advise
! Action insight
Results
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18. http://www.dsquare.be
D square: http://www.dsquare.be
Production excellence through real-time decision support
Friday 30 March 2012