This document discusses smart manufacturing and Industry 4.0. It begins with an agenda and overview of making factories smarter. A case study is presented on Reply's solution for Sabelt, an automotive safety belt manufacturer. The solution involves collecting data from Sabelt's operations using IoT and analyzing it in AWS to improve productivity, flexibility and quality. Next steps discussed include expanding the solution with machine learning for predictive maintenance and production, and a B2B ecommerce application.

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Anna Buttaboni
Senior Solution Architect, Reply
Luigi Cicchese
Partner, Reply
Industrie 4.0: How to make the
Manufacturing Smart with AWS
IoT and Big Data services
Michele Alessandrini
Senior Solution Architect, AWS

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Agenda
Industrie 4.0: The Same Your Factory, Just Smarter
A Real Case Study: Smart manufacturing
Introducing Sabelt
Reply solution and Next steps

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Industrie 4.0:
The Same Your Factory, Just Smarter

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FACTORY
SMART
FACTORY
CUSTOMIZED
PRODUCTS
MASS
PRODUCTS
PRODUCTS
FORECAST
ADAPTIVE
PLANNING
HUMAN
DRIVEN
MACHINE
DRIVEN

5. MACHINE
LEARNING
SMART
PRODUCTION
SMART
WORKINGSMART
LOGISTICS
DIGITAL
ECOSYSTEM
IOT
CLOUD
COMPUTING
CLOUD
COMPUTING
BIG
DATA
OBJECTS
TAGGING
WEARABLES
CLOUD
COMPUTING
MOBILE
FIRST
OBJECTS
TAGGING
PROFICIENCY
AREAS

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REGULATORY CHALLENGES ECONOMIC CHALLENGES
TECHNOLOGICAL CHALLENGES SOCIAL CHALLENGES
 Lack of standardization
 Legacy-installed base
 Significant upfront investments
 Cybersecurity
 Data integration
 Internal system barriers
 Lack of skilled workers
 Liability of current technologies
 Social/political concerns
CHALLENGES TO INDUSTRIE 4.0 ADOPTION

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o ENHANCING PRODUCT INNOVATION
PROCESS
o CREATING NEW BUSINESS OPPORTUNITIES
o REDUCING DOWNTIME
o REDUCING ASSETS LIFECYCLE
o MAXIMIZING ASSET UTILIZATION
o IMPROVING OPERATIONAL EFFICIENCY
o IMPROVING PRODUCTIVITY
o ENHANCING WORKER SAFETY
o ENHANCING PRODUCT INNOVATION
PROCESS
DRIVERS TO INDUSTRIE 4.0 ADOPTION

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A Real Case Study:
Smart Manufacturing

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INDUSTRIE 4.0: CUSTOMER NEEDS
• SPEED
Low time to market: from project to prototype with advanced technologies
• FLEXIBILITY
High product customization with cost comparable to mass production
• QUALITY
Improve quality of the product with more frequent and effective quality
controls
• PRODUCTIVITY
Low production costs with real time production monitoring

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WMS ERP
AWS
Cloud
On premise
Edge
Field
Data Ingestion
Data Lake
Data Analysis
REPLY SOLUTION: FUNCTIONAL OVERVIEW

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REPLY SOLUTION: ARCHITECTURE
o Architecture
o Extensible - modularly add components to the backend
(e.g., services for voice and image recognition, AI, ...)
o Dashboard
o Alarms notification
o Real time data analysis
for warehouse and
orders management
o Field Data Analysis:
o Production volume
o Warehouse occupation: correlated with
WMS data
o Orders fulfillment: correlated with ERP data
o Production line health: correlated with
historical production data
o AGV tracking

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REPLY SOLUTION: NEXT STEPS
oML analysis for:
o Predictive maintenance
on production line
o Predictive production
o AGV paths
optimization
o Application next steps:
o B2B ecommerce

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Ing. Giulio Graziano
Sabelt S.p.a
SABELT 4.0 – Episode 2

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BUSINESS UNITS
MORE THAN 40.000 SEATS
PRODUCES EVERY YEAR
PROVIDER OF RETAINING SYSTEMS
FOR ALL ISS RESUPPLY MISSIONS
PROVIDER OF SAFETY BELTS FOR 8
OUT OF 10 FORMULA 1 TEAMS

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OEM
ALPINE FERRARI JAGUAR
VIPER ALFA ROMEO 4C MC LAREN
ABARTH
MITO

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VISION OF SABELT 4.0
CUSTOMERS
ERP
Warehous
e
Automati
on
Productio
n Area
Product
Engineering
Prototyping
MATERIALS
INFORMATION

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LESSONS LEARNED
THINK AND
PRIORITIZE
THINK BIG SHARE
KNOWLEDGE
STEP BY STEP FOCUS THE TRAINING

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THANKS