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TRANSCRIPT
Mike Alperin
Industry Consultant
7/14/2016
Advanced Analytics for High Tech Manufacturing:
Process Control Systems
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Agenda
Tibco Analytics
History and Theory
Basic Capabilities
Demos
Predictive Models
Alerting
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• Integration• Business Process Management• API Management
• Data Visualization & Dashboards• Advanced Analytics• Streaming Analytics
Visualizing Data in Spotfire
Analytics Spectrum
Spotfire in Manufacturing
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Selected Spotfire Manufacturing Customers
Supply
Chain
• Demand Forecasting• Order Management• Inventory
Optimization• Supplier
Performance• Transportation
Analytics• Early Warning
Systems
Manufacturing
Operations
• Real-time Equipment & Process Monitor
• Process Capability• Optimize
Maintenance• OEE & Factory
Productivity
Field Service &
Support
• Optimize Maintenance
• Repair & Customer Service Analytics
• Supplier Performance
• Order Management• Inventory
Optimization• Transportation
Analytics
Product Quality &
Reliability
• Real-time Quality Monitor
• Root Cause• Reliability• Warranty
Sales &
Marketing
• Customer Needs
Product Requirements
• Market Segmentation
• Propensity• many others
Manufacturing Use Cases
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History and Theory
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© Copyright 2000-2016 TIBCO Software Inc.
• Control Chart developed by Walter Shewhart at Bell Labs in 1924
• Adopted by Japanese industry after WWII. ‘Quality Revolution’
makes it back to US in 1980s – Toyota, Ford, Motorola
• Statistical methods used to monitor and control a process
• Ensures that the process operates at its full potential.
Statistical Process Control
• Make as much good stuff as possible with a minimum of bad stuff
• SPC can be applied to any process where output can be measured:• Manufacturing
• Marketing & Sales
• Medical / Healthcare
• Services, etc.
Walter Shewhart’s first Control Chart
Western Electric Candlestick phone
Voice of the ProcessAssess temporal variability
Key Metric: Instability Index = St = % out-of-control data points
Voice of the CustomerCompare actual distribution to Spec Limits
Key Metric: Process Capability Index = Cpk= (mean – closer spec limit) / 3 Sigma
ASTM International
Process Control vs. Process Capability
Control Limits
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The Normal Distribution
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Western Electric RulesProbability
0.3 %
1 %
1 %
Basic Capabilities
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X-bar R Control Charts with Limits and Rules set-upX-bar R Control Charts with Limits and Rules set-up
• Solution Areas
• Assess Process Capability
• Process Control: Detect changes from baseline
• Root Cause Analysis
• Alerting
Process Capability & Control
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• Capabilities
• High Level Summary
• Spec Limits
• Trend Charts
• Visualize Distributions
Process Capability
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Process Capability Summary with drill-downProcess Capability Summary with drill-down
Summary with drill-down to Control ChartsSummary with drill-down to Control Charts
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Process Control
• Capabilities
• Shewhart charts: Xbar-R, Individual-Moving Range, EWMA, Cusum
• Control Limits: Setting & Storing
• Western Electric or Nelson rules
• Advanced: multivariate, Predictive models
Interactive Limit Setting on Individuals Control ChartsInteractive Limit Setting on Individuals Control Charts
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Process Control
• Capabilities
• Shewhart charts: Xbar-R, Individual-Moving Range, EWMA, Cusum
• Control Limits: Setting & Storing
• Western Electric or Nelson rules
• Advanced: multivariate, Predictive models
Limits Set-up for Exponentially Weighted Moving Average Control Charts. Limits Set-up for Exponentially Weighted Moving Average Control Charts.
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Process Control
• Capabilities
• Shewhart charts: Xbar-R, Individual-Moving Range, EWMA, Cusum
• Control Limits: Setting & Storing
• Western Electric or Nelson rules
• Advanced: multivariate, Predictive models
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Root Cause Analysis
• Investigate problem cause
• No single method or analysis technique
• Develop specific workflow most relevant for each industry / use case / company / etc.
• Capabilities
• Basic drill-down to visualizations
• Classic Statistics: Correlation, ANOVA, Regression, etc.
Equipment Commonality Analysis - ANOVAEquipment Commonality Analysis - ANOVA
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Root Cause Analysis
Root Cause - Machine Learning (GBM) – Advanced Root Cause AnalysisRoot Cause - Machine Learning (GBM) – Advanced Root Cause Analysis
• Investigate problem cause
• No single method or analysis technique
• Develop specific workflow most relevant for each industry / use case / company / etc.
• Capabilities
• Basic drill-down to visualizations
• Classic Statistics: Correlation, ANOVA, Regression, etc.
• Machine Learning
Demos
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Customer Case Study
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© Copyright 2000-2013 TIBCO Software Inc. 24
Electronic Test Equipment Calibration:
Discovery, Trouble-shooting, Resolution:Tens of Service Centers– 100s of calibrations– 1000s of tests– 100,000s of measurement points
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Daily email summary: highlights two issues:
Drill-down on first issue yields 3 observations:1. Variation > Measurement uncertainty significant issue
2. Not related to calibration software version3. Smaller prior variations have been seen previously
Discovery + 2 min Discovery + 2 min
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Discovery + 10 min
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Discovery + 15 min
© Copyright 2000-2013 TIBCO Software Inc. 28
Advanced & Predictive Models
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Automotive Warranty Early Warning System
Business Problem
• Major Automotive Manufacturer
• Costs of producing unreliable product
TIBCO Solution
• Rapidly detect and respond to warranty problems
• For every component: Model Fail rate
• Use model to predict Field Fail rates
• Alert when Field Fail rates exceed predictions
Model: Fail rate = f(production date, days in service, model)
Control Chart
showing actual and
predicted fail rates
for a component
Yield Differences between Batches with varying Sample Sizes
Problem
• Batch Sample Sizes Vary
TIBCO Solution
• Funnel Plot to identify outlier batches with abnormally high yield loss
• Trend yield data
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Alerting: Scheduled to Real-time
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REAL-TIME ANALYSIS BATCH ANALYSIS
PROCESS ZONE STRATEGICTACTICALOPERATIONSEXECUTION
TIME INCREMENT
IMPORTANCE OF AUTOMATION
Quarters/Years
Months/Quarters
Hours/Days/Weeks
Seconds / Minutes
Not ImportantImportantNecessary
Analytics Time Scales
Automated Scheduled Alerting System for Control Charts. Automated Scheduled Alerting System for Control Charts.
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Scheduled Alerting
• Capabilities
• Scheduled Alerting using Spotfire Automation Services
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Scheduled Alerting – Rule and Alert Configuration
Scheduled Alerting – TERR enables advanced rules
Rule Breaches above are calculated with a TERR data function
This simple chart actually drives the alerting
Solar Cell Manufacturing
Business Problem
• Solar Cell Manufacturer – 600K Wafers / day
• Immediately Troubleshoot Process when producing bad product
TIBCO Solution
• Real-time Monitoring of Equipment and Product critical metrics:
• temperature, pressure, resistivity
• Alert when metrics beyond limits
• Root Cause Analysis to improve process
Results• Improved solar cell efficiencies
• Reduced equipment downtime
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“For every 1% increase in shipped product, we make $11MM in profit. The demand is there, we just need to fulfill it.”
- Head of Quality, Solar Panel Manufacturer
“For every 1% increase in shipped product, we make $11MM in profit. The demand is there, we just need to fulfill it.”
- Head of Quality, Solar Panel Manufacturer
Real-time Operational Visibility & Alerts: Tibco Solution
(E-mail) Alert
Drill-down
Real-time Monitor
Diagnostic Analysis
• Real-time operational visibility - Detect problems in a timely manner• Automated Alerts for Critical Equipment & Product Alarms
Streambase Workflow
Remote Monitoring of Pumps
• Continuous data (sensors)
• Electrical parameters
• Downhole pressures and
temperatures
• Surface pressures
• ~10 values / pump / minute
• Parameters constantly
monitored
• Prevent failures (extend equipment
life)
• Enhance production (keep systems
running)
Transformer
ESP Controller
Well head sensors
P
P P
Controller
VSD
RTURTU
Remote Terminal Unit
Antenna
Spotfire steps
1. Navigate to wells w issues; focus on best time range
2. Filter to get best data
3. Mark the event for detailed analysis
4. Highlight leading indicator zone
5. Calculate features to define anomaly
6. Incorporate any required cleaning
7. Calculate control limits on reference set of wells
8. Modify limits, time zones and backtest rules/limits on data history
Develop rules for real-time monitoring
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Calculate Limits & Deploy Real-time Alerts
4. Calculate limits on reference set, backtest and deploy
Streambase steps
1. Read data
• PI
• ODS (Oracle)
2. Data Cleaning
3. Feature calculation
• Leading indicators
4. Test results against rules
and thresholds
5. Send notifications
• Spotfire automation
Action on Data in Motion – Streambase Analytics
Event Flow
Drill-down to Root Cause Analysis
Notifications and Alerts
Examples of Notifications & Alerts
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Dashboards
Mobile Devices
Value Creation
• Extend Equipment Life / Increase Production
• ESP install approximately $200,000
• 10% improvement in ESP runtime =
$100+ MM/yr on collection of 2000 pumps
• Spread organizational best practices digitally
• SME into digital form
• Standardizing operational practices
• Bad actor identification
• Data cleaning and feature development
• Central to problem
• Feeds other systems
Q & A
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Thank you!
Mike Alperin
Manufacturing Industry Consultant
+1(603)-315-4340
First to Insight, First to Action