The document discusses the significant impact of IoT technology in industrial settings, highlighting its applications in predictive maintenance, inventory management, and operational efficiency. It emphasizes the importance of data collection and analysis through various IoT components like gateways and storage units, ultimately leading to actionable insights. The document also shares case studies from companies like Tesla, Caterpillar, and Daimler, illustrating the transformative benefits of IoT in manufacturing.

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2. 40.3% of these smart IoT driven devices are
in factories, manufacturing units and similar
business
The global worth of IoT cellular devices is going to
approach
$350 million by 2025 as per the latest report by

3. PART II: IOT
ARCHITECTURE
PART III: INDUSTRIAL IOT IN
ACTION
PART I: THE BENEFITS OF INDUSTRIAL IOT

4. What Purpose Does IoT Serve in a Manufacturing Setup
 Predictive maintenance based on real-time
performance data
 Gap Identification based on machine
utilization data to improve OEE
 Remotely controlling environment
parameters
 Accurate inventory tagging for proactive
supply management
 Route planning & optimization based on
real-time data
 Cross channel visibility on inventory for
shared cost reduction
 Connected, Safe and more productive
Part 1

5. The components of an IoT Setup:
Part 2
Smart things The Gateways
IoT AnalyticsThe Storage

6. Plant floor things: Need to track
inventory, manage machines,
increase efficiency, save costs,
and even save lives
Supply chain things: Shipment
tracking, product authentication,
GPS devices, monitoring storage
conditions, locating goods
Back office things: Energy-saving
equipment, Customer’s usage data
Smart Things
01
02
03

7. The ‘Gateways’
Cloud GatewayField Gateway
 Similar to
broadband routers
 Connected to sensors
 Computational & processing
capability
 Connected to
storage unit
 Security protocols
 Data compression
& optimization

8. These sensors are
gathering data all the
time which is streamed
through the gateways to
a storage unit.
The ‘Storage’
This is Big data; you
need huge storage and
hence data lake is an
ideal fit.

9. Raw data - structured,
unstructured or semi-
structured. It stores all the
data whether you use it or not
(but you keep it for ‘if a
need arises’ like for backup
or exploration).
Data Lake
Prepossessed and structured
Data with ETL methodology.
Ready for data discovery.
Data Warehouse

10. IoT Analytics
All the layers so far lead
to this stage. In this
stage, all the information
covered so far is dwelled
into to extract key
insights to fuel business
decision making. Here, the
data is used to find
answers to questions like:
What happened?
– Descriptive Analytics
Why did it happen?
– Diagnostic Analytics
What might happen?
- Predictive Analytics
What should be done?
– Prescriptive Analytics
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02
03
04

11. Part 3
INDUSTRIAL
IOT IN ACTION

12. NUMBER 1: TESLA
In-house Manufacturing Operating
System - allows to fine-tune processes
and equipment efficiencies in a very
agile way
Robots quickening the
repetitive & strenuous
task of lifting, placing &
bolting
Autonomous vehicles are moving
inside the factory
Every piece of item is tagged
with sensors to get as much info
as possible
The factory presents a fabulous
demonstration of robotics, IoT and
exceptional IT Department.
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03
02
01

13. Asset Intelligence Platform based
on Pentaho helps them save millions
of dollars in predictive maintenance.
It helps customers’ make some golden
discoveries
In one of the examples quotes by the
company – it helped the ship operators save
$400,000 per ship by recommending -
cleaning the ship’s hull every 6 months
rather than a year“Oftentimes when people look at data, they’re
looking for the ‘grand slam’ – one thing that’s
going to save them tens or hundreds of thousands
of dollars. In reality, it’s the small
improvements that can add up to big dollar
savings across many vessels.” – said James
Stascavage, the former intelligence technology manager
NUMBER 2: CATERPILLAR
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02
03

14. Plant floor personnel equipped with
iPads that allows them to manage
machine efficiency, fuel consumption
rate to tracking shipments and
confirming reception
The network allows them to do this by
centralizing PLC data and connecting
operations to execution and logistics
systems
Maintenance and scheduling were
just a click away and everyone
was notified with all the
necessary information
NUMBER 3: DAIMLER
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02
03

15. Manufacturing giants across
the world have shifted
their focus from a pure-
play product focus to
building software
capabilities as well.
Conclusion:
They are investing
handsomely into electronics
subsystems that are
autonomous and are smart in
ways that were beyond
comprehension just a decade
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Email: rishabh.rai@polestarllp.com