SlideShare a Scribd company logo
2
Copyright © 2020 Accenture. All rights reserved. 2
INDUSTRY X
The Triple Zero for the future
ONE
FUTURE
ZERO HARM ZERO LOSS ZERO WASTE
“Potential reduction of
22,500 injuries and
498 lives saved
through autonomous
operations, robotics
and remote operating
centers.”
World Economic Forum & Accenture, 2017
Digital Transformation Initiative: Mining &
Metals Industry
“Typical cost of
downtime averages
$180,000 per
incident. Lost profit
based on lost
production time, up
to $130,000 per
hour for every
equipment failure
incident.”
Boltstress Ultrasonics, 2018
Cost of Downtime When Machinery
Breaks Down in the Mining Industry
“Comminution
(grinding)
consumes
50% of mine site
energy and up to
4% of electrical
energy globally.”
Jeswiet & Szekeres, 2016: Science
Direct
Energy Consumption in Mining
Comminution, 23rd CIRP
Conference on Life Cycle
Engineering
Most read
INDUSTRY X
Azure IoT Reference
Architecture for Enterprise
IoT use cases
Codiax 2021
Puskás János
2021. 05. 14
Copyright © 2020 Accenture. All rights reserved. 2
INDUSTRY X
The Triple Zero for the future
ONE
FUTURE
ZERO HARM ZERO LOSS ZERO WASTE
“Potential reduction of
22,500 injuries and
498 lives saved
through autonomous
operations, robotics
and remote operating
centers.”
World Economic Forum & Accenture, 2017
Digital Transformation Initiative: Mining &
Metals Industry
“Typical cost of
downtime averages
$180,000 per
incident. Lost profit
based on lost
production time, up
to $130,000 per
hour for every
equipment failure
incident.”
Boltstress Ultrasonics, 2018
Cost of Downtime When Machinery
Breaks Down in the Mining Industry
“Comminution
(grinding)
consumes
50% of mine site
energy and up to
4% of electrical
energy globally.”
Jeswiet & Szekeres, 2016: Science
Direct
Energy Consumption in Mining
Comminution, 23rd CIRP
Conference on Life Cycle
Engineering
Copyright © 2020 Accenture. All rights reserved. 3
INDUSTRY X
Introducing the
Reference Architecture
• A reference architecture is a tricky thing; generally, technology architectures don't tend to be
one-size-fits-all. Different scenarios benefit from different approaches. And yet, we want our
solutions to implement the (collective) learnings and best practices from our previous work.
• THIS reference architecture will target a specific scenario - the enterprise IoT use case, where
mature organizations (implying diversity of use cases and interested parties, systems that have
evolved over time, and an abundance of data sources) are pursuing a collection of applications
(rather than a single purpose-built application) built around the data collected from one or more
sets of connected devices.
• We are building a reference architecture for developing an IoT Platform on Microsoft Azure, which
implies a specific set of technical capabilities that enable functionality
Copyright © 2020 Accenture. All rights reserved. 4
INDUSTRY X
Capabilities the platform
must deliver
Sources represent the large
variety of places where data is
received, sourced, and retrieved.
Processing is the area in the platform
where data is used; for example,
preparing it for reporting, analyzing it for
the creation of insights, or comparing it to
determine compliance or performance.
Consumption consists of the APIs to
enable access to data residing in
storage as well as the front-end
application(s) or component(s) for
viewing and accessing said data.
Ingestion is the method by which
data is collected, rationalized,
enriched, and made consistently
consumable.
Storage include the variety of
repositories where raw and
generated data is persisted.
Copyright © 2020 Accenture. All rights reserved. 5
INDUSTRY X
Sources
Copyright © 2020 Accenture. All rights reserved. 6
INDUSTRY X
Ingestion
Copyright © 2020 Accenture. All rights reserved. 7
INDUSTRY X
Processing - Calculations
Copyright © 2020 Accenture. All rights reserved. 8
INDUSTRY X
Processing - Analytics
Copyright © 2020 Accenture. All rights reserved. 9
INDUSTRY X
Data Storage
Copyright © 2020 Accenture. All rights reserved. 10
INDUSTRY X
Thank You

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Janos Puskas (Accenture) – Azure IoT Reference Architecture for enterprise IoT use cases

  • 1. INDUSTRY X Azure IoT Reference Architecture for Enterprise IoT use cases Codiax 2021 Puskás János 2021. 05. 14
  • 2. Copyright © 2020 Accenture. All rights reserved. 2 INDUSTRY X The Triple Zero for the future ONE FUTURE ZERO HARM ZERO LOSS ZERO WASTE “Potential reduction of 22,500 injuries and 498 lives saved through autonomous operations, robotics and remote operating centers.” World Economic Forum & Accenture, 2017 Digital Transformation Initiative: Mining & Metals Industry “Typical cost of downtime averages $180,000 per incident. Lost profit based on lost production time, up to $130,000 per hour for every equipment failure incident.” Boltstress Ultrasonics, 2018 Cost of Downtime When Machinery Breaks Down in the Mining Industry “Comminution (grinding) consumes 50% of mine site energy and up to 4% of electrical energy globally.” Jeswiet & Szekeres, 2016: Science Direct Energy Consumption in Mining Comminution, 23rd CIRP Conference on Life Cycle Engineering
  • 3. Copyright © 2020 Accenture. All rights reserved. 3 INDUSTRY X Introducing the Reference Architecture • A reference architecture is a tricky thing; generally, technology architectures don't tend to be one-size-fits-all. Different scenarios benefit from different approaches. And yet, we want our solutions to implement the (collective) learnings and best practices from our previous work. • THIS reference architecture will target a specific scenario - the enterprise IoT use case, where mature organizations (implying diversity of use cases and interested parties, systems that have evolved over time, and an abundance of data sources) are pursuing a collection of applications (rather than a single purpose-built application) built around the data collected from one or more sets of connected devices. • We are building a reference architecture for developing an IoT Platform on Microsoft Azure, which implies a specific set of technical capabilities that enable functionality
  • 4. Copyright © 2020 Accenture. All rights reserved. 4 INDUSTRY X Capabilities the platform must deliver Sources represent the large variety of places where data is received, sourced, and retrieved. Processing is the area in the platform where data is used; for example, preparing it for reporting, analyzing it for the creation of insights, or comparing it to determine compliance or performance. Consumption consists of the APIs to enable access to data residing in storage as well as the front-end application(s) or component(s) for viewing and accessing said data. Ingestion is the method by which data is collected, rationalized, enriched, and made consistently consumable. Storage include the variety of repositories where raw and generated data is persisted.
  • 5. Copyright © 2020 Accenture. All rights reserved. 5 INDUSTRY X Sources
  • 6. Copyright © 2020 Accenture. All rights reserved. 6 INDUSTRY X Ingestion
  • 7. Copyright © 2020 Accenture. All rights reserved. 7 INDUSTRY X Processing - Calculations
  • 8. Copyright © 2020 Accenture. All rights reserved. 8 INDUSTRY X Processing - Analytics
  • 9. Copyright © 2020 Accenture. All rights reserved. 9 INDUSTRY X Data Storage
  • 10. Copyright © 2020 Accenture. All rights reserved. 10 INDUSTRY X