REGIONAL SEMINARS 2016
Kevin Geneva, Field Service Engineer
Sept 22, 2016
Using the PI Integrator for MS Azure to
Operationalize Predictive Analytics
REGIONAL SEMINARS 2016
Global food processing company
• More than 270 plants worldwide
• Over 100 years old
• Grains and Seeds are processed for use in
– Food and beverage
– Industrial uses
– Nutraceutical
– Animal Feed
2
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Centrifuge/Decanter Operation
Variables
• 25 Feed Related
• 25 Per Decanter Related to
Operational/Machine Behavior
Quick Facts
• 2 Plants
• 28 Machines
• 6 Month Average Life
• $50,000 per Rebuild
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Analysis Model
DataSources
Apps
Sensors & Devices
People
Data Intelligence
Cortana Intelligence
Action
Apps
Automated systems
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Preparing the Data
DataSources
Apps
Sensors & Devices
People
Data Intelligence
Cortana Intelligence
Action
Apps
Automated systems
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PI Asset Framework
One version of the truth
• 2 Plants
• 28 Machines
Preparation work
• Template Design
• Deployment
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System Architecture
LEGEND
P = Primary Node
S = Secondary Node (Redundancy)
FO = Automatic Interface Level Failover
NWay = Nway Buffering (send to HA PI)
*D = Direct mPI
*C = Crosslinked mPI
BLUE = ADMIN STATION
RED = Software not provided by OSIsoft
PI Data Archive Collective
PI Data Archive [HA]
Local Data
PSC
C
Process DataPI AF Server
PI Asset FrameworkLocal Architecture
PI Data Archive Collective
PI Data Archive [HA]
Local Data
PSC
C
Process DataPI AF Server
PI Asset FrameworkLocal Architecture
PI Data Archive Collective
PI Data Archive [HA]
Corporate Data
Maximo Data
PSC
C
PI AF Server PI Asset FrameworkAggregated Architecture
PI Integrator for
Business
Analytics
Firewall
SQL ServerOn Premesis
Power BI Desktop
Cortana
IntelligenceAzure ML
PowerBI.com
SQL Azure
Archive data remained on
source
Aggregated on central PI AF
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PI Integrator for Microsoft Azure
Asset Framework
(AF)
PI Integrator for Business Analytics
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PI Integrator for Microsoft Azure
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PI Event Frames
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PI Event Frames
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Data Analysis
DataSources
Apps
Sensors & Devices
People
Data Intelligence
Cortana Intelligence
Action
Apps
Automated systems
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Top Features
Variable 1 285.105583
Variable 2 214.418511
Variable 3 172.824017
Variable 4 169.973469
Variable 5 159.950095
Variable 6 130.138557
Variable 7 91.258758
Variable 8 89.65731
Variable 9 75.05133
Variable 10 36.644271
Variable 11 29.905867
Variable 12 26.395968
Variable 13 21.45298
Variable 14 19.099895
Variable 15 18.041149
Variable 16 13.537764
Boosted Decision Tree Regression - Top features
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Top Features Operations Related
Feed Composition
Machine Related
?
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Operations RelatedR
un
Lif
e
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Machine RelatedR
un
Lif
e
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Feed CompositionR
un
Lif
e
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???R
un
Lif
e
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Results Analysis
DataSources
Apps
Sensors & Devices
People
Data Intelligence
Cortana Intelligence
Action
Apps
Automated systems
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Results Analysis
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Results Analysis
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Results Analysis
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Contact Information
24
Kevin Geneva
Field Service Engineer
OSIsoft, LLC
24
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Questions
Please wait for the
microphone before asking
your questions
Please don’t forget to…
Complete the Survey
for this session
State your
name & company
REGIONAL SEMINARS 2016
Thank You