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


“At least, we have data”


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


New Business Models

Quality of Life

Early Warnings

Efficiencies

New Value

AnalyticsIoT/BIG DATA Act

Understand ActSense

High VelocityComplex

Large

The IOT Promise


PEOPLE

PROCESS

TECHNOLOGY

Industry 4.0Strategy & Infrastructure


Sense – Understand – ACT

DeployETLData

Alerts / Reports / Decisioning

IoT DataIntelligent Filter /

TransformStreaming Model

Execution

Data Storage

Deploy


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


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


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


Asset Efficiency

Improved Planning

Minimize Downtime

Quality Reliability

Predictable Yield

Reduced Costs

Optimized Production

Manufacturing AnalyticsConnected factory


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


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…


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%.


Data Analytics platformApproachable analytics journey

Mobile

ONE INTEGRATED SOLUTION FOR ALL ROLES

Office Integration

Cloud


Internet of ThingsMore on Iot

sas.com/iotebook

DownloadSurvey

First movers interviews

sas.com


Thank you

http://www.sas.com/

the analytics of things - sas · used data mining technologies can additionally be used for root...

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