S U M M I TP a r i s

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Industrie 4.0 impacts de l’ IoT, de l’IA et du ML

Xavier DelacourSolutions ArchitectAmazon Web Services

@XavierDelacour

I O T 1 0 2

Xavier MichalletHead of Data

Soitec

@xmichallet

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Opérations 50/mn

Vitesse de la chaine1m/mn

Consommation électrique

2Kw/H

Produit de séries x,y,

Une erreur aujourd’hui

Bras nécessitant une maintenance dans 1000

opérations

Le produit est terminé

Problème de qualité détécté

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L’IoT stimule la croissance du marché industriel

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La 4ème revolution industrielle

Industrie 1.0

Production mécaniquealimentée par l’eau et la vapeur

Industrie 2.0

Production de masse basée sur la division des taches alimentée par de l’énergie eléctrique

Industrie 3.0

Electronique et Informatique pour pousser l’automatisationde la production

Industrie 4.0

Systèmes de production cyber physiques

18ème Siècle 20ème Siècle 1970s Aujourd’hui

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Les différentes étapes du voyage vers la fabrication numérique

ConnectivitéOpérationautonome

Capacité de prédiction

Que se passe-t-il si ?

et optimisation

Mise en place d’une culture data driven pour passer des operations en reaction à la prédiction

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Quoi et Pourquoi ca se passe ?

“réaction”

Que pourrait-Il arriver ? “simulation”

Qu’est ce qui va arriver ?“prévention”

Comment une réponseautomatique peut-elle –

être obtenue“auto-optimisation”

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Quels sont les facilitateurs techniques de l’industrie 4.0?

Robots autonomes

Simulation

Intégration verticale et horizontale

IoT industriel

CybersecuritéCloud

Fabricationadditive

RéalitéAugmentée

Analytique etBig Data

Le Cloud est une des 9 facilitateurs

Le Cloud est le facilitateur central àtoutes les disciplines et les industries

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3 zones d’application

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Que pouvez vous faire avec l’industrie 4.0

PLCMES

ERP

SCADA PLC

#1 Track and trace

Just in time delivery, condition

monitoring…

#3 Quality

management

Shape/Size/default detection

#4Predicative Failure

#5Predictive

maintenance, digital twin

#2 Monitoring

#2.1Consumable

monitoring (lubricants, filter…)

#2.2Condition

monitoring

#2.3Workers efficiency

and safety

#6Tour de contôle

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Exemple de clients industriels

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Maintenant… Comment faire ?

Exportez vos donnéesvers le cloud & créezun data lake

Tirez partie du ML et de l’IA pour

moderniser votreusine

Analysez et visualisezvos données

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© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T

Envoyez vos données silotées dans votre usine vers un data lake

Pour analyser rapidement quelle valeur peut être générée.

Pour simuler des cas d’utilisation et leur un RoI comme la maintenance prédictive et le contrôle de la qualité afin de choisir lequel implémenter.

Donner un accès centralisé aux différents clients de vos données afin de leur permettre d’innover

Pourquoi ?

DL

Operational Reporting and

Dashboarding UsersAd-hoc/Self-service Users

Data Science, ML/AI Users

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AWS a développé des outils pour faciliter ce transfert

Storage | Archival Storage | Data

Catalog

ISV Connector

Sigfox Lora Connector / API

ʥA

MQTT ʥ

A

AWS a développé des outilspour vous aider à envoyervos données dans votredata lake sans impactervos processus de production:

Connecteurs avec des parntenaires éditeursde logiciel

Adapteur pour protocols industrielsdans Greengrass

Connecteurs avec des protocols de logisitique.

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• Processez• Enrichissez• Stockeztemporairement• Requêtez

• Aggregation de connectivité• Routez les messages• Déclenchez des actions

locales

Actions

• Stockage long terme• Enrichissement et

calcul complexe

ML : Décision, prédiction, alerte

Process & Compute

User interaction

• Connectez votre objet• Activez l’intelligence locale et

le ML at the edge

Extraire Router Préparer Processer Exploiter

Cycle de vie de la donnée

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Smart Gateway

execution ML message routing

rules engine…

EdgeDevice

Secure messagingBroker, Rules engine, Shadow, Security

Device managementRegistry, OTA updates…

Fleet protection Audit, Alert

Visual design of IoT applications

Process, enrich, temporary store

Clean and enrich data

Store & query data

Data set ready for analytics

Event detection & action

aggregate connectivity, trigger local action

Site monitoring visual tool

Operational Reporting and

Dashboarding Users

Ad-hoc/Self-service Users

Data Science, ML/AI Users

LT store, heavy compute & enrich

ML: Decision, prediction, alerting

ML platform

BI /analytics/ monitoring

Actions

Process & Compute

User interaction

Fonctionnalités AWS supportant ce processus

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AWS IoT Events

Le cercle vertueux de l’IoT

AWS IoT Analytics

AWS IoT SiteWise

AWS IoT Device Management

AWS IoT Things Graph

AWS IoT Core

AWS IoT Device Defender

AWS IoT Device SDK

Amazon FreeRTOS

AWS IoT Device Tester

AWS IoT Greengrass

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Xavier MichalletHead of DataSoitec

@xmichallet

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1st IOT Device @Soitec

Soitec – Who we are

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We design and deliver innovativesubstrates & solutions to enable our customers‘products shaping everyday life

DESIGNER & MANUFACTURER OF INNOVATIVE SEMICONDUCTOR MATERIALS

4Core Technologies

SMART CUT, SMART STACKING, EPITAXY

1100

1200-mm wafer fabs (Bernin I, China (via Simgui))

300-mm wafer fabs (Bernin II, Singapore*)CAPABILITY

Employees WorldwideGLOBAL PRESENCE

23“

”

High-growth MarketsSMARTPHONES, AUTOMOTIVE, CLOUD, IoT

Largest manufacturer of engineered substratesLEADER

*Customer samples: Q3FY19Corporate presentation Soitec Proprietary Copyright @ 2019 Soitec Jan. 2019

Soitec at a glance

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Soitecfoundation

1992 Bernin I Fab

100/200-mm

19992002Bernin II

Fab300-mm

Smart Cut ™Invention

1991Singapore

Fab 300-mm

20082014

Manufacturing Partner in China -

200-mm

2015-16Reinforce core semiconductor

business & Return to profitability

2017Back to profitable

ResultsLong-term supply

agreement signed with GF

〉 Revenue: €311m in 2017-2018

〉 Stock Exchange: Euronext since 1999

〉 Employees: 1100 worldwide, 20 nationalities

〉 Patent portfolio: >3000

〉 R&D spending: ~8% of annual revenue

〉 Worldwide leader in engineered substrates

〉 Capacity:

〉 Business model: wafers, licensing

200-mm – 1.1M wafers/y. (incl. the 50k wafers/y. capacity extension planned in Bernin I during FY’19)

300-mm - 1.6M wafers/y. (incl. the 150k wafers/y. capacity extension planned in Bernin II during FY’19)

2018First 300-mm wafers

being shipped to RF-SOI/ FD-SOI

customers from Singapore

Corporate presentation Soitec Proprietary Copyright @ 2019 Soitec Jan. 2019

Soitec in the value chain

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Smart Cut TM

technology

SOI processed wafer with multiple raw dice per wafer

SOI substrates(Silicon on Insulator)

Silicon die with millions of transistors

SOI transistor

S

Base material

Buried Oxide

DGSi

IC

PCB

Starting wafers

Engineered substrates

Corporate presentation Soitec Proprietary Copyright @ 2019 Soitec Jan. 2019

Our engineered substrates are at the heart of everyday life

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Higher reliability

Longer battery lifeOutstandingPerformance

$$$$

Optimized cost

Cloud infrastructure IoT

Automotive SmartphonesSoitec’s

engineered substrates

Corporate presentation Soitec Proprietary Copyright @ 2019 Soitec Jan. 2019

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Inside our Fabs

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Centralised, consolidated IT

Fully virtualized servers (VMware since 2006)

Cloud First Strategy

All new apps must be in the cloud (Saas or hosted in Public cloud)

Legacy apps migration to be study

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The process equipment is requiring a regulation based on the Atmospheric Pressure

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Project initiated

Get the pressure from the process equipment, perform the regulation inside our manufacturing system

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Pressure information provided by the process equipment is not stable and sensors are not matched

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Option 1

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Option 1

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Option 2

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Data Collection and data storage OK

Expose and Consume Data through API

- IT Security check- Clean Room certificat

Casing / 3D Printer

Acquisition Marathon test in office and in clean room

Experiment

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Partner IT/Manufacturing

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1 Tool Only1 Sensor

⇒ PRODUCT OK !!

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Risk Analysis (Failure Mode and Effects Analysis -FMEA)

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Realability & Availability❖ Deployment of 3 sensors❖ Average of 3 sensors is computed❖ Sensor matching check

Risk around the IoT device

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New device with a screen to enable manual data collection as a workaround.

Risk around connectivity

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Move To Production

❖ Monitoring & SLA Commitment❖ Spares❖ Training for IT & Maintenance teams

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Architecture

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Vizualisation

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Monitoring

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Results 1/3 : Cost Effective

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IoT Devices

20 Eur 40 Eur

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Results 2/3 : Flexible cost

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Results 3/3 : New IT

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Fast : 1 Month Alpha / 2 Month Beta / Total 6 months project with very low workload (24 MD)Scalable : By designSupport Effective : ServerlessOpen : API based

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What’s Next ?

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S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T

Maintenant que vous avez unebonne vision de ce que vous

pouvez faire, et que vous avezaccès à vos données, quel

problème voulez-vous résoudre ?

aws.amazon.com/IoT

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Merci !

S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

Xavier DelacourSolutions ArchitectAmazon Web Services

@XavierDelacour

Xavier MichalletHead of Data

Soitec

@xmichallet

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I TS U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.