AWS Summit Milan 2018 Come costruire una soluzione Digital Twin con AWS IoT e AI-ML Speaker: Oreste Dimaggio, Partner Solutions Architect AWS

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Gianni Pelizzo
Partner & Industry 4.0 Corporate Director, Techedge
Oreste Dimaggio
Partner Solution Architect, AWS
How to build a “Digital Twin” solution
with AWS IoT and AI/ML

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Agenda
Business Perspectives
• Business needs in I4.0 projects
• High level architecture
• The importance of Machine Learning
• How to integrate AWS cloud with customer services processes
Technological Perspectives
Use Case & Call to Action!

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The convergence between IoT and ML

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Business needs in Industrial IoT
INCREASE VISIBILITY
BIG DATA ANALYSIS
FOR BUSINESS PURPOSES
IT AND INDUSTRIAL AUTOMATION
CONVERGENCE
HYPER PERSONALIZATION

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Digital Twins concept
How a ‘Digital Twin’ for
physical assets can help
achieve no unplanned
downtime?
The answer is to create a
digital twin for example in the
turbine made up of little digital
twins of all the components
that make up the unit to allow
the monitoring and simulation
of these devices in the field.
Equipment
monitoring
Data
Collection
Data
Collection
Digital Twin
Master Data
Custome
r ERP

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Use Case: Digital Twin
Ideas
Geometries
Stress simulations
Cost
Designs
The Physical World
ENGINEERING
The Digital World
AS DESIGNED
Closed Loop Engineering
AS MAINTAINED
Performance
Issues
Stability
Cost
OPERATION
?
. . .
DECOMMISSION
Production data
Quality fingerprint
. . .
PRODUCTION
AS BUILT
Ramp Up
. . .
SHIP
AS DELIVERED

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Digital Twins concept: benefits
FOR THE MANUFACTURER
• Real time monitoring and up to date
information about the asset
• Seamless integration with ERP and
Plant Maintenance
• Predictive and Condition Based
maintenance scenarios
• Leverage on 3D contents for
maintenance and training
FOR THE USERS
• Real time and accurate installed
based management
• Provide additional services on top of
manufacturing assets
• Push additional spare
parts/retrofitting on customer
equipment ID card
• Move ahead from product to service-
driven business model

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Reference Architecture
Smart
Services
Machine
learning
Business
Logics
Device
connectivity
Device
Manag.
Ingest Analyze
Store
Machine
Learning
ERP
IoT
Gateway
IoT
Integration Hub
IoT
Cloud Platform

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How to leverage on Machine Learning
Possible Applications
• Conversational
• Process Automation
• Prediction  Recommendation
• Recognition

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How to consume Machine Learning
Service
• Pre trained model on general use case
• Exposed as API or web service
• Pro: easy to use, robustness
• Cons: rigidity
Platform
• User trained model on specific data
• Exposed as API or web service after development
• Pro: flexibility
• Cons: development time

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Business Case in Industry 4.0 Scenario
Predictive and Smart Maintenance
• When machinery needs assistance?
• How can machinery perform better?
Supply Chain Optimization
• How can I minimize warehouse stock?
• When do I need to make a new order?
Customer Service
• Where is my spare part and which is the optimal warehouse?
• Is this the right spare part (field support)?
• Which is the right sequence of repair?

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AWS Service
Service
• Amazon Comprehend: user sentiment – topic text extraction
• Amazon Lex: chatbot
• Amaxon Polly: text to speech
• Rekognition: video and image recognition and analysis
• Amazon Transcribe (preview): speech to text
• Amazon Translate (preview)
Platform
• Amazon SageMaker
• Amazon Machine Learning
• AWS DeepLens: built-in ML camera sensor

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How to improve Customer Service with IoT and
ML
Technological Layer Features
Edge Computing In deepth equipment optimization
Cloud
Machine learning to predict equipment failures;
predictive maintenance
ERP Backend
Components availability; Stock status; logistic
processes
Mobile App Image recognition; global status of the equipment

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Lesson Learned
THINK BIG
IoT DRIVES THE
DIGITAL
TRANSFORMATION:
connecting things to IT
and business processes
is the key to achieve
business outcomes
START SMALL
Select a VIABLE
USE CASE WITH
FAST ROI and
develop a Proof of
Concept
SCALE FAST
Learn from early
insights and automate
as you expand,
LEVERAGING
CLOUD TO SCALE
FAST

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Showcase Architecture

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Smart Asset Maintenance Demo
Connect (IoT)
 Edge sensor
 Streaming data ingestion
Monitor
 Real time digital control room
 Maintainer mobile application
 Back office web application
Predict
 Battery RUL (Remaining Useful Life)
 Battery discharge residual mileage
Recognize
 Car plate identification
 Spare part code identification

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Demo

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Speaker Contact
Partner & Industry 4.0 Corporate Director,
Techedge
Gianni Pelizzo
Partner Solutions Architect, AWS
Oreste Dimaggio

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Thank you!