On the road to digitalization, manufacturing companies must increase their operations efficiency and accelerate their innovation rhythms. AWS provides tools and best practices for incorporating digital capabilities to achieve manufacturing business objectives without compromising security and governance and while reducing cost structures. It’s time to drive change and emerge better prepared to face current and future business environments. A strategy based on digital processes, tools, and data-driven decisions that enhances the value for customers is making a difference in the success of manufacturing companies. Learn about best practices, customer cases, and examples of companies that embarked on the digitalization journey and emerged as market leaders.

1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Improving manufacturing
operations is everything
Douglas Bellin
Global Business Development – Industry Solutions
Amazon Web Services
M F G 4 0 1

2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Improving
manufacturing operations
is everything!

3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Manufacturing
Industry Drivers
Emerging Markets
Complex, Dynamic Value Chains
Security—Cyber & Physical
Truth in Data
Demanding Customers
Converging Technologies
Ubiquitous Connectivity
Traceability & Transparency,
Brand & Reputation
Workforce
Shortage of Expertise, Knowledge Transfer
(Attrition), Tech Savvy

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Product-as-a-
Service
Digitally
“Executed”
Manufacturing
Data Is More
Than the
New Oil
Connected
Products
Manufacturing industry trends
Sustainability

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Responding to
Business Demands
24 × 7 × 365
Operations
Asset
Life Cycle
Enabling the
Workforce
Protecting and
Securing IP
Unleashing Data and
Bringing Insights
Global & Regional
Collaboration
Cost
Reduction
Manufacturing industry challenges

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If you knew the state of everything in the world
and could reason on top of the data:
What problems would you solve?

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Revenue Growth
Operational Overhead
Empowered
Sales Teams
Increased
Efficiency
Intelligent Decision-
Making
Products That Get
Better with Time
Better Relationship
with Customers
Data-Driven
Discipline

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Digital manufacturing is an important element
of the digital supply chain
Supplier Manufacturing Distribution
The signal is used to
manage downstream
activities.
In the factory, this is used to plan
the production run
Customer and consumer
provide demand signal
Supplier
Network
Raw
Materials
Inventory
Production
Phases
Shipped
Out
Finished
Good Stocks
Transit
Stocks
Last-Mile
Fulfilment
Sales

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Supply chain trends
• Smaller brands with
digital channels are
carving out their
share
• M&A for CP
companies are
increasing at a faster
rate than other
industries
• Personalization in
marketing with
brands; online
experiences for their
users, delivering
dynamic content; and
more
• New smaller brands
move faster
• Develop a
relationship with the
consumer
• Sell direct to the
consumer
• Blockchain
5. Market Share
• Keep the consumer
engaged
• Product
transparency
• Change buying
habits
• Influence of social &
mobile
• Experiment with
direct to
consumer
• Trust/security
4. Cost
Removal
• Digitization across
the value chain
• Managed services
• Automation and
robotics
• Core modernization
• Cloud
transformation
• Speed of
change
• Provide alternate
ways to use/receive
product
• Interactive
product
• Consumer
personalization
• Low costs of mass
production &
flexibility to
personalize products
3. Product
Innovation
2. Know the
Consumer
1. Protect the
Brand
• Growth in mass
customization
• Supply chain

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Source - Deloitte’s 2018 Global Chief Procurement Officers Survey
Many companies have no visibility beyond tier 1
65% have limited
to no visibility
beyond tier 1
supplier
11%
55%
1%
6%
27%
Virtually no visbility below tier 1
Limited visibility below tier 1
NA
Full Transparency
Good Transparency below tier 1

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What if you could enhance the entire supply chain?
Enable adaptable, innovative, and scalable supply chain
services that optimize business outcomes
Foundational Advanced Capabilities
Quality
Excellence
Delivery
Excellence
Cost
Excellence
new
New Product
Introduction
Risk
Management Segmentation
Acquisition
Integration Security
Supplier
Collaboration
Workforce of
the Future
Sales & Ops
Planning
Sustainability
Factory of
the Future
Connected
Supply Chain
Development

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The value of a digitized supply chain
Increased
Visibility
Proactive Issue
Resolution
Enhanced Customer
Experience
Data Anytime.
Anywhere. Any
Device.
End-to-End
Collaboration

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Connect the clouds on a platform . . .
. . . create a community (shippers, suppliers, and logistics providers)
…and the “Game” changes.
Financial
Services
In-Market
Packaging
$
Import/Export
Fulfillment
Service
Logistics
Demand
Transportation Providers and
Brokers
Packaging
Buyer
Planning
DC
Retai
l
Wholesale
Planning
Production
API
Production
Third-Party
Suppliers
Re-packers
Seller

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Key factors for
visibility technology
Implementation
▪ Connectivity with (future) partners
▪ Alignment of processes, people, IT
▪ Cooperation of partners
Functionality
▪ Understanding of functionality by all
supply chain partners
▪ Integration in current way of working
Vision
▪ Determination of scope in line
with business objectives
▪ Organizational capabilities
▪ Translation of vision
Cost and service
▪ Quantification of (indirect) benefits
▪ Cost and benefit sharing
▪ Selection of services offered
Technical architecture
▪ Integration in current architecture
▪ Flexible and cost-effective setup
Many consumer-oriented companies
have visibility technology in place

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Supply chain network
A single network platform to connect, collaborate, & execute intelligently
Network Intelligence | Control Center
Customers Distributors Manufacturers Transportation
Providers
3PLs Banks Ocean
Carriers
Suppliers
End-to-End Visibility & Control
Network Platform
Workflow Automation | Single Information Data Model | Data Quality | Multi-Party Integration | Security | Extensibility | Mobility
Single Connection | Global Onboarding and Support
Plan Source Make Move Deliver Pay

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What is preventing the industry from moving ahead?
AI/ML &
BIG DATA
expertise is
rare
Building and
scaling AI/ML &
Big Data
technology is hard
Deploying and
operating
models/solutions in
production is time-
consuming and
expensive
A lack of cost-effective,
easy-to-use,,and
scalable AI/ML & Big
Data services

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Realizing value from Big Data is challenging
What’s
holding
you back
from
using Big
Data?
Unable to link data
together
96%
of manufacturers
state data is not used
Data collected too
infrequently
Data difficult
to access
39%
of manufacturers do not
regularly collect data
66%
of manufacturers find
data is difficult to access
Without the right platform, data insights remain elusive

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AWS in Manufacturing
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About Georgia-Pacific
Georgia-Pacific, owned by Koch
Industries, is an American wood
products, pulp, and paper company
based in Atlanta, Georgia. The
organization is one of the world’s
largest manufacturers and distributors
of tissue, pulp, paper, toilet and paper
towel dispensers, packaging, and
wood and gypsum building products.
Industry: Manufacturing
Headquarters: Atlanta GA
Employees: 35K
Website: www.gp.com
We are using AWS data analysis technologies to predict . . . precisely
how fast converting lines should run to avoid tearing. By reducing
paper tears, we have increased profits by millions of dollars for one
production line.
Steve Bakalar, VP of IT & Digital Transformation
“
”
Challenges Solution Benefits
Georgia-Pacific wanted to gain new
insights from manufacturing data
collected at paper production plants,
but it relied on disparate sources to
analyze data on material quality,
moisture, temperature, and other
features.
Georgia-Pacific uses an AWS
advanced analytics solution,
featuring Amazon Kinesis and
Amazon SageMaker, to
collect and analyze data from
equipment at manufacturing
facilities across North America.
• Boosts profits by millions of dollars
• Predicts equipment failure 60–90 days
in advance
• Runs more production lines in a
predictable manner
• Ensures highest quality products
Case study: Paper & building
product manufacturing
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About SKF
Founded in 1907, SKF is the world’s
largest bearing manufacturer. The
company also manufactures seals,
lubrication and smart lubrication systems,
maintenance products, mechatronics
products, power-transmission products,
and condition-monitoring systems.
SKF has a large distributor network with
17K distributor locations spanning 130
countries.
Industry: Manufacturing
Headquarters: Sweden
Employees: 46K
Website: www.skf.com
I see a lot of speed of innovation coming from AWS, and we are
confident that this is the platform we are going forward with.
Johan Tommervik, CIO
“
”
Challenges Solution Benefits
• Move beyond selling only products
to a “rotating equipment
performance” model
• Ensure automatic lubrication of
bearings to maximize performance
• Gather data from customers to
improve product design
• Add new placement part revenue
Connected System 24 single-point
lubricator feeding data lake with
Amazon S3 to ingest and analyze
data; AWS ML to analyze products
in the field; AWS database to
manage large amounts of complex
vibration and equipment data;
AWS IoT and AWS Lambda to
speed time to market and lower
costs.
• Revenue expansion beyond ship-and-
forget to a services enhanced model
• Grow sales even if raw product
shipment numbers do not increase
• Innovate faster with lower costs
• Focus on value for customers instead of
managing IT resources
Case study: Smart bearing and
smart manufacturing
© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T

22. AWS Manufacturing reference architecture
AWS IoT
Greengrass
Edge/GW
S3
Data Lake
Kinesis
MES
Factory Machines
ML
Inference
AWS IoT
Core
Amazon SageMaker
ML
Amazon
QuickSight
Business
Intelligence
Amazon
Athena
Historian
AWS Storage
Gateway
Amazon
EMR
EBS EC2 AWS
Batch
Amazon
AppStream
Amazon EBS EC2
E&D Workloads
(PLM/HPC/CAE)
Enterprise Workloads
(SAP ERP/CRM)AWS
DMS
Amazon
RDS
Local Servers
Amazon Redshift
Data Warehouse
DataIngestion
Amazon API
Gateway
AWS IoT
SiteWise
AWS Snowball Edge
Smart Products
Amazon
DynamoDB
Lambda
AWS IoT Core
Amazon Forecast
Plant Maint. Planning
Sample Business Functions
Greengrass
Connectors
AWS IoT Analytics
Amazon
Timestream
Outposts
AWS IoT Events
Amazon
EC2
Lambda
Business Logic
S U M M I T

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Manufacturing
Data
Flywheel
YIELD
QUALITY
UPTIME
PRODUCT
Shop
Floor Data
LIFE CYCLE MGMT
IMPROVEMENTS
CUST SAT
LOYALTY
Connected
Product Data
R&D
NPS
CHANGEOVER
LOWER CHANGEOVER
New Product
Introduction

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• Factory visit/Amazon FC visit
• DI workshops
• Working Backwards workshops
• PR/FAQ
Next steps

25. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Douglas Bellin
bellin@amazon.com