This document provides an overview of Industry 4.0 concepts including: - Examples of Industry 4.0 use cases like predictive maintenance, quality control, and remote monitoring. - The Industry 4.0 architecture including devices, edge computing, data lakes, analytics, and applications. - The technology stack required including connectivity, security, device and data management, analytics, and digital twins.

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Pankesh Patel
System and Software Engineering for
Industry 4.0

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n Industry 4.0 context
n Industry 4.0 use cases/motivation
n classification
n examples
n Industry 4.0 architecture
n Conceptual framework
n Technology stack, various vendors
n Summary
Agenda

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Industry 4.0 context
Image source: https://bit.ly/2OS0No9

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Industry 4.0 use case classification / motivation
Optimizing factory operations
• Early machine failure alerts
predictive maintenance
• Real-Time quality control
• Increase visibility of factory
operations.
• Service-oriented manufacturing
corporate app store, Service catalog
• Remote monitoring of product
• Rapid product innovation (Reduce
time to market).
• Smart products (Increase value
proposition).
Finding new business
opportunities
Improving workers' safety
and productivity
• Leveraging Industry 4.0
technologies for improved
collaboration.
• Interactive training for
workers.
• Identifying health and
safety hazards before they
occur.

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App-based smart manufacturing
ABB's drive tune
• Dashboard to see KPIs & analytics
• Worker safety
Source: https://new.abb.com/drives/mobile-tools/drivetune
Augmented SmartFactory
• On-fly asset inspection
• Write repair actions/instructions on asset
• Role-based insights
• Production, maintenance and control managers
Augmented Smart FactoryKL- source: https://bit.ly/2kQGaLi

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n Reduce downtime, extend lifetime of an asset, increase energy efficiency
n Optimized operational planning and schedule
n Potential business models
n Monitoring services, sensors
n New features and integration offerings over time (new apps, security updates,
subscription based services, cloud-based platforms)
Smart maintenance
ABB Ability smart sensor solutions - source: https://bit.ly/2Q6izB5

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Augmented reality, safety and training
Mobile, Interactive and Situation-aware
Tutoring
Industrial worker
With google glasses/HoloLens
AR technologies allow employees to
access work instructions and manuals in
field, in addition to enabling remote
guidance.
This adds their productivity and make them
safer, since accuracy and safety go hand-in-
hand.
source: http://bit.ly/2ylnEjQ

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Drone and safety
source: https://bit.ly/2RgKxeL https://bit.ly/2zKXN4N
• Health, Safety and Environment (HSE)
inspection
• "Bird eye" view
• Camera to capture images, evidences
• Grid inspection
• Camera to capture any potential issues
• Remote inspection for worker safety

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Digital platform - motivation
3 years
2 years
1 year
SHORTER DELIVERY TIMES VOLATILE MARKETS
24/7 SERVICE
SHORTER PRODUCT LIFE CYCLES
MORE INDIVIDUALIZED
CUSTOMER WISHES
Slide source: https://bit.ly/2DS40zJ

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n Rapid innovation and prototyping
n Reduce time to market
n New features and offering
n Use of cutting edge technologies
n Lower upfront IT costs
Digital platforms
https://bit.ly/2KLKbs9 https://amzn.to/2DMqgLm https://bit.ly/2xTcwZQ https://bit.ly/2QoFl7v
https://bit.ly/2NfjLAh https://www.predix.io https://bit.ly/2DMc0CB

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n Examples:
n GE predix IIoT platform for various apps and services (e.g., predictive maintenance, anomaly
detection,)
n Azure AI gallery for IIoT machine learning algorithms
n Siemens launched MindSphere to use deployment-ready IIoT apps.
Example: IIoT marketplace
https://www.predix.io/catalog/services/ https://gallery.azure.ai/

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System and Software Engineering for Industry 4.0
Slide source: https://bit.ly/2lmhmKQ

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n Aggregating raw data from different endpoints, Central data
analysis in real-time/batch mode
n Edge devices, Gateways
n Tasks
n Data communication using proprietary/standard protocols –
HTTP, MQTT, OPC UA
n Formatting using PPMP, OPC UA
n Data Storage
n Data filtering
Key software features for Industry 4.0
Reference and icon source : https://bit.ly/2lmhmKQ
Data Aggregation

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n Remote network access to factory equipment introduces safety
and privacy concerns.
n Security features like
n device authentication,
n role-based access control,
n encryption of data
n software updates need to be considered.
Key software features for Industry 4.0
Reference and icon source : https://bit.ly/2lmhmKQ
Security

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n Remote device management is required for any large-scale
implementation.
n Relying upon manual updates on the factory floor is prone to
errors, time consuming and costly.
n Device management for industrial IoT devices should include
initial setup and configuration, health check of device, software
update and deactivation.
Key software features for Industry 4.0
Reference and icon source : https://bit.ly/2lmhmKQ
Device Management

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n Industry 4.0 implementations will generate a tremendous
amount of data and events.
n For data management, software will be required to filter this
data at the edge, provide real-time analytics at the edge and
cloud, provide batch-oriented analytics and data storage.
n For event management, software will be required for event
routing, processing and handling at the edge.
Key software features for Industry 4.0
Reference and icon source : https://bit.ly/2lmhmKQ
Event management &
data analytics

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n Digital representation of physical asset
n Ease deep integration, machine learning and monitoring
n Tools to create and model a twin,
n APIs and runtimes to interact with a digital twin,
n Administration consoles to manage the lifecycle of a digital
twin collection.
Key software features for Industry 4.0
Reference and icon source : https://bit.ly/2lmhmKQ
Digital Twin
management

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Conceptual framework
Device
Edge
Data Lake
Analytic
Application
Industrial motors, pumps Production machines, PLCs Smart devices & tools
Industrial gateways Storage and edge analytics
Information from web services Holistic view of factory
Fleet of machines Supply chain
Icon source: https://thenounproject.com
AI tools and techniques, stream analytics On-premise /cloud IIoT algorithms
Dashboard Augmented reality
Chatbot
Mobile app Services
App store
Digital twins

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n OS: ‘bare metal’, embedded or real-time
operating systems for device -specific
capabilities.
n HAL –enables access to the hardware features
GPIOs, memory, etc.
n Communication Support – drivers and
protocols allowing to connect the device to a
wired or wireless protocol like Bluetooth,
MQTT, CoAP, etc.,
n Remote Management – the ability to
remotely control the device to upgrade its
firmware or to monitor its battery level.
Eclipse Industry 4.0 architecture for constrained devices
Source: https://iot.eclipse.org/white-papers/

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n OS: general purpose OS – linux, windows
n Runtime: ability to run application code, and to allow
the applications to be dynamically updated. example,
a gateway may have Java, Python, or Node.js.
n Communication & connectivity– connectivity
protocols to connect with different devices (e.g.
Bluetooth, Wi-Fi). different types of networks (e.g.
Ethernet, cellular)
n Data management & messaging: local persistence to
support network latency, offline mode, and real-time
analytics at the edge, as well as the ability to forward
data in a consistent manner to an IoT Platform.
n Remote management: remotely provision, configure,
startup/shutdown gateways
Eclipse Industry 4.0 architecture for gateways
Source: https://iot.eclipse.org/white-papers/

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n Connectivity and Message Routing –interact with
very large numbers of devices/gateways using
different protocols and data formats, but then
normalize it to allow for easy integration.
n Device Management & Registry – a central registry
to identify the devices/gateways running in an IoT
solution and the ability to provision new software
updates and manage the devices.
n Data Management and Storage – a scalable data
store to support volume & variety of data.
n Event Management, Analytics & UI – scalable event
processing capabilities, ability to consolidate and
analyze data, and to create reports, graphs, and
dashboards.
n Application Enablement – ability to create reports,
graphs, dashboards, … and API for application
integration.
Eclipse Industry 4.0 architecture for cloud platform
Source: https://iot.eclipse.org/white-papers/

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Cross-stack functionality
Source: https://iot.eclipse.org/white-papers/
n Security: authentication, encryption and authorization
n Ontologies: Interoperability, heterogeneity
n Tools and SDK: development of applications

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n Industry 4.0 – motivation
n New business models and new opportunities
n Optimizing factory operations
n Workers productivity and safety
n Industry 4.0 use cases
n Architecture, RAMI 4.0 and IIRA
n Technology
Summary

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n Technology for building Industry 4.0 applications
n Open source tools
n Cloud tools
n IIoT demonstrator
n Digital twin: a key element of Industry 4.0
n Getting started for SMEs
Next agenda…

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THANK YOU FOR YOUR ATTENTION
Questions?

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Contact…
Pankesh Patel, PhD
Senior Research Scientist,
Fraunhofer USA/ Center for Experimental Software Engineering (CESE),
College Park, Maryland, USA.
Mobile: +1 240-302-3609, Fax: 240 487 2960
Email: ppatel@fc-md.umd.edu / ppatel@cese.fraunhofer.org

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AWS Industrial Internet of Things architecture
Image source : https://aws.amazon.com/iot/solutions/industrial-iot/

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Microsoft Azure IoT architecture
Image source : https://bit.ly/2PhD2mw

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n ThyssenKrupp and Microsoft Azure
n Microsoft (Azure IoT service) to obtain several
measurements of lifts (engine temperature,
shaft alignment, speed, door functionality, etc.).
n parameters analyzed in real time using
algorithms to minimize breakdowns.
Example: platform as a service
More detail: https://bit.ly/2ylnEjQ
Slide source: https://bit.ly/2Nebw7y

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n GE platform and E.ON
n GE platform to combine sensors on
wind turbines with accurate weather
data.
n Optimize the use of turbines
maintenance and power generation.
n With E.ON (Climate and Renewables in
North America), GE is taking a
percentage of the incremental income
due to improved power generation.
Example: enhancing services
Slide source: https://bit.ly/2Nebw7y

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Example: new features offering through marketplace
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App Store
Intelligent User
Interface Apps
Motor
Management
Apps
Driver
Assistance
Apps
Green
Driving
Apps
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Slide source: https://bit.ly/2ylnEjQ

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n Microsoft and Jabil
n Quality assurance to maintain a high quality
of a product.
n Identifying errors and potential failure early in
manufacturing process – improve
productivity.
n amount of scrap and re-work goes down
n manufacturing cycle time decreases
n production goes up
n Process visibility
n Early prediction of future failures in
manufacturing pipeline and before they reach
to OEM PC manufacturer
Example: quality assurance
Slide source: https://bit.ly/2P5nT7M
Reference: https://bit.ly/2RkKEGo

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n Computer program designed to simulate
conversation with human users, accessible
from a interface (e.g., text, voice).
n Helping maintenance crews to verify factory's
condition
n Field operation – "What is the
temperature reading of a motor #1 of
floor #3?"
n Feedback from users on trial runs
n Improved customer-manufacturer
relationship
n Scalable
Example: Chatbot and smart manufacturing
Image source: https://bit.ly/2zLZ9Mo
n Features
n Easy to use
n Real-time interactions with devices
n Questions- answer structure
n Natural communication
n Continuous improvement over time
n Personalized relation with engineers (context, history)

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n Monitoring & inspection for quality assurance.
n Easy to use for worker and easy to roll-out into existing
system.
n Mobile app and web portal
n Visual inspection and confirmed by inputs and
observations into app
n Timer to track productivity
n Data sync to a web portal
n Access management
n Use cases
n Extension to other quality improvement processed
n Supplier’s quality improvement
n Monitoring worker’s productivity
n Improving efficiency of quality improvement process
App-based quality control
Smart Factory APP
10:10
Assignee: ABB
Cabinet
Process:
Liquid painting for cabinet
Incoming
Material
quality check
Mechanical
Pre-treatment
Chemical Pre-
treatment

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n Quality assurance
n Asset maintenance
n early fault detection
n New business model
n Subscription-based
services
Track & Trace
Tech Mahindra Track & Trace : https://bit.ly/2OcAloW
Slide Source: https://bit.ly/2Qe1aX6

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Deep integration
Image source: https://assets.dm.ux.sap.com/de-leonardolive/pdfs/50982_acatech_v1.pdf

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n Hands free, just with gestures you can get into additional details,
n Novel applications/opportunities
Asset inspection – advanced HCI
Reference: https://www.youtube.com/watch?v=zo11WA7nwaA , https://www.youtube.com/watch?v=Gld4fXyk14A ,
https://www.youtube.com/watch?v=XK_hW_c99Xs , https://www.youtube.com/watch?v=pLMTKN_Wn3c

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Service-oriented architecture use cases
Sensor-Service Valve-Service Pump-Service Control-Service Communication-Service
Digital Twin
hardware-independent
Device Control
hardware-dependent
Slide source: https://bit.ly/2ylnEjQ
• Self-organization
• Flexible manufacturing
• Fault tolerance

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n Ali's print machine, once this machine leaves the factory
n Get detail from Ali
n Medical device manufacturer?/ food product??/ Fish??? (IoTA example)
n Boing ? (Malasian Airleine)
n Read additional notes
Blockchain + IIoT

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Industry 4.0
Image source: http://www.bcmcom.com/solutions_application_industry40.htm