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© Copyright 2019 OSIsoft, LLCAuckland Seminar 2019 │Organiser Co-host © Copyright 2019 OSIsoft, LLCAuckland Seminar 2019 │
Organiser Co-host
Sam Pride, Technical Advisor
01/10/2019
Enabling IT/OT Convergence:
Operations Data and Advanced
Analytics
EMPOWER YOUR ANALYTICS WITH OPERATIONAL DATA
© Copyright 2019 OSIsoft, LLCAuckland Seminar 2019 │Organiser Co-host
Introduction
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• Wants to drive and enable operations
• Deep expertise in engineering
• Wants trusted, purpose built and reliable
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• Deep expertise in info systems
• Focused on digital transformation
• Early adopter of new technology
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DataManagement
&Integration
OT data is from a variety of
dynamic sources
✓The PI System standardizes &
normalizes OT data
OT data requires context to
compare fleets of assets
OT data is variable,
continuous and time based
✓ Data Management with AF/EF
& PI Integrator reduces time &
complexity of analysis
✓Operations data needs to be
prepared for use in IT tools
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Time-series Data is Not Naturally Aligned or
Contextualized
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Extending Your Opportunity Bring Operations Insights to the Enterprise
Insights
Operations
Data
scientists
IT
Expertise
ITOperations
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An ERP is not suited to operate your plant,
a PI System is not suited to be your ERP
It’s a better together story…
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Cloud Strategy
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T H E P I S YS T E M
MI C R O S O F T A Z U R E
S A P
I D O N ' T K N OW
O T H E R
ESR I AR C G I S
AW S
H A D O O P
I B M W A T SO N
G O O G L E C L O U D P L A T F O R M
S P A R K / D A T A B R I C KS
What Technologies are Needed for Enterprise Analytics?
*OSIsoft survey to
214 customers
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OSIsoft has a multi-cloud strategy designed for
repeatable patterns with major cloud vendors
It’s a better together story…
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DataScience
Virtualized PI System
Architecting for IoT
An Enterprise Data Management & Integration strategy is necessary for success
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PLC
SCADA
DCS
Data
Lake
Data
WarehouseData
Hub
Business
Intelligence
PI Server
PI Integrator for Business Analytics
Streaming
Analytics
Primary Network ingress
Machine
Learning
Streaming &
ML Insights
DataScience
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© Copyright 2019 OSIsoft, LLCAuckland Seminar 2019 │Organiser Co-host
PLC
SCADA
DCS
Data
Lake
Data
WarehouseData
Hub
Business
Intelligence
PI Server
PI Integrator for Business Analytics
Streaming
Analytics
Primary Network ingress
Machine
Learning
Virtualized PI System
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© Copyright 2019 OSIsoft, LLC
PLC
SCADA
DCS
Data
Lake
Data
WarehouseData
Hub
Business
Intelligence
PI Server
PI Integrator for Business Analytics
Streaming
Analytics
Primary Network ingress
Machine
Learning
IoT Devices
Secondary
Network
ingress
Architecting for IoT
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Advanced Analytics
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Success When Used to Augment Decisions
Greater Operational
Efficiency
Better Environmental
Protection
Enhanced Ability to
Prevent Costly Failures
Henkel (with pmOne) predict
when a transition occurs for
an exothermic reaction, saving
5% of process time.
United Utilities proved an ability
to accurately predict
combined sewer overflows 6
hours before an incident.
Invenergy (with SparkCognition)
predict catastrophic gearbox
failures at least one month in
advance.
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Five Considerations Before Starting with Advanced Analytics
1. Gaps in data collection
2. Poor data quality
3. Low # of modes
4. Unknown relationships
5. Natural skepticism
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How does the PI Integrator help you with these obstacles?
1. Gaps in data collection – filter or interpolate
2. Poor data quality – filter unreasonable values
3. Low # of modes – determine modes by indexing on events
4. Unknown relationships – work with data experts, no code needed
5. Natural skepticism – involve SME in iterative training without requiring
a lot of their time
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How do you reduce
the uncertainty of
what can be achieved
with advanced analytics ?
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Adopt Iterative Workflows that Include SMEs
Discover Explore Implement
… and use technology that support these workflows
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Discover
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Data preparation capabilities that accelerate
training algorithms or creating views for BI
Tools:
• Common nomenclature
• Aligned data
• Normalized measurements across assets
• Complex filtering by
• Asset type
• Event type
Discover
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Discover
Begin from common
nomenclature & hierarchy
Pick from measurements
that shape the model or view
Filter based on
similar assets
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Discover
Select all data from a
particular event type
Quickly preview events
after applying filter
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Discover
Include multiple
filters to clean
data
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Discover
Find all operational data
associated with all curtailment events
Remove outliers
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Operational data of an asset that is usable by
algorithms or BI Tools!!
• Asset Context
• Data Alignment
• Asset Normalization
• Filtered on a Curtailment Event Type
• Filtered for T > -273.15 C
Discover
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Discover
Select where you
want to publish
One-time bulk or
incrementally
push
Benefit from native integration to
AWS, Azure, Hadoop, and SAP HANA
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Discover
What if you want to
analyze events
relative to each other?
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Discover
Index views
of operational
data by
events
Compare
events on a
timescale
relative to
start of the
event
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Explore
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Explore
Adjust a new
view starting from
the previous view
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Implement
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Implement
Create a stream
of features for
your algorithm
Begin from the
shape of your
training data
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Implement
Adjust object if
needed and
determine how it
updates
Pick a messaging
hub to stream to
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Summary
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Capabilities That Streamline
Advanced Analytics
• Context
• Normalization
• Event Marking
• Iterative Workflows
• Operationalization
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Summary
• Advanced Analytics
– Start with a small project that involves SMEs
– Use an iterative approach to your projects
• PI Integrators
– Support analytics workflows with drag-and-drop data preparation for SMEs
– Provide native integration to a variety of advanced analytics platforms and BI Tools
– Sends curated data via bulk and incremental uploads and streams
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PI System Accelerates and Operationalises Advanced
Analytics
Automation SystemsAssets Edge Devices / Sensors IoT solutions
data warehouse
stream
processor
data lake
machine learning
business
intelligence tool
Operational Data Infrastructure
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push trained algorithm
110111010111110
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