The overwhelming majority of today’s industrial machines is not internet-ready. This is because many industrial machines lack connectivity or have proprietary or industry-specific interfaces. The value of these machines is in their access to data and metadata that can be used to unlock new business opportunities. In this session, we provide a detailed view into how to use AWS Greengrass and AWS Lambda to connect machines with industrial interfaces, such as OPC UA, Modbus, Ethernet/IP, and EuroMap63. We also walk you through a demonstration and show you how to connect to industrial machines and provide data and metadata at the edge and in the cloud.

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Industrial Internet of Things:
Connecting Existing Machines to
Tomorrow's Internet of Things
Dr. Markus Bestehorn
IoT BD
AWS
I O T 3 0 3
Jan Metzner
IoT Specialist SA
AWS
Cord Gatzka
Manager DB IoT Cloud
Deutsche Bahn

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Slide 3
Markus Bestehorn, Jan Metzner
What will you learn?
• Industry 4.0 @ Deutsche Bahn
• Use case details
• Building a digital twin
• Accessing data on industrial assets
• OPC/UA
• Modbus
• Raw TCP
• Industry 4.0 Extraction Pattern

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Slide 4
Markus Bestehorn, Jan Metzner
Data from Assets – The Foundation of Digitial Twins
Unable to link
data together
96%
of industrial
state data is not used
Data collected
too
infrequently
39%
of Manufacturers do not
regularly collect data
Data difficult
to access
66%
of industrial companies find
data is difficult to access
Why?
SCM World/Cisco “Smart Manufacturing & the Internet of Things 2015”

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Slide 5
Markus Bestehorn, Jan Metzner
Decades of this...
Source: https://xkcd.com/927/

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Slide 7
Markus Bestehorn, Jan Metzner
... resulted in this!
Operations (OT) Enterprise (IT)
IT Systems
CRM
Asset Management
ERP
Supply Chain
Finance
Maintenance
Compliance
Shopfloor
Single machine with
multiple components
following different
standards
Complete production
line likely to have
many machines with
different protocols
Challenge: Get
data from OT to IT
and make it usable!

7. DB Group boundlessly connected –
DB IoT Cloud & Digital Twins as an essential
component of intelligent digitalization
Cord Gatzka - DB Systel GmbH

8. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 9
IoT areas at Deutsche Bahn

9. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 10
IoT areas at Deutsche Bahn
Energy
Passenger traffic
Train stations
CargoMaintenance and Repair
Office Buildings
Tracks

10. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 11
How can assets communicate
with each other
across all business areas?

11. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 12
Digital Twin
Digital Twins

12. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 13
Digital Twin
Digitalization of the freight wagon
Installed sensors enable two types of
measurements
1. relating to operation
2. relating to the environment
SENSOR FEATURES:
position
temperature
humidity
load
mileage
RFID tags

13. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 14
Digital Twin
Receiving data from sensors Creation of a Digital Twin
Data is aggregated, processed and stored in the
DB IoT Cloud for a unique Digital Twin identity!
14

14. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 15
Digital Twin
Receiving data from scans
Data from external sensors is processed for
example by artificial intelligence so that the
capabilities of the Digital Twin grows
Enrichment of the Digital Twin
!
15

15. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 16
Digital Twin
Receiving data from RFID sensors
Process-based information is attached to
the Digital Twin and creates additional value
Further enrichment of the Digital Twin
!
16

16. DBIoTCloud
17Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
By interacting with the Digital Twin,
you obtain information which you
don’t have at the physical asset
Gaining new knowledge
for example
• Health Status (signs of fatigue)
• ETA (Estimated Time of Arrival)

17. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 18
Digital Twin Ecosystem
DB IoT Cloud
Communication between Twins
Train Station
Train Engine
Maintenance &
Repair
Wagon
Wagon

18. DBIoTCloud
Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018 19
Therefore we need to integrate into
a highly heterogeneous physical
world of devices and things.

19. DBIoTCloud
20Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

20. DBIoTCloud
21Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud
Copyright: Deutsche Bahn AG / Martin Busbach

21. DBIoTCloud
22Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

22. DBIoTCloud
23Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

23. DBIoTCloud
24Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

24. DBIoTCloud
25Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

25. DBIoTCloud
26Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
RFID Asset Identification
Modbus Connectivity
DB IoT Cloud

26. DBIoTCloud
27Deutsche Bahn - DB Systel GmbH | Cord Gatzka | 2018
Modbus
Protocol
Converter
RFID
Controller
RFID
Reader
Edge Device DB IoT Cloud
RFID
Tag
RFID Asset Identification
Modbus Connectivity

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Slide 29
Markus Bestehorn, Jan Metzner
Operations (OT)
Solving Industrial Data Extraction
Factory Machines
Enterprise (IT)
IT Systems
CRM
Asset Management
ERP
Supply Chain
Finance
Maintenance
Compliance
Protocol
conversion
Modbus
conversion
OPC UA
conversion
Gateway
Custom / Proprietary
Protocol
MQTT

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Slide 31
Markus Bestehorn, Jan Metzner
Operations (OT)
Demo: OPC UA, Modbus and more
24V I/O
Fieldbus
OPC UA
conversion
Fieldbus

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Slide 33
Markus Bestehorn, Jan Metzner
Operations (OT)
Demo: State and Imaging Data
24V I/O
Fieldbus
24V I/O
TCP
Modbus
conversion
Shadow
Shadow
OPC UA
conversion
Recognition Data
(QR Code/Image)
Gateway
Fieldbus

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Slide 34
Markus Bestehorn, Jan Metzner
Operations (OT)
Demo: Digital Representation in the Cloud
24V I/O
Fieldbus
TCP
Modbus
conversion
Shadow
Digital
Representation
Shadow
OPC UA
conversion
Recognition Data
(QR Code/Image)
State
Information
Life/High
Frequent
Information
Near-Life
/Historic
Information
24V I/O
Fieldbus

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Slide 35
Markus Bestehorn, Jan Metzner
IIoT Design Pattern – ETL @ Edge
Load
• Buffering
• Compression
• Gateway  Cloud
Transform
• Formats (CVS  JSON)
• Filtering
• Data translation
Extract
• Protocol conversion
• Data rate
• Polling vs Events
Operations (OT)
Gateway
Extract Transform Load

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Slide 36
Markus Bestehorn, Jan Metzner
Key Takeaways & Call to Action
AWS Lambda on AWS Greengrass
makes industrial data extraction
simple
Jump into Industry 4.0
• Start building
• Get help – AWS prototyping teams!
Industry 1.0 Industry 2.0 Industry 3.0 Industry 4.0
Approach applicable to various
industrial protocols

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Slide 37
Markus Bestehorn, Jan Metzner
Breakout repeats
Monday, November 26th 2018
Industrial IoT: Connecting Existing Machines to Tomorrow's IoT, ft. Deutsche Bahn
11:30 – 12:30 | Aria West, Level 3, Juniper 1
Wednesday, November 28th 2018
Industrial IoT: Connecting Existing Machines to Tomorrow's IoT, ft. Deutsche Bahn
18:15 – 19:15 | Aria East, Level 1, Joshua 8

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Slide 38
Markus Bestehorn, Jan Metzner
Related breakouts
Monday, Tuesday, November 27th
Building IoT Applications for a Smart Home, ft. Vestel
Location & 16:00-17:00 | MGM, Level 1, Grand Ballroom 111
Tuesday, November 27th
Serverless Industry 4.0 & AI: Drive Business Insights from Machine Data
14:30-16:45 | Aria East, Plaza Level, Orovada 8
Tuesday, November 27th
Making the connection and extracting value
11:30-12:30 | Aria East, Level 2, Mariposa 3

38. Thank you!
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