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Why customers run SAP on AWS
for Industry 4.0

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Industry 4.0

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The 4th Industrial Revolution
Industry 1.0
Mechanical production
powered by water and
steam
Industry 2.0
Mass production based
on the division of labor
and powered by
electrical energy
Industry 3.0
Electronics and IT for a
further automation of
production
Industry 4.0
Cyber physical
production systems
18th Century 20th Century 1970s Today

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What are the technical enablers of Industry 4.0?
Autonomous
Robots
Simulation
Vertical & Horizontal
Integration
Industrial Internet of
Things
CybersecurityCloud
Additive
Manufacturing
Augmented
Reality
Big Data
& Analytics
Cloud is one of the
9 standalone enablers
Cloud is the central
innovation enabler across all
disciplines and industries

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What sets AWS apart?
Security Fine-grained control
Service Breadth & Depth
Pace of Innovation
100+ services to support any cloud workload; rapid customer driven
releases
Experience: 1M+ customers Building and managing cloud since 2006
Global Footprint 18 regions, 55 availability zones, 114 edge locations
Artificial Intelligence Fully integrated in AWS
Ecosystem Thousands of partners; 4,200+ Marketplace products
Enterprise Leader
AWS is positioned highest in execution and furthest in vision within the
Leaders Quadrant

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The true value of digital
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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Two Predominant Outcomes
Smart products and services are brought to market with smart factories
Smart Factories
Smart Products and
Services
Connectivity and Internet Technology
Smart Sensors and Actuators
Cloud Processing and Storage
Big Data Analytics and Artificial Intelligence

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Smart Factories built on Cloud Computing
Smart factories – simple and adaptive
Global Data and
Integration Platform
Internal Focus
applications
Processes
Employees
Equipment
• Highly reliable
• Highly available
• Increased agility
• Increased innovation
• Lower total cost
• Knowledge capture

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Smart products built on Cloud Computing
Smart products and services – individualized and quickly brought to market
Global Data and
Integration Platform
External Focus
applications
Processes
Employees
Equipment
applications
Rich and adaptive
customer experience
Innovate and quickly
bring to market
Smart, connected
and updated

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Manufacturers want to use Big Data to improve insight
Manufacturers plan to use Big Data to build:
• Single view of operations
• Insight from hard to reach stranded data – OT
• Insight from new data sources – mobile / social / IoT
• Real-time inventory management
• Predictive Maintenance and a move towards Prescriptive Maintenance
• Product improvement recommendation engines
• Operational performance insights
• Dynamic production engines
• and more… Industry 1.0 Industry 2.0 Industry 3.0 Industrie 4.0

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Problem
Valmet produces complex equipment with
multiple dependent processes running in parallel.
Valmet customers need visibility into the state of
these processes to control quality and avoid
downtime.
Solution
Valmet is building a new digital twin capability to
allow paper mill operators to view equipment
and process data during production runs. AWS
IoT Analytics is at the core of this solution
training ML models for paper quality forecasting
and scheduling metrics generation for digital
twin view-generation.
Impact
AWS IoT Analytics allows Valmet to combine
historical models of equipment performance
with live data from current operations to glean
insights that help them learn how to make their
paper better and stronger.

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Realizing customer and operational insight from your data
requires a robust Industrial Platform
Customer and
Operational Data
Customer and
Operational Insights
ConsumeAnalyzeStoreIngest

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Characteristics of a Data Lake
Future
Proof
Flexible
Access
Dive in
Anywhere
Collect
Anything

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Manufacturing innovation
Smart Factory
Closed loop automation
and intelligence
Here-and-now
Realtime remote
monitoring
Predictions
Machine learning &
Edge AI
Event based digital
monitoring for optimized
operations, stock handling,
safety monitoring and
reducing MTBR
Automated alerting
connected to ERP, Asset
and operational services to
create fully automated,
data driven operations
Data logging and
analytics platform;
integrated data types to
reduce MTBF and
optimize productivity

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Find real value in raw data streams

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Sample customers

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Problem
Wärtsilä needed to accurately predict, when the
marine engines they manufactured needed to get
serviced. Understanding and predicting the
service schedule is vital for Wärtsilä to increase
their service and parts revenue.
Solution
Accenture worked with AWS account SAs, AoD
SAs, and Salesforce SAs to architect an IoT
solution using Salesforce and AWS IoT Core to
collect data and build predictive models. The
solution developed is scalable and extensible
beyond just this use case, as Wärtsilä has 14,000
ships with 35,000 engines installed. There are
great possibilities for sensor driven IoT use cases.
Impact
The entire solution should result in an increase
in parts/service sales for Wärtsilä and higher
customer retention.

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Problem
As Konecranes specializes in the
manufacturing and service of cranes globally,
they discovered that when they needed to
make updates to their machinery it meant
downtime and local presence onsite.
Solution
Using Greengrass has enabled them to
deploy updates using cloud models that
continually get smarter over time as they
sync with the local environments.
Impact
This allows them to simplify their current
crane architecture and make it possible
to update calculations to the cranes in a
secure way even after the installation
has taken place.

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AWS and SAP

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Why do customers run SAP on AWS?
New LoB solution Tech refresh Exit data center
Analytics side-car Business continuity International expansion
Corporate restructure Innovation lab SAP S/4 HANA

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Common Triggers for SAP Transformation
Technology Drivers
• Aged Infrastructure or Data Centers impacting performance or reliability
• Data Center or Infrastructure capacity Issues
• Upgrading or moving to a new SAP software release
• Implementing new SAP modules
• Consolidating multiple SAP instances
Business Drivers
• Business process change driven by digital transformation or strategic initiatives
• Entry into new geographic markets or new lines of business
• Merger, Acquisition and/or Divestiture events
• IT or Business Process Outsourcing and/or new major go-to-market partnerships
• Business frustration with cycle time required to implement changes or receive actionable business insight

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Why is SAP on AWS the right answer?
Accelerating the Digital Transformation journey
Flexibility Technical Excellence Economics
• Rapid Provision:
Create new HANA systems
through AWS Quick Start in <1 hr
• Grow (or shrink) as you go:
Scale-Up or Out your
configuration in <1 hour
• Expertise:
SAP, AWS and joint partner
ecosystem
• Secure:
Innovate while maintaining a
secure environment
• Simplify:
Clone and upgrade systems
with ease
• Consume:
Provision new SAP innovations
through SAP’s Cloud Appliance
Library (CAL)
• Low Cost of Entry:
2TB for 40 hours <$700*
• Flexible pricing:
Achieve up to 72% discount on
X1 for 3 year commitments

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Customer Benefits
• TCO Reduced by 70% and
• SAP Administration workload reduced by 300%
• Performance improvement of 40%
• Sped deployment times, cutting provisioning time from months to
weeks
• Increased business agility – decreased deployment time by 30%

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Customer Benefits
• Increase agility and reduce costs while modernizing infrastructure
• Global user base required better SLAs for system up-time, disaster
recover and telecommunications
• 52% decrease in IT costs with greater speed to market and increased agility
• 50-60% reduction in cost and 80-90% reduction in TCO
• Migrated in 48 hours

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Customer Benefits
• Cost savings of over 50%
• All data to users with a simplified experience
• 4TB migrated in under 10 hours
• Full migration in under 3 weeks
• Delivery times have been reduced from weeks to minutes and from
hours to seconds
• Finance, sales, and operations teams have access to full data sets and
the ability to analyze on demand

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SAP Use Cases

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SAP on AWS Use Cases
▪ Migrate from on-premises or 3rd party infrastructure to AWS…
▪ Test / Training / Sandbox systems
▪ DEV and QAS landscapes only
▪ Complete SAP environment
▪ SAP legacy systems
▪ New implementation…
▪ New SAP customer – New SAP Implementation on AWS
▪ Existing SAP customer – New SAP solution on AWS
▪ DR for on-premises SAP production environment
▪ SAP Document and Data Archiving to AWS Cloud Storage
▪ Temporary infrastructure for…
▪ SAP upgrades and OS/DB migrations
▪ POCs

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Predictive Maintenance

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Machine Analytics is the #1 customer initiative to achieve Digital
Manufacturing
Increasing Adoption of New Technologies Millions of Unconnected Machines to Connect
0% 10% 20% 30% 40% 50% 60% 70% 80%
Big data analytics (eg.
Maintenance, quality)
Connectivity technologies
(connecting plant floor…)
Factory automation
Mobile devices (eg. Ruggedized
handheld devices…)
Modern plant-floor IT (eg. MES,
PLM, etc.)
Cloud computing
Wireless plant-floor networks (eg.
WiFI, M2M…)
RFID / Location technologies
Plant-floor video (process
monitoring, real-time…)
Source: SCM World survey of 483 Industrial customers
70%
60%
50%
40%
30%
20%
10%
0%

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What does a manufacturing customer do today for Machine Health?
• Time & resources invested by customer to
develop in house solution for machine health
• Multiple software tools from different vendors
• Data is collected but no one looks at it
actively, so it becomes useless
• No centralized view of all assets and alarms
Manufacturing
Customer
IMAT
OEE
Vimana
Hartzell
specific
macros
Reinshaw
probes and
software

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With Predictive Maintenance
• Single click to check machine health
• Accountability: operators can start their shift by running a
calibration check
• No custom macros needed
• Integrate with existing OEE dashboards
• Proactive alarms associated with each machine
• Unique machine signatures determined by algorithms

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Connected Machine Key Advantages
Machine Visibility
Customer Challenges:
• No machine green light
activity
• No operator accountability
Customer Outcomes:
• OEE improvement
• Reduced downtime
Converged Platform
Customer Challenges:
• Operation silos with
dedicated hardware
• Legacy system and
Windows patch
Customer Outcomes:
• Integrate with IT service
model
• Security from within
Machine Analytics
Customer Challenges:
• Unexpected down time
• High defect rate
• Manual maintenance
schedule
Customer Outcomes:
• Real-time anomaly
detections and reduce defect
• Predictive maintenance
Machine Visibility
Customer Challenges:
• Unauthorized access to
device
• Complex remote access
and troubleshooting
Customer Outcomes:
• Platform utility, not
standalone separate solution
• Security

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Next Steps

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SAP on AWS Customer Experience
Scope Prove Move

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SAP Rapid Migration Test Program
Eliminate the unknowns of migration to SAP HANA with the
SAP Rapid Migration Test Program
SAP and AWS deliver a quick, low-cost way for you to understand the actual time, cost,
and business impact of migrating your SAP applications to run on SAP HANA with the SAP
Rapid Migration Test Program and AWS FAST.
Standard,
supported
and proven
tools
Results
as fast as
48 hours
Costs as
little as
$1,000

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Conclusion – SAP on AWS
Improve security
posture
Scale to meet
actual demand
Build once,
deploy globally
Improve operational
reliability
Deploy in minutes
vs. week/months
Deploy complex
topologies with ease
Customers can focus
on core competency
16-22% less TCO
than on prem

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Thank You!