Sensor Data Management & Analytics: Advanced Process Control

Michael O’Connell, PhD
Chief Analytics Officer
@MichOConnell
Sensor Data Management &
Analytics
Advanced Process Control

Data from the Cars
Brakes
Tyres
Fuel / Energy Storage
Aerodynamics / Drag / Downforce
Engine Temperature / Condition
300 sensors
50K channels of data
<1 sec increments
500 GB / weekend

Great Mercedes Car
Season Start
• 1st and 2nd in first 5 races
• 1st in first 8 races
Season to Date
• 12 of 17 race wins
Car Constructor Champions
• Won after 13 of 17 races
Certain to win Driver
Championship
• Lewis will likely clinch in Austin
Hamilton 2 1 1
Bottas 1 2 2
Hamilton 2 1 1 1
Bottas 1 2 3 4
Hamilton 1 3 1 9
Bottas 2 5 2 15
Hamilton 1 2 2 4
Bottas 8 3 3 5
Hamilton 1 3
Bottas 2 1

Visual Analytics & Data Science at Mercedes

6
• Value of Sensor Analytics -- Case Studies
• Manufacturing Process Control
• TIBCO Technology
• Machine learning and edge devices
• Links and Assets
Sensors, Analytics, Data Science

TIBCO Spotfire Visual Analytics

Energy – Drilling &
Production Optimization
Production Surveillance
Drilling Operations
Real-Time Features, ML Models, Visual Analytics

9
Transformer
ESP Controller
Well head sensors
P
P P
Controller
VSD
RTURTU
Remote Terminal Unit
Antenna
Real-time sensor data
• Electrical parameters
• Downhole pressures and temperatures
• Surface pressures
Sensor Data monitored 24x7
• Prevent failures & extend equipment
life
• Enhance production / keep systems
running
Oil & Gas Production
https://community.tibco.com/wiki/ai-demand-data-science-operations

10
Insight to Action on Sensor Data
Anomaly Normal Function
Insight on
Historical Data
Apply Data
Prep + Model
to new Data

Wind Turbine Operations
60K turbines
1K data points / minute / turbine
Asset Management

13
Weather
Forecast
Electricity Price Grid
Turbines & Sensors
35,000 turbines connected (60 GW)
60,000 turbines in 75 countries (110 GW)
1000+ sensors / turbine
1000 data points / minute / turbine
Asset Data / Analytics
Turbine event logs, vibration, oil, grease,
image data
ERP master data, service reports, spare parts
100+ TB asset data
1,600,000,000 analytics last 5 years
80,000 notifications last 5 years
Asset Management Anemometer
Temperature
Direction
Power output
Pressure
Temperature
Rotation
Vibrations
Event Logs
Counters
Configuration
Pitch
Position
Speed
Loads

Anomaly Detection
Hi Tech Manufacturing
Manufacturing Process
Control
Run to run control
Fault Detection
Yield Optimization

Feedforward Run-to-Run
controller
Run-to-Run
controller
Feedback Feedback
Shop Floor: Tools
Process
flow
Metrology Process ToolProcess Tool Metrology
Fault Detection
models
Fault Detection
models
ACTIONS
MES
Tool Maintenance
MES
Product Hold
Email
Notification
Stop Eq.
Process
Fault Detection, Virtual Metrology
Run-to-Run control
Edge Tier: Pre-process
Edge analytics:
Extract useful features
TIBCO EMS, BW, Flogo
Platform Tier: Real-time Decisions
TIBCO Streaming
Enterprise Tier: Visualize & Manage - Business Apps
TIBCO Spotfire, Data Virtualization
Reports & Dashboards
Data Science Tier:
TIBCO Data Science
Models: Build, Evaluate &
Push to Production
MES to Product Optimization: APC
Virtual Metrology

16
Digital Twins for Semiconductor Manufacturing Yield: Wide-and-Big Data Analysis
Build Models to relate Product Yield Failure Modes ( Yi ) with Process Parameters ( Pi )
Start
Process
Step 1
Process
Step i
Measure-ment
Step 1 Process Step i+2
Process
Step n
・・・・・・
Yi = f(P1 , P2, P3, … Pn)
Digital Twin
Yield Models
P1 Pi Pi+2 Pn
Equipment Sensor Data
Pi+1
Physical Measurement Data
Process Optimization
Process Monitoring
Process Control
~ 1K Steps,
> 1M Process
Parameters
Run continuously to capture new
relationships as they emerge
Equipment Names
Digital Twin for Yield
Y = f(Y1, Y2, Y3, … Yn )
Yield,
Yield Components or
Clusters
Product Test:
Pass / Fail, Failure Modes

17
• Not just Big Data – many rows: lots, wafers, die, units
• Also Wide data – many columns: > 1M Process Parameters
• Sensor traces
• Time series for every sensor on each machine in each run
• Physical Measurements
• Film thickness, Critical dimensions, Layer-to-layer overlay, Defect classes & counts
• Equipment and Process attributes
• Machine and component IDs, Process Recipe info
• Supplies
• Chemical batch IDs, QA sample data
The Extreme Challenge of Big & Wide Data
“Today [semiconductor] fabs collect more than 5 billion sensor data points each day. The challenge is to turn
massive amounts of data into valuable information.”
- Ann Kellehere, VP of the Technology and Manufacturing Group, Intel

18© Copyright 2000-2019 TIBCO Software Inc.
Anomalies v Lot Yield Loss v Time
Clusters: Anomaly Signatures
Variables associated
with marked
anomalies above
Cluster 2 highlighted (green)

Machine Learning Model
Yield loss = f (process parameters)
Data Preparation
Wide Data Analysis
Variable Dimension Reduction

Time Series
Sensor Data

24
SAX: Symbolic Aggregate ApproXimation
coding technique for comparing time series patterns @ scale
J. Lin and E. Keogh. iSAX: Indexing and Mining Terabyte Sized Time Series.
Proceeding. KDD '08 Proceedings of the 14th ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining, p. 623-631, 2008.
SAX Encoding

Wide Data Variable Selector
Correlate SAX data to yield loss

Correlation Histogram
Filter out low correlations

Machine Learning Model
Yield loss = f (process parameters)

30
Solution Architecture
• In-database parallelized computing
• Leverages Hadoop, Apache Spark™
• In-memory dedicated fast server • Interactive in-memory
visualization environment
Data Prep, feature
engineering & selection
Further feature selection
& model building
Visualization of
Results

DATA SOURCES
TIBCO Analytics Transformation platform
Core App 1.. Edge App 2..
Streaming
Sources
In-memory
Data Grid
...
REPORTING/VIZDATA SCIENCE
ANALYTICS
ACTIONS
Data Science Operational Analytics
INFORMATION MANAGEMENT
Metadata
(Data Governance,
Data Catalog)
MDM / RDM
DATA OPERATIONS
Data Virtualization
Master and
Reference Data
Management
Data Store 1 Data Store n EDW/Lake
Metadata
Master &
Reference Data
Transactional
Data
Powered by shared data assets
EVENTS
Streaming /
Events
INTEGRATION
Hybrid
Integration
API
Management
Spark Compute & Store
Visual Analytics
METADATA
AUGMENT
INTELLIGENCE
UNIFY
DATA
INTERCONNECT
EVERYTHING
Cloud Native Open Platform AI Foundation

Visual Analytics
& Data Science
Metadata
Master &
Reference Data
Transactional
Data
REPORTING/VIZDATA SCIENCE
ANALYTICS
ACTIONS
Data Science Operational AnalyticsVisual Analytics

TIBCO Spotfire
Augmented
Search & AI-Powered Insights
Start in seconds, instant insights
Automated
Automagical Dataflows
Author & audit with automatically
recorded data flow steps
Agile
Low Code Analytic Apps
Agile exploration made even easier
Aware
Spotfire Data Streams
Real-time awareness and action
A(X) Experience = Analytics, Accelerated
Visual Analytics
& Data Science

34
AI Suggestion Engine
1. Spotfire User selects target variable
2. AI Suggestion engine discovers variable
relationships to target
3. AI Suggestion engine displays smart
visualizations in order of strength
• Best practice graphics
4. Few clicks to AI-guided, brush-linked
analytics application
• User styles, adorns graphics and layout
Spotfire Recommendations
AutoML for Business Analyst
Visual Analytics
& Data Science

35
Natural Language Query
• User searches multiple data tables +
relationships + Spotfire help
• NLQ displays best-practice graphs
• Sorted by AI Suggestion Engine
• Brush-linked analytics application
constructed from chat interaction
Spotfire: NLQ Search
Search on data, relationships, software help
Visual Analytics
& Data Science

AI
Shows me where to look
Explains what I see

37
Real Time Data Visualization
• User selects time window
• Data Streams shows live-updates
• Calculations (forecast) on live visuals
Users and Data
• Many real-time data sources supported
• Simple data source connector
• Brush-linking – static & real-time visuals
• Same behavior as rest of Spotfire
Spotfire: Data Streams
Real-Time Awareness and Action
Visual Analytics
& Data Science

Modeling
+ Visual composition
+ Multilingual Notebook
+ Native ML & OS
+ AWS, AZURE, GCP
+ AutoML, data prep
Operations Deployment
+ Model lifecycle mgt
+ Batch automation
+ Real-time event processing
+ REST, Apps, embedding
Data Access / Prep
+ Distributed compute
+ Feature engineering
+ Reusable templates
Medic eg researcher
on epidemic
monitoring
Engineer eg
aerodynamics engineer
Marketeer eg
customer engagement
analyst
Data Scientist
Citizen Data Scientist
Data Scientist
Citizen Data Scientist
Analytics Operations
IT / Software Engineer
FUNCTION
USER
or
AUTOMATION
Business User
Analytic Operations
IT / Administration
Business Applications
+ Engineering/IoT
+ Customer analytics
+ Risk management
+ Supply Chain
TIBCO Data Science
Visual Analytics
& Data Science

AI
Can be explained
Can be put into production

Videos Shown
1. Spotfire AI Suggestion Engine
2. TIBCO Data Science AutoML
3. TIBCO Connected Intelligence Cloud –
Customer Engagement App
AI Foundation
• Automate Manual Tasks
• Promote Innovation
Business Analyst | Data Scientist | Developer
Spotfire AI Foundation Videos Shown
1. Spotfire
AI-Suggestions
2. Data Science
Customer Targeting
3. Operations
Case Management
Spotfire and Data Science AutoML
Visual Analytics
& Data Science

TIBCO Flogo and Edge ML
TIBCO Flogo is an open-source project for edge integration and IoT Apps
Model inferencing on-device
• TensorFlow models trained for image
recognition, accelerometer patterns, etc.
• Inferencing executes on-device or as a
serverless function
Software Design
• Models trained in TIBCO Data Science -- point-
click or Tensorflow in Notebook
• Deployed within Flogo Applications
• Additional on-device data prep and rules logic
using Flogo Activities
IoT Case Studies
• Image recognition of damaged packages
• Coffee maker image recognition of vessel
(TIBCO-Jabil partnership)
• Accelerometer state recognition

TIBCO Factory Solution Accelerators
Improve OEE
Reduce Costs
Optimize Mix
Deliver On Time
Holistic Factory Monitor
Smart SchedulingGlobal View
Factory View
Machine / Sensor View
Download this accelerator
from the TIBCO Exchange

Machine Learning: Anomaly Detection
SOM
Autoencoder
X f (X) z f ’(z) Xhat

AI on Demand: Data Science in Operations
Cloud Starters, Accelerators, Analytic Apps
Thoughtleader-led solutions
AI on Demand
Data Science in Operations

46
Questions & Contact
Thank you!
Michael O’Connell
TIBCO
moconnell@tibco.com
@MichOConnell
TIBCO Community
community.tibco.com
TIBCO Exchange
community.tibco.com/exchange
Spotfire Trial
www.tibco.com/products/tibco-spotfire
TIBCO Tech Blog
community.tibco.com/blog

Questions & Contact
Thank you!
TIBCO Community
community.tibco.com
TIBCO Exchange
community.tibco.com/exchange
TIBCO Tech Blog
community.tibco.com/blog
Spotfire Trial
spotfire.tibco.com/trial
Michael O’Connell
TIBCO
moconnell@tibco.com
@MichOConnell

Sensor Data Management & Analytics: Advanced Process Control

Sensor Data Management & Analytics: Advanced Process Control

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