The Analytics of Things - SAS · Used Data Mining technologies can additionally be used for Root...
Transcript of The Analytics of Things - SAS · Used Data Mining technologies can additionally be used for Root...
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The Analytics of ThingsCreating new value from industrial IoT data
Christoph HartmannSAS
8th of February 2016
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“At least, we have data”
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Survey Findings & ThoughtsExpectations from IoT initiatives?
Source: SAS IoT Impact Study, September 2016. N = 75. Multiple responses allowed. Q1: What does IoT or the 4th industrial revolution mean for your customers, your business, your competitors?
Fig 1: Diverse expectations Efficiency & Cost Offering & Revenue
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New Business Models
Quality of Life
Early Warnings
Efficiencies
New Value
AnalyticsIoT/BIG DATA Act
Understand ActSense
High VelocityComplex
Large
The IOT Promise
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PEOPLE
PROCESS
TECHNOLOGY
Industry 4.0Strategy & Infrastructure
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Sense – Understand – ACT
DeployETLData
Alerts / Reports / Decisioning
IoT DataIntelligent Filter /
TransformStreaming Model
Execution
Data Storage
Deploy
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People, process and technology need to work hand in hand so that IoT analytics create value.
Be ready to apply analytics into the data stream … where real-time action matters.
KEY TAKEAWAY
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Pro
cess
R&DHistory
Material dataResearch data
…
ForecastEconomical factors
Historic dataCausal factors
…
ProductionSensor data
Logistics dataScheduling data
…
QualityEquipment data
Testing dataSupplier data
…
SalesPOS data
Consumer dataChannel data
…
AftermarketConsumer data
Perceptual qualitySocial media
…Manufacturing Supply Chain
Mo
net
izat
ion
• Understand product lifecycle volume
• Offer capacity to WiP
• Advanced Process Control
• Operational Excellence
• Stabilize and ensure equipment reliability
• Real time decision e.g. price, features etc.
• Continue / discon-tinue products
• Real time decisions for next best offer
• Connect customer need with R&D
• Perceptual Quality
Dat
a
Data Lake
An
alyt
ics
Balance demand and supply
Reduce Asset downtime
Improve production efficiency
Find & Fix field issues faster
Right product, place & time
Use consumer feedback from www
External Factors, Weather, Events… Predictive Analytics & Decision Support
Value of analytics in the Manufacturing supply chain
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Manufacturing AnalyticsSAS Quality Analytic Suite
Quality Analytic Suite
Sensors Inspection/Reports ERP MES CRM / Call Center Regulatory Environmental Etc.
Co
rrective Actio
n Trackin
g
Events Stream Processing Access to PI
Monitor & Report Data Access Exploration Analysis Modeling Deployment
SAP HANA Hadoop
Perceptual Quality
Field Quality Analytics
Asset Performance Analytics
Production Quality Analytics
Data Models
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Asset Efficiency
Improved Planning
Minimize Downtime
Quality Reliability
Predictable Yield
Reduced Costs
Optimized Production
Manufacturing AnalyticsConnected factory
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SAS Production Quality Analytics Summary of Applications
With SAS, manufacturers will significantly reduce costs during the entire lifecycle of products:
• Pinpointing critical problems quickly
• Gaining process understanding.
Improved Problem Resolution
• Reducing waste and rework
• Improving products and processes
Performance Improvement
• Establishing control and reduce variation
• Determining process capability
• Shortening cycle times
Shortened time to market
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Tire manufacturerProduction Quality Analytics
Rubber Mix
Cord Manf.
Bead Manf.
Tire Building
Vulcanisation
Finish
Final Quality Inspection
Shipping to Factory
Target is to enable Engineers to drive sustainable Quality and Productivity Improvements
Visual Inspection
X-Ray
Uniformity Balance Geometry
Over-Inspection
Support Tire Production end-to-end: Mixing, Preparation, Building, Curing, Final Finish…
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Use Harmonic Vector Analysis to find whether systematic influences on quality exist which than can be identified via Root Cause Analysis
4 rules identifying better / 6 rules identifying worse than average quality
Use process optimization potential by analyzing “positive” rules
Used Data Mining technologies can additionally be used for Root Cause Analysis for Semi-Finished Products
Production Quality Analytics Production Quality Analytics
Manufacturing Analytics
By fixing 50% of the discovered issues, Virgin Yield improved by 3%.
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Data Analytics platformApproachable analytics journey
Mobile
ONE INTEGRATED SOLUTION FOR ALL ROLES
Office Integration
Cloud
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Internet of ThingsMore on Iot
sas.com/iotebook
DownloadSurvey
First movers interviews