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From Industrie 4.0 to Cognitive Manufacturing

Thorsten SchröerDirector and Industry LeaderWatson IoT for Manufacturing

www.localmotors.com

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Our strategy

+ +

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AnalyticsCustomerEngagement Security

Powered by CognitiveIndustry SpecializationHealthcare Finance IoT

GlobalEcosystem

Content ConversationComputeCloud

Watson Platform

Data (Public, Private, Partner)

Built cloud-based industry platform

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BlockchainEdgeWeatherPredict need and improve

decision makingAnalyze data and act on it close

to the sourceShare transactions with tamper-resistant

records, transparency and trust

IoT Devices

IBM Watson IoT Platform, Business Analytics

and Cognition

Cisco Edge& Edge Analytics

Equipping you with competitive advantage and game-changing technology

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Eco-System Extending capabilities with partners

IBM IoT for Electronics

IBM IoT for Automotive

2015 2016

IBM BluemixIoT Zone

Maximo for aviation

Maximo Asset ManagementTRIRIGA Data Manager

Maximo for Oil and Gas, Service Providers, Health/Safety/Env

Platform partners

Device and network partners

Application partners

Industry solution partners

IBM IoT for Manufacturing

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The Analyst view

Source:Forresterwave– iotsoftwareplatforms4q2016 (November2016) Source:GartnerMagicQuadrantforDataSciencePlatforms

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Artificial Intelligence - IBM Watson

10>1890 Tabulating 1960 Programmable >2010 Cognitive

A Cognitive Solution =

Analytical System

Natural Language Processing(NLP)

Machine Learning/Deep Learning

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Why Cognitivein Manufacturing and Supply Chain?

Cognitive Manufacturing – Stairway to heaven

Gather the data

Visualize the patterns

Advance to analytics

Infuse with cognitive

• Instrument your equipment/assets to collect data

• Gather already existing data

• Visualize your data in meaningful dashboards

• Start to see patterns

• Gain insights from the data

• Produce models, prediction recommendations

• Enrich with data from other sources

• Refine models with cognitive machine learning

• Utilize other cognitive functions to improve engagement

Asset needs to be connected, outfitted with sensor or data gathered

Use analytical models to predict equipment failures and provide recommendations

Use the platform to quickly build dashboards for data visualization

Use speech, video, image to diagnose complex problems

IBM Watson IoT for Manufacturing

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For analytics, utilize purpose driven advanced analytics dedicated to manufacturing metrics or generate your own models with PMQ

IBM Watson IoT for Manufacturing

Manufacturing Analytics PMQ

PlantPerformanceAnalytics

MaintenanceAnalytics

QualityAnalytics

WarrantyAnalytics

• Prebuiltindustrymodels• Rolespecificuserinterface

• Provenalgorithms• Cognitiveextension(future)

• Packagedanalyticstools

• Custombuildandexecutemodels

• BIcustomizableinterface

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IBM Prescriptive Quality on Cloud

Earlier, more definitive detection of quality problems in comparison to traditional statistical process control methods.

Reduce scrap and re-workImprove process throughput

Lower supply and material costsIncrease production yield

ibm.co/pqoncloud-trial

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DifferentiatingelementsofWatsonIoT technologyandecosystem

Partnered InnovationOpen ecosystemDevice partnershipsEmbedded securityEdge Analytics

Data IntegrationWeather dataSocial dataApplication dataPlatform of platforms

Advanced AnalyticsPredictive AnalyticsReal-time AnalyticsData MiningOptimization

Cognitive TechnologyNatural Language ProcessingMachine LearningTextual AnalyticsVideo/Image Analytics

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Cognitive Visual InspectorCognitive Equipment Advisor

Cognitive RoboticsCognitive Acoustic InspectorCognitive Energy OptimizerCognitive Quality Analyzer

Cognitive PlannerCognitive Resolution Room

Cognitive Supply Chain AdvisorCognitive Plant Advisor

Project Examples

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SmartFactoryKL Demonstrator 2015

Fast setup and change of manufacturing linesLotsize 1 with +ROI+ROI in high labour countryProvides and organizes the partner network

www.smartfactory-kl.de

I4.0 – Smart Factory

IBM helped an automotive manufacturer gain a far deeper understanding of the many factors that affect production quality

25% increase in the overall productivity of the cylinder-head production line

100% payback achieved within two years

50% reduction in the time required to ramp up the process to target levels

Industrie4.0&Cognitive FactoryatJohnDeereMannheimWorker Assistance

WatsonIoTPlatform

Cognitive Robot Demo

Machinelearning Text

Image

NaturalLanguage

WatsonCognitiveAnalytics

FoxbotwritescalligraphyHannoverMesse2016

Voicerecognition

DashboardshowsKPIinformation

Foxbot publishesjointsensordata

IBMPMQobservesoperationalstatistics,raisesmaintenancenotifications

MQTT

ConversationwithoperationsmanagerusingBluetoothheadset

1 2 3

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Cognitiverobotmaintenanceexample

WatsonIoTPlatform

PMQBluemix

Watsonconversation&voice

services

Images

imagescapturedusingImagingStationinproduction

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Defectscross- checkedagainstlibraryofpastimagesandtrainedalgorithmsforreuse

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Reusepreviouslytrainedalgorithmsandretraininproductiontohandlevariations

3a

Developnewimageanalyticsandtrainoversamplesetstohavehighaccuracy;Deploytoproductionasanewbasecase

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3b

Variation of past case?

Entirely new case?

Connects & Reasons

Real Time Monitor

Learning System

MachineLearningsystemcrawlsthroughlibraryandattemptstoimprovealgorithmaccuracyoverlargerdataset.

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PMQAnalyticsandreportingfordaily,weekly,pershiftreports

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COGNITIVE VISUAL INSPECTOR

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CognitiveQualityAdvisor

CognitiveSupplyChainDisruptionsAdvisor

CognitiveResolutionRoomsAdvisor

We teach Watson Supply Chain.

IBM Supply Chain Operations Group drives to become a cognitive business

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ibm.biz/cogmanufacture

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IBM’s commitment to the Internet of Things

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Collabratory Clients

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IBM Watson IoT Center

Final thought

“The biggest danger to a producer with a factory is a producer without a factory.”

Prof. Dr. Günther Schuh, RWTH Aachen