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Wired to Win
Wireless, Cloud, Networking Technologies
for Elevating Indian Manufacturing

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Whitepaper 2024-25
 What to expect inside

Executive Summary
03
Indian Manufacturing sees Unprecedented Opportunities 04
Technology is driving Performance through Learning Methods
05
Implications of Trends on Manufacturing Connectivity 06
Choosing the Right Tech Stack 07
Converting Business Ambition to Technology Choice 10
1. Instrumentation Digitalization Choice 10
2. Connectivity Technology Choice 11
3. Application Cloud Collaboration Technology Choice 12
4. Networking Technology Choice
13

Getting Started to set the Right Technology 15

Why Airtel Business for network Technologies Choices 16
Bibliography 17
©Zamun 2024 | www.zamun.com Whitepaper 2024-25 02
Executive Summary

Network tech helps capture

great manufacturing opportunities
.. and there’s a stepwise way to choose it wisely

The world of manufacturing is going through some advancement in technology maturity is seen,
major transformations, across business and moving beyond pre-programmed functionality,
technology drivers which are creating fundamentally towards intelligent machines capable of learning,
new opportunities. The pandemic was a major adapting, and operating within complex
game changer. Initially, there was a manufacturing environments35. There is also the need to develop
slowdown, then accelerated focus on digital talent, with skills in cloud and AI technologies,
connectivity. There is also a shift in global sourcing enable data capture and governance and set an
strategies with many countries going for the “Make approach for better future readiness.
here” incentive programs, data hosting in-country
and non-dependence on China. We propose a stepwise TASK-ICAN approach to
ensure the right return on technology investment.
Consequently, India has set an ambition of The need is to first define the TASK at hand – by
increasing the manufacturing sector’s contribution tracking technology implications, articulating
to 25% of GDP1, up from 13% today2. This is ambition, setting stack specification and keeping
supported by ‘Make in India’, that has led to nearly KPIs well-defined. These metrics drive the right
$0.45 trillion in exports³ at 6% growth during FY23. choice of ICAN: digital instrumentation, connectivity,
Now large and small manufacturing setups will need collaborative applications and networking
a networked environment to deliver this growth. A technologies.
careful choice of technology approach should
identify relevant trends, set KPIs and work out a
suitable networking technology stack. With the
advent of autonomous systems, a substantial

Define Technology Approach Choose Manufacturing

Networking Technology

T A S K I Instrumentation
Digitalization

Track
C
Set Stack
Connectivity
Technology and
Technology
Trends Specifications
Articulate
Ambition

A
Understand Keeps KPIs Application
Implications Well-Defined Cloud
on Manufacturing Collaboration

N Networking
Technology

Figure 1: Manufacturing Networking Technologies

©Zamun 2024 | www.zamun.com Whitepaper 2024-25 03

Industry Trends

Indian Manufacturing sees

Unprecedented Opportunities
and some surmountable challenges

The Indian Manufacturing sector is experiencing 4. Manufacturers are looking for business
five key trends, driven by global shifts, historical metrics, not just technical specifications to
constraints and growth ambitions. The focus on deliver Return on Investment .
global trade, specialization, connectivity, and a. Tech companies are delivering
distributed supply chain has led to interesting business metrics that impact business.
implications: For e.g. Slack offers KPIs of increasing
awareness, customer growth, and sales
1. Geopolitical concerns about supply chain pipeline⁹ .
“The PLI scheme is access and local manufacturing jobs. Growth b. Manufacturers are asking tech
not to make the ambition and opportunity for the Indian has providers to commit outcome SLAs like
beneficiaries been shaping policies. production cost per unit, reduced cycle
dependent on a. ‘Make here’ policies such as ‘Make in India’ time, and not just tech SLAs like link
government services – with incentive schemes, like India’s PLI⁴,
but can be utilised as
uptime. A two-wheeler manufacturer
for land availability, tax holiday, and export that produces a vehicle every 20
a boost in the promotion. seconds, has asked for an SLA for
manufacturing
b. China +1 policy for supply chain productivity enhancement to 15 seconds
sector, an initial
non-reliance. China’s Zero-Covid Policy per vehicle.
support for the had shot up lead times, forcing the US and
long journey ahead.
Ultimately competition Europe to look at India as an alternate 5. Lack of data and technical talent leads to
will prevail,” source. India's advantage is its young slow adoption of high-end AI use cases.
population⁵, albeit with low skills⁶. According to a McKinsey report, India could
face a potential skill gap of specific technical
2. Environmental and sustainability concerns. skills of 85-90 million workers by the year
Piyush Goyal
Commerce and Industry As the world focuses on SDGs, Sustainable 2030. Increasingly, 1/3rd of manufacturers
Minister, India Development Goals, the manufacturing sector are investing heavily and actively using AI10.
is held responsible for lifecycle emission control
and living conditions. Given these trends, Indian Manufacturing sector
a. Moving factories away from urban centres. leaders need to invest in technology and talent to
Industrial relocation policies, such as the overcome environmental concern, speed up
1999 Supreme Court mandate to shutdown development and deliver on business RoI.
Delhi factories, aim to combat pollution.
b. Measuring and eliminating emissions
and carbon credits. Migration to -26.0%
decarbonization, renewables, and new
digital ways of working accelerate the
net-zero transition. To achieve the Paris
56
60 -30.0%
Agreement’s 1.5°C limit for global
temperature increase, emissions need to
drop by 45%⁷.
50
42
40
3. Faster customer needs evolution. 29
In a hyper-connected world disruptive tech is 30
released daily and digital distribution has
accustomed people to updates. 20
a. Shorter product lifecycles – faster
obsolescence, disposal, reusability and 10
recycle concerns create time pressures to
deprecate products with less opportunity 0 2016 2021 2026**
to learn and amortize costs.
b. Shorter new product development cycles Figure 2: Time to market in weeks
– faster prototyping and testing have
reduced time to market to 42 weeks in
2021, going to 29 weeks in 2026⁸. (Figure 2)

©Zamun 2024 | www.zamun.com Whitepaper 2024-25 04

Technology Trends

Technology is driving Performance

through Learning Methods
.. and by creating faster decision and better controls

- Manufacturing has always led in the usage of - vehicles) and AMRs (autonomous mobile robots)
“A very tangible technologies such as SCADA. Today, technology is are becoming prevalent in warehouses to
benefit in engineering driving efficiency, productivity and sustainability remotely handle tasks such as picking, packing,
and design is reduced across OT and IT. As 93% of the industrial and transporting goods, without infrastructure
cycle time for design
manufacturing industry has started using AI11, it has modifications, leading to improved accuracy with
iterations,”
become the top adopter of AI. less staff. India’s robot density is 148 per 10,000
“AI speeds up the employees and can grow to China’s level of 77215.
process by homing in - Smart, connected products require a new
on the specific “technology stack” made up of new product - New Analytics and Simulation16- 29% of global
parameters that you hardware, embedded intelligence, connectivity, manufacturing companies have implemented
need to focus on. cloud software, security tools, a gateway, and digital twins driving future market growth at
We’ve had design integration with enterprise systems12. 42.6% from US$9 billion in 2022 to US$137 billion
cycles being cut from - Manufacturing efficiency requires new production by 203017.
12 months to less than methods and R&D with live inventory view and
six months. That’s an
real-life prototyping. These are supported by - New Judgement and Decisioning – AI’s first use
easily quantifiable
benefit.”
enhancements in the Manufacturing Performance cases18 are in Predictive Maintenance, R&D19, then
Layers and the Learning and decision layers. (Figure 2) automated factory control20. An early adopter is
the semiconductor industry, where about 1,000
Gunaranjan Manufacturing Performance Layers specialists are needed to manufacture a GPU.
Now Nvidia has developed an AI system,
Chaudhry co-designed by chip design companies Synopsys
Director, Data Science, - New Materials. The industries of Energy
and Cadence, that aims to accelerate production
SymphonyAI generation and storage, Aerospace & Defence,
by speeding up the engineers’ work21.
Medical and Biotechnology, and Automotive and
Transportation are leading the use of new-age and
Collectively this group of tech trends are known as
lightweight materials, such as composites,
Factory 4.0 – enabling connectivity, visibility and
ceramics, advanced aluminium alloys, and
automated decisioning across the supply chain.
performance alloys13
Industry 4.0 has led to increased integration of IT
and OT. While this improves efficiency, it also
- New Manufacturing Technologies. 3D printing
creates new cybersecurity challenges for
helps visualize, develop and produce fast. India’s
manufacturers33 as Learning Layers expose
3D printing market revenue will grow at 20.3%
Performance Layers to open networks. Many
CAGR from $111 million in 2022 to $705 million by
manufacturing systems still rely on legacy OT
2030. The U.S. market was estimated at $4.46
infrastructure, which may lack robust security
billion in 2022 and expected to grow at 15.7%14.
features. Organizations must address these
challenges to build a resilient OT security program.34
Learning and Decision Layers
The Next evolution of the Manufacturing Technolo-
- New Digitized Sensing Technologies and Precise gy is Industry 5.0 – a fully integrated low latency
Controls can digitally measure temperature, human-to-machine collaboration, enabled by the
pressure, location, etc. AGVs (automated guided current advances in automation and Generative AI.

Manufacturing Technologies Layers Industry 4.0 application

Machine Predictive
Decisioning (AI/ML) Learning Maintenance
Learning and Quantum
Big Data Augmented Computing
Decision Analytics (Simulation) Analytics Reality
Layers
IoT Smart Sensors
Controls Sensing (IoT)
Advanced Robotics Location Tracking

Manufacturing facilities
3D
Manufacturing Printing Cloud
Digital
Performance Computing
Twin
Layers Materials Manufacturing Technologies Efficient
materials

Figure 3: Manufacturing Technologies and Industry 4.0

© Zamun 2024 05 Whitepaper 2024-25
Implications of Trends on
Manufacturing Connectivity
Beyond driving India’s growth ambitions of 25% development, supply chain and customer
“Everyone in these trends require an environmentally and interactions. A "digital twin" can be created to
manufacturing humanly responsible approach, while handling visualize what is happening.
is excited about talent and skill shortage22. Connectivity and
AI, but relatively few cloud solutions, come to the rescue for 3. Predictable: Pre-fitted models are used to
are using AI at scale to manufacturing companies if they strategically calculate future event likelihood to predict machine
transform the way they choose a desired level of maturity to avoid maintenance, quality issues, demand trend
work.” reckless expenses and management analysis, supply chain roadblocks, and operational
complexity. downtime.
Philippe
Rambach There are 4 levels of maturity, with increasing 4. Autonomous: Data is used to automatically train AI
Chief AI officer of value beyond a Standalone facility, that has models, enhance decisioning logic and help in
Schneider Electric disconnected devices. Expectedly, they require maintenance, product design and development,
higher hardware, software and talent optimization and many other advanced use cases.
investments. The key is to identify the level of (Figure 5)
maturity that gives the highest ROI. These level
of maturity are (Figure 4) As Manufacturers go up the technology maturity
curve, they deliver products and services more
1. Connected: Business processes and OT efficiently, and fare better than their competition in
(Operating Technologies) are reflected in IT the market.
systems and data processing systems for
smoother manufacturing and logistics Increasing technology maturity fundamentally
operations across: relies on connecting more layers of devices with
a. All machinery and plants for process programming. The following diagram shows how
implementation technology maturity increases by a high level of
b. The vendor and distributor ecosystem connectivity and starts to deliver higher benefits.
for collaboration
MATURITY BENEFITS
2. Visible: The visibility of metrics from sensor

Faster Decision
and controls data helps real-time awareness,

Logic Update
Data driven
Awareness
Implement
running controls remotely, improving product

Intelligent
Support
Process

Decisioning (AI/ML) Autonomous

Learning and
Decision Analytics (Simulation) Predictable
Layers
Controls Sensing (IoT) Visible

Manufacturing facilities
Manufacturing
Performance
Connected
Layers Materials Manufacturing Technologies

Standalone
Figure 4: The 5 Stages of Technology Maturity

Respondents rated top use-cases currently in pilot and production stage

Pilot Production
Knowledge management Product design
23% 29%
Quality control Content creation
23% 28%
Maintenance of production assets Conversational AI with chatbots
22% 28%
Automation of production documentation Process optimazation
22% 25%
Product lifecycle management Machine data analysis
18% 22%
Materials research Quality control
18% 22%

Source: MIT Technology Review Insights Survey, 2024 Figure 5: Top AI use-cases in pilot and production

06 Whitepaper 2024-25 © Zamun 2024

Choosing the Right Tech Stack
Given the desired technology maturity companies must
elegantly make a choice of the technology stack they
will deploy in a stepwise process. The TASK-ICAN
approach starts with having a good understanding of
your environment and ambitions. It starts with making
sense of trends from your company’s perspective.

T
rack Technology Trends in the context of how
industry leaders and competitors are using
them. Start with Defining your Industry
Manufacturing Complexity along 4 core
areas:

1. Method of Manufacturing
◦ Discrete vs. Continuous vs. Job-shop. The nature
of your process defines the focus on speed,
3. Spread of Manufacturing setup, has a deep impact on the
quality and changeovers. (Figure 6)
choice of technology.
▪ Discrete or Batch Processes need speed of
◦ Measurements of different metrics through sensors,
change to reduce downtime during process
cameras and controls
changes.
◦ Size and distance of facilities can vary due to input costs,
▪ Repetitive or Continuous processes need to
supply lines, process complexity and regulations
boost the throughput of high-volume consis-
◦ Mobility requirements. Discrete, job-shop processes and
tent, repeatable production lines.
supply movements need data from mobile devices
▪ Job-Shop Processes are highly specialized or
◦ Multiplicity of locations and production lines. Larger
small batch-runs –focused on high quality,
companies need to aggregate multiple lines and locations
performance-sensitive work, at lower through-
working in sequence or in parallel.
puts. They are prevalent in R&D, Process
Development and Premium products.
4. Collaboration of Manufacturing Ecosystem is between the
◦ Volume and Consistency of demand. In high
company, its Supply Chain and Distribution partners to drive
demand and low margins situations, the need is
productivity and customer service.
non-stop production. With cyclicality in demand of

A
product lines, the focus will move to switch-overs.
For e.g. An E-bike manufacturer needs 99.9%
rticulate Ambition based on the understanding of
uptime to meet its consistently high demand.
manufacturing complexity and technology trends.
The maturity levels can range from Standalone,
2. Dynamism of customer needs changes prioritization
Connected, Visible, Predictable to semi or fully
and can happen due to three primary reasons:
Autonomous. In the context of manufacturing, an autonomous
◦ Regular business cycles, such as hour-of-day,
system is an entity having the capability to control the execution
month-end, year-end. These lead to change in
of its plans and strategies and the ability to recover without
focus from converting sales, supply chain
modifying scheduling. It can structure its own action and
inventory integration to closing of books with
environment independently, without needing any external
auditors.
influence36.
◦ Product and technology release cycles – As new
The 4 technology elements are a) connections across different
versions get released, the production line has to
lines, factories or companies, b) digitalization of sensing data, c)
be reoriented and many new steps are added
precision, automation of controls, d) analytics and simulation of
potentially every week or month.
manufacturing environment, and e) AI/ML based judgement and
◦ Introduction of disruptive technologies – such as
decisioning required.
mobile commerce, GPS-tagging, visual AI
analytics, can create new data streams that need
One example of how manufacturing methods can create
to be prioritized.
different levels of desired technology maturity is shown below:

Manufacturing Technology Maturity Levels

Methods
Connected Visible Predictable Autonomous
Repetitive or • Scada Integration • Energy Management & Distribution • Predictive maintenance • Autonomous material
Continuous • Video Assisted Application • ML for quality analytics handling using AMRs or
• Industrial Sensors • Process Automation AGVs
processes
• Process Monitoring • AR/VR enabled Collaboration
Discrete or • Factory Floor • A digital twin to manage assets • Predicted Maintenance cycles • Automated Product Quality
Batch Processes Connectivity • Asset, inventory management • AR/VR enabled Collaboration Management
• Product Lifecycle • Product Design Management • Assisted Assembly
Management (PLM) • Video Assisted Application
• Remote Plant Monitoring/Visibility

• Collaboration
Job-Shop • "Smart Product" Development
Processes • Design • AR/VR enabled Collaboration
Management

Figure 6: Methods of Manufacturing impact Desired maturity

© Zamun 2024 07 Whitepaper 2024-25

S
et Stack and Specifications. Manufacturing elements. We are trying to answer these basic questions on tech
organizations need to formulate the stack and specifications based on the ambition. Here's how
technology stack levels based on the chosen Manufacturing Complexity can impact a company’s Technology
technology maturity, across the 4 technology need:

Complexity Dimensions Technology Need Tech Metrics Basic question it answers

How often is connectivity needed
Discrete vs. Batch vs. Job-shop Multiple iOT measurements a. Uptime
Method (Active / overall time)
of Manufacturing Volume and Consistency Variation in availability, no jitter
of demand
Non-stop production b. Reliability
(needs spectrum diversity)

Regular business cycles

Ability to prioritize and change c. Agile How much variability is expected in use
fast, without physical visit Prioritization cases priority with No click provisioning

Dynamism Product and technology Connectivity with

of customer needs release cycles design partners How secure should the data transfer
d. Secure Cloud
Introduction of R&D connectivity been against vulnerabilities
disruptive technologies with academia

e. Bandwidth How much data needs to be downloaded or

Measurements of different Visual (high bitrate)
taken back across concurrent channels
metrics/dimensions Two-way communication f. Backhaul (Backhaul = Upload)
Large Area, How secure should the data transfer
g. Coverage
Spread Size and distance of
Long distance connectivity been against vulnerabilities
of Manufacturing production facilities Connection with many How many devices per area, with
setup devices in a dense area h. Device Density
concurrent active connection
Mobility requirements Moving materials to measure
of data capture Robots and moving controls
i. Mobility How much do data providing sensors move

Multiplicity of locations instantaneous long-distance

and production lines communication
j. Latency How quickly we want to see response
across long distance locations

Supply Chain ERP, production collaboration

Collaboration k. Cloud How often is connectivity needed
of Manufacturing Volume and Consistency Logistics, Marketing Collaboration (Active / overall time)
Ecosystem of demand collaboration tools

And here is an example of selecting the right maturity level for a few technology metrics:

Example Tech Metrics Connected Visible Predictable Autonomous

b. Reliability Three-nines Four-nines Six-nines Six-nines

e. Bandwidth 1 – 10 kbps 10 kbps – 10 mbps 1– 25 mbps 1– 100 mbps

h. Device Density 1,000 – 10,000/km2 ~100,000/km2 ~100,000/km2 ~100,000/km2

j. Latency <100ms <30ms <10ms <5ms

K
eep KPIs Clear. Given the time and cost As the manufacturing company defines its relevant technology
investment, business and technology teams trends, ambition, technology stack and specification and the right
should define metrics such as production KPIs, it becomes relatively easy to choose the elements of the
volume, timely delivery, etc. to connect tech Network Technology Stack across the four levels : (Figure 7)

I
with business ambition. Some metrics for regular review: nstrumentation (Sensory and Motor) Digitalization
▪ Production efficiency technologies – for converting instrument measurements
▪ Supply chain response times into digital data and taking control actions remotely -
▪ Customer response times and experience the choice between iOT technologies.

C
▪ Maintenance repair/shutdown times onnectivity technology – for picking data from devices in
▪ Quality of control decisions a reliable and useful manner. -
the choice between mobile and Wi-Fi.

A
pplication Cloud Collaboration technology –
for collaboration securely for ERP and Marketing–
the choice of cloud date centres.

N
etworking technology – for bringing together applications
from all locations and companies -
the choice between SDWAN vs. LAN.
In the following sections, we detail the choices, pros and cons and
relevant manufacturing use cases for these technology choices

08 Whitepaper 2024-25 © Zamun 2024

Converting Business Ambition to
Technology Choice
Now it is easier to pick up each of the technology With this comparison, it becomes clearer which
choices and check their performance against the technology helps a manufacturing company
relevant technology metrics of: a) Uptime, b) achieve its desired state of maturity at the best
Reliability, c) Agile Prioritization, d) Secure Cloud, Return on Investment. Let’s see these by each
e) Bandwidth, f) Backhaul, g) Coverage, h) Device technology element in the following sections
Density, i) Mobility, j) Latency, and k) Cloud
Collaboration.

Instrumentation
Connectivity
Application
Networking
5G

Figure 7: Network Technology Stack in Manufacturing

09 Whitepaper 2024-25 © Zamun 2024

1. Instrumentation Digitalization Choice

The choice of instrumentation digitization is the Available Options for Instrumentation

foundation of creating a connected manufacturing Digitalization Technology
setup and hence is fundamental to all the higher
maturity stages. The key use cases that are relevant There are primarily two options for this digitalization
here are: technology:
i. Point of Sale instruments, such as: a. GPS based tracking, with Sim-card based mobility
a. Sound boxes for e-commerce and tech – This technology is high location accuracy
m-commerce transactions and can provide high upload bandwidth. Since it
b. Smart meters for Utilities such as EV charging can be on a smartphone operating system it can
and household power be upgraded on the cloud. However, it is
ii. Telematics for remote information and control of expensive, and needs direct line of sight to GPS
vehicles, such as for opening doors, activating satellites
ACs, infotainment, seeing driving speed and
acceleration, reading maintenance schedules for b. Cell phone Tower based tracking – This
fleet vehicles technology triangulates location based on cell
iii. Logistics and Fleet management (for containers, phone tower locations and hence is low cost and
trucks, taxis) for smart location tracking does not need direct line of sight to satellites.
iv. Managing Industrial Equipment to drive optimal However, it is lower accuracy and has low data
usage, reduce damages, avoid theft, ensure good upload bandwidth. It can also track assets without
technician work approach dependency on the fleet owner. Such technology
Today, the use of IOT technologies is really growing comes in a low size, and with standard batteries –
exponentially. Industrial IOT Deployment which were at leading to easy use and replaceability for rugged
15.7 billion devices in 2023 are likely to grow to ~39 use conditions.
billion devices by 203023 , at a growth rate of 16%.

The key considerations here are primarily mobility,

uptime and reliability since a small amount of data must
be sent mainly for analytics and transaction purposes.
Bandwidth millisecond latency and agility are not as
essential, unless the use-case elevates to autonomous
or remote-controlled vehicles.

Case Studies of iOT Instrumentation Digitalization Technology

Remote Genset Monitoring Autonomous

A large manufacturer was deploying The IOT solution used was an end-to-end Based on the incoming data stream, the genset
gensets in remote locations and was IOT platform with an Edge Gateway, and manufacturer was able to build models that predicted Predictable
unsure about fuel usage levels and Integration hub, a centralized Data genset breakdowns 30-40 hours before they happened,
security of the same. Management platform and a Web/Mobile leading to pre-emptive repairs. This led to major benefits Visible
application for tracking the solution. The • 25% reduction in product breakdowns
IOT system was deployed along with the • 30% in reduction in warranty costs Connected
genset to provide real time insights into the • 25% improvement in MTTR (mean time to repair)
performance of the genset. Standalone

The Problem Statement The IOT Solution

Theft in transit Autonomous

Companies transporting raw materials and The IOT solution deployed was a cellular Remote area asset tracking of high value assets was achieved Predictable
finished goods in remote areas have a connectivity triangulation to track and with:
major issue of loss from theft or monitor assets to minimize losses. This • Instant alert on parameters. Visible
negligence due to poor visibility and works on basic cellular connectivity and can • Automation tools like Geofence, Route replay, Live location
controls. Remote areas have poor have 20-25 days battery life with a 1 hour • API Integration with customer’s telematics/logistic platform Connected
connectivity and cost of expensive devices ping. • 70% lower cost compared to traditional GPS tracker
is not affordable. Standalone

© Zamun 2024 10 Whitepaper 2024-25

 2. Connectivity Technology Choice
4%
4%
Entertainment and retail
Utilities
After choosing the instrumentation digitalization B. Public 5G – also provides the right latency and
method, we move to connectivity. The key coverage, in case the Public 5G infrastructure is reliable.
5% Public sector

7% Other

6%

6%
Education

Healthcare
considerations here are a) Uptime, b) Reliability, e) This solution compromises on security and might not be
8% Mining and oil and gas Bandwidth-spectrum slicing, g) Coverage, h) Device possible in remote areas with poor connectivity. For e.g.
17% Transport and logistics Density, i) Mobility, and j) Ultra Low Latency when government services are needed for high volume
of use cases, at low cost, with less security concern
Available Options for Connectivity Technology then Public 5G gives all the desired benefits such as
44% Manufacturing Metro and transport.
There are primarily four potential Connectivity
technologies to choose from: C. Private 4G - can be utilized in cases where latency and
Figure 8:
5G share of publicly * 4 choices to A. Private 5G – provides the best bandwidth requirements are low, while the requirement
announced private LTE/5G deploy Private mix of latency, long distance for device density, coverage and mobility are high
networks, 2022 5G
coverage, device density and a. Security and dedicated access at par with Private
lower capital
expenditures, with security. Private 5G 5G, at nearly the same investment
right security. implementations tend to require
higher upfront capex typically in b. Ability to handle good data downloads, but
1. Isolated Private
the range of ₹5 cr or more, restricted in uploads for e.g. HD CCTV.
5G,
2. Hybrid private which can be optimized by
5G - Remote utilizing one of the shared D. Wi-Fi – is the simpler solution for a low device density,
Core Network, deployment scenarios*. Private and low power requirement IoT scenario. Suitable only
3. Hybrid Private
5G, however, turns out to be for indoor applications as fixed IoT devices, don’t need
5G – Shared mobility
RAN, reasonably low on operating
expenses for Massive IoT.
The global market opportunity for Private 5G Networks
a. Dedicated access and bandwidth - Use of
excluding China has been $1.2B in 2024, and will increase
special 13-digit SIM card for devices to
to $21 B by 203025. Manufacturing will account for ~40% of
differentiate from human users. Use of dedicated
global private 5G deployments.
Access Point Names APNs, rather than GPRS, so
that the private 5G core is dedicatedly available Key Metrics Private 5G Public 5G Private 4G WiFi
b. Ability to handle high-volume data for both a) Uptime 99.9999% 99.9999% 99.9999% 99.9% not possible
b) Reliability
downloads and uploads. With low latency and
Very high Very High High Lesser
c) Agile Prioritization Can be achieved by creating a secure network

great mobility hand-offs, such as CCTV HD video, d) Secure Cloud Fully Secure Not Secure Fully Secure Not Secure
(WPA vulnerable to hacking)

drone data, robots and AGVs. e) Bandwidth

f) Backhaul
Upto 1 GBPS
Upto 1 GBPS
Upto 1 GBPS
Upto 1 GBPS
Upto 100 MBPS
Upto 10 MBPS
Upto 1 GBPS
Upto 10 MBPS

c. Future Readiness – as 5G networks ability to g) Coverage

h) Device Density
Indoor + Outdoor
100-1000 per node
Indoor + Outdoor
100-1000 per node
Indoor + Outdoor
50-100 per node (??)
Only Indoor24
30-35 per node
take on more device density and bandwidth is i) Mobility Pan India Pan India Pan India Fixed Location

already there, more devices and use cases can j) Latency ~ 1ms ~ 1ms 20- 50 ms > 100ms
k) Cloud Collaboration Can be achieved by creating a secure network
easily be added without adding more Access • Targeted for Industry 4.0 • Capable for Industry 4.0 • Part capable for Industry • Part capable for Industry

Points, and no further capex is required.

• 10-year IoT device battery • 10-year IoT device battery 4.0 (good for mobility and 4.0 (good for static
life life downloads) uploads - HD Video
Others • High spectrum diversity • High spectrum diversity • 10-year IoT device battery streaming)
eMMB, ULRCC, mIoT eMMB, ULRCC, mIoT life • Very low device battery
supported supported life

Case Studies of Private 5G Connectivity Technology

Patchy Wi-Fi Limiting Industrial Automation

The existing Wi-Fi network at a Automobile plant The Private 5G Solution created a network The Automobile manufacturer was able to run various
was impacting the plant’s efficiency due to to connect 1500 devices using an Industry 4.0 use cases seamlessly with increased
patchy coverage and high latency. This further On-premise Core and 7 industry grade production, automated data reporting and reduced
hampered customer’s goal to deploy industrial radios (5 Indoor + 2 Outdoor) network blind spots
use-cases to connect assemblies and Production
units, and to drive more efficient Inventory
Management and Fleet management. Autonomous

Predictable
The Problem Statement The Private 5G Solution
Visible

Connected
Paint Defect Detection needed Machine Learning
Standalone
The automobile manufacturer needed to The Private 5G + Machine Learning Solution Cloud image processing with ultra-low latency and
accurately identify paint defects in the enabled real time HD video streaming to Massive IoT device density ensured that paint defects
production line, while the Local CPU was the Private Cloud, enabling all HD images to were identified while the production line was in process,
not able to do HD image processing be processed on a cloud hosted GPU allowing for in process solution of the paint defect,
reducing final production errors entirely.

11 Whitepaper 2024-25 © Zamun 2024

3. Application Cloud Collaboration Technology Choice
Multi-location manufacturing ecosystems work together for Available Options for Cloud Collaboration Technology
better R&D and operational efficiency. Increasingly
collaboration applications are using AI for language support, A. On-premise Cloud – This gives full control and security,
image identification, chat-bots and analytics. which can only however, has the immense need for upfront capex and
be served from a high-compute, high-data, machine learning direct ongoing maintenance responsibilities, with less
environment – on the cloud. We see 5 key use-cases for features. This option might only be reasonable where data
Cloud collaboration: centre and hyperscale cloud solutions are not available.
B. Dedicated Private Cloud hosted by Data Centre Providers
1. ERP Connectivity – Enterprise Resource Planning across – Gives full control on privacy and security, while removing
locations and partner ecosystem is essential for better the hassle of maintenance. However, the capex and
production efficiency and has to be done in a real-time upgrade investment remain with the manufacturing
secure manner. company and applications availability is limited.
2. BCP and DR – Business continuity and Disaster Recovery C. Multi-tenant Cloud hosted by Data Centre Providers- This
highly depend on data recovery, which is best done on converts all capex to opex as the Data Centre provider
cloud with auto back-up settings. takes over responsibility of setup and regular upgrades.
3. Logistics – Visibility of raw material and finished goods However, the access and provisioning are still physical,
inventory through iOT devices and partner data is while AI application availability is limited. New partners
possible only through a shared network, ideally the cloud. cannot be added instantaneously.
4. NPD – New Product Development needs remote data
D. Hyperscaler Cloud hosted by global providers - AWS, GCP,
sharing and control for working across countries and with
Azure – the most advanced version, where provisioning is
academic institutions, all of which are available on the
fully virtual, allowing for scalability to new partners, access
cloud and use the higher end AI services.
to AI/ML applications and fully virtualized BCP and DR.
5. Marketing – has become highly digital-first and all
customers and influencers are online, hence managing
the marketing platform is best done on cloud-applications, The global cloud market for engineering and manufacturing
using language, image and conversational AI tools. Operations was $13 billion in 2021 and is growing at 26%
CAGR to reach over $107 billion. This is driven by PLM
While the early use cases of ERP and BCP focus mostly on systems, and design and simulation systems such as
a) Uptime, b) Reliability, g) Coverage, h) Device Density, and CAD/CAM23
j) latency; the higher order use cases of logistics needs much Cloud Technology Options
higher i) mobility; and insight dependent use-cases of NPD Use Cases On-premise
Cloud
Dedicated
Private Cloud
Multi-tenant
Cloud
Hyperscaler
Cloud
and Marketing needs much higher d) Security, e) Bandwidth, ERP Connectivity Local data Sharing across Sharing across Sharing and
f) Backhaul and k) Cloud Collaboration. analytics for SCADA locations Locations and partners AI/ML applications

BCP and Disaster Secure backup Backup as Disaster Data recovery Data + Application
a service as a service recovery
Recovery
IOT backwards IOT across IOT + Data analytics
Logistics - data availability supply chain and automation

New Product -
Development

Marketing - -

Case Studies of Cloud Collaboration Technology

Secure critical server infrastructure

A large scale process manufacturing company need to avoid The Hosted Data Centre Security Solution Secured network benefits were available
zero-day threats while there was lack of skilled security experts enhanced physical and virtual security across instantaneously across the nationwide network in
at remote locations. The presence of Industry 4.0 applications on-premise, hybrid, and cloud-based data centers. partnership with global security products and Service
had exposed many functions to operational risks as the digital This was done by application whitelisting, OEMs
supply networks were widespread and open. fine-grained intrusion detection & prevention, - High uptime increases production and helps meet
including system & admin lockdown, integrity and demand
configuration monitoring - Network security protection against perimeter
Autonomous
breaches for critical manufacturing assets
Predictable
The Problem Statement The Private Cloud Solution
Visible

Connected
High operational efficiency and agility
A leading seed manufacturer company. It had IT infrastructure The Private Cloud Solution brought together all the The enhancement of standardized visibility Standalone
across 17 countries, and the lack of standardization, due to local core IT infrastructure under highly scalable private and controls led to better market
3rd party data centers, led to high TCO. This lack of network cloud. The new platform could handle change in responsiveness, lower technology opex and
flexibility and agility was hindering business visibility, scale and workloads and also improved security with a TCO, higher productivity with enhanced
time to respond to market needs. world-class firewall management security.

© Zamun 2024 12 Whitepaper 2024-25

4. Networking Technology Choice
For industrial complexes where many different units come such as MPLS, 4G, 5G, satellite internet, RF, VSAT and
together to form an integrated value chain, it is critical to have hence is not dependent on any provider or technology
an integrated visibility across all partners. For remote factory to create a high bandwidth network, if they work on the
locations, many times reliable connectivity may not be IP protocol. SDWAN providers such as Airtel have
available and a single connectivity provider may not be partnered with multiple local MSOs27 such as evotel,
sufficient. In such a situation, a solution is required to create a SDL, local cable providers to provide access to all
network across multiple providers and network types. They available networks, beyond their own.
might share the same application ecosystem, the same cloud, e. SDWAN can do dynamic allocation of network as new
or go to link based data exchange, but will need a virtual digital use cases emerge, by creating primary and
network regardless of this method. There are fundamentally secondary SLAs and QoSs. This is possible through
two use cases: centralized controller and software defined
1. Manufacturers who work with many vendors, using ERPs provisioning.
and APIs. Auto manufacturers typically source over 2,000 f. SDWAN allows secure sharing of data between
parts from multiple vendors from nearby vendor zones different organizations, such as ERP, supply chain
and remote places. information, dealer management to update their
2. Direct Consumer Marketers that work with distribution demand and inventory levels directly over a secured
dealerships. They need virtual network for dealer channel.
management, especially for remote locations such as Leh
and Thar.
Given connected manufacturing setups are now very
complex with multiple plans, and companies connected Traditional Network
across the supply chain, it becomes imperative to create a
single network feel with very low latency and high bandwidth Switch Control Plane
across multiple networks and locations. This needs the Data Plane
creation of a ‘virtual network’ that brings all types of networks
– whether Wi-Fi, LAN, WAN or 5G, into one network for all
practical purposes, without losing security.

Available Options for Networking Technology Software-Defined Network

1. MPLS or Multiprotocol Label Switching is a routing Programmable
Switch
technique that directs data from node to the next based
on labels rather than network addresses.
a. MPLS needs purpose-built devices to access the
network using label switching. It works on
pre-tunnelled routing and hence it is very reliable Controller
although limited to where these dedicated routes have Machine
been created.
b. MPLS is inherently secure, given its closed Figure 9: The difference between SDNs and traditional networks
device-constrained nature
c. MPLS bandwidth is expensive and limited, and
cannot be shared
d. MPLS can not be prioritized for variable use cases Here’s some architecture29 and metric wise comparison that
once the provisioning has been done. It typically needs can help companies choose their virtual networking
physical access to devices to change application and technology30.
data prioritization.
Key Metrics SDWAN MPLS
2. SDWAN or Software-Defined Wide Area Network is a
a) Uptime 99.9999% 99.9999%
wide area network that uses software-defined networking
technology over the Internet using overlay tunnels which b) Reliability Very High Very High

are encrypted. Instantaneous Not possible

c) Agile Prioritization
a. SDWAN is based on IP based routing, and hence re-prioritizable without visit

dynamic tunnel creation can happen, allowing for d) Secure Cloud Can be secured
with SASE
Fully standalone
and Secure
easy addition of new entities on the network. Can be aggregated Must be built using only
e) Bandwidth
b. SDWAN can enable load sharing of traffic based on across multiple networks one provider’s network
Where there is a
criticality, availability and latency, while still offering i) Mobility Pan India
defined providers network

secure and dedicated channel. This result is significant k) Cloud Collaboration Can be achieved by Sharing not possible unless
creating a secure network on the same device network
cost optimization of IT and communication Low Capex, can merge High Capex,
Costs
expenditure. across all network types needs purpose-built devices

c. SDWAN can aggregate over two or more service Others Dynamic tunnel creation
Can create network across
Pre-planned device-based
tunnel
providers, thus increasing overall capacity. It also different providers and
network types
Can create network only on
one provider
allows higher reliability by switching and prioritizing Can dynamically change Dynamic QoS changes not
QoS and SLAs possible
traffic during failure modes.
d. SDWAN can also aggregate across network types

13 Whitepaper 2024-25 © Zamun 2024

Here are some most cited reasons to deploy SD-WAN with Factors Driving SD-WAN Adoption SD-WAN Cost Savings
the leaders of SD-WAN technology31. Application visibility 59.6%
> 40% 1.1%
Enable better
business continuity 56.5%
26 to 40% 16.9%
Consolidation of all
network devices/ 55.9%
functions 11 to 25% 37.6%
Enable effective
network management 53.8%
5 to 10% 35.7%
Apply and manage
security policies 53.1%
effectively
Less than 5% 8.3%
SDWAN can also be integrated with MPLS to get both Effective utilization
of multiple transport 53.0%
benefits as appropriate28. Additional Security can be offered links
Easy provisioning of
50.5%
in SDWAN through Secure Access Service Edge (SASE) new branches

where individual devices can be configured for secure Improved application 48.3% Figure 10: Reasons to deploy
performance
remote collaboration. This allows organizations to enable SD-WAN
effective work from home policies and remote work Reduce costs on
MPLS/private circuits 48.3%
ecosystem. Remote yet secure access can be enabled Reduce vendor
dependency/lock-ins 42.0%
despite using Broadband/LTE/5G internet.

Self Service
Web Portal

Internet SDWAN NFV SDN

RO MANO Controller SDN
Switch

CE 2.0 / MPLS SD-WAN

Gateway Central Office,
CPE Data Center or Head End SDN
Switch

Figure 11: SD-WAN - Can integrate with MPLS and provide additional security

IDC forecast data shows that in 2022, the SD-WAN infrastructure market grew 25.0% and through 2027, the market will grow at a
compound annual growth rate of 10.1% to reach $7.5 billion32.

Case Studies of Networking Technology

Central inventory view across 190 factories

An Indian auto parts and tyres manufacturer SDWAN created a virtual tunnel across 190 factories, Cloud based VPN allowed the company to:
wanted to have a central view of the raw while aggregating 5G, Lan and 4G connections. This - Create a bandwidth of up to 10MBPS by using an aggregation
materials and WIP inventory across all locations created a full view across all assembly lines. The OT of up to five, 2MBPS connections, that allowed for HD video
– may of which were in remote areas, while Operating Technology and SCADA views across all along with SCADA integration across locations
some were in well-connected zones these lines was now visible in a central office over the - SLA uptime of 99.99% availability, 60-80 ms latency from
cloud, with no need to set up a fully private network. pop-to-pop was reliably achieved
The connectivity was provided with one main provider, - Dealer management system was able to move from
and a secondary backup provider for enhancing prioritization of Sales, Service to Support with regular SLA
reliability of uptime and reducing jitter. re-prioritization (e.g. from tracking to billing), with real-time
provisioning using pre-set templates, without local tech support Autonomous

Predictable
The Problem Statement The SDWAN Solution
Visible

Multiple Connectivity, Centralized Management & Security Connected

A multinational electronics manufacturer SDWAN enabled Active-Active mode and auto This new virtualized WAN created much better Standalone
was facing over-utilization of MPLS failover on MPLS over Internet. Provided a - Network agility through application aware routing with a
bandwidth as all traffic was routed through centralized console for all policy and change mesh network
one central hub and there was no management. Solved the security issue with a secure - Security of cloud applications with local internet
centralized console to check network channel local internet breakout for cloud applications. - Operational efficiency and failover support with
performance while there were security centralized management
vulnerability to cyberattacks

© Zamun 2024 14 Whitepaper 2024-25

Getting started to set
the right technology
As you set up your manufacturing organization to set up d. Stage-wise Investment Approach – It’s important
your leadership ambition, it becomes clear that setting to set up key metrics, both operating and financial
the right environment for business benefits from to ensure that these are being achieved. Metrics
technology is necessary. While the above approach need to relate to goals that are tangible – such as
focused on defining the TASK right, and then going increase in production or revenue and customer
onwards to set the ICAN technology stack, there are satisfaction. At the same time, they also need to be
few other considerations that are needed. Specifically, connected with technology metrics so that
these are organizational set-up requirements, that cover technology gets the impetus to run smoothly – to
areas of leadership, vision, skill, investment approach deliver on the purpose. Once metrics are achieved,
and review mechanisms. the plan should be extended to the next stage of
use-cases as trust in technology is built across the
We believe that the following steps will help in drive the organization.
best return on the technology investment: e. Regular Review Mechanisms – Measurement will
get visibility, but there will always be missing
a. Explicit Leadership Engagement – Most CXOs of pieces and unknown root-causes. A data-driven
the manufacturing organization need to be aligned and analytical review process, with good follow-up
with the choice of use-cases and the technology program management is necessary to drive the
implications of the same. As technology value from technologies, especially for
investments only work out, when they are manufacturing companies with high spread.
implemented well and utilized with an increasing
number of use cases. The enthusiasm of the
leadership team cascades across the organization
leading to better long-term ROI and competitive
advantage.
Explicit Detailed
b. Detailed Strategic Vision – The leadership team
Leadership Strategic
should explicitly mention the vision they have with Engagement Vision
the increasing use of the technology. Metrics
should be connected to what will be tangibly
achieved so that the teams are aligned and
excited.
c. Skill Development and Staff Engagement – The Skill
lack of technical skills and organizational talent is Regular Development
the main reason why some organizations are Review and Staff
unable to invest in the right technology or, worse Mechanisms Engagement
still, unable to leverage the investment. A focused
approach to train on use cases must be done and Stage-wise
key technology people should be encouraged to Investment
learn the new technologies, like AI. Additionally, Approach
hiring for the right skill set is essential.

Figure 12: Steps to maximize return on technology investments

Conclusion
Manufacturing companies have a huge opportunity to drive profitable growth by better integrating devices
with analytics and AI across their supply chain in a secure and real-time manner. By evaluating technology
trends and setting ambitious use-cases, manufacturing enterprises can identify their business KPIs and
technology metrics that allow for the right choice of networking technologies across IoT, Connectivity and
Application Collaboration.

To ensure a definitive move towards the most mature "Autonomous" stage of Manufacturing Networking
Technologies, manufacturers need to align development of technology, business models and ecosystem
relationships in multiple steps of maturity. Such a stepwise approach will ensure the right future-readiness,
while ensuring good Return on Investment of Networking Technologies.

15 Whitepaper 2024-25 © Zamun 2024

 Why Airtel Business for
Network Technologies Choices
Airtel Business is a leading provider of integrated communications solutions in India. With a wide gamut of end-to-end
solutions spanning cellular IoT, connectivity, cloud, data centre, cyber security and cloud-based communications, the
company’s offerings are engineered to deliver high-speed connectivity, unparalleled wide coverage and scalable
bandwidth to customers across enterprises, governments, carriers and small and medium businesses (SMBs).
Benefits

Airtel Business Benefits Unique Features

IInstrumentation
Digitalization
• Real-time tracking with solutions like basic SIM, Bluetooth,
and GPS-based tracking.
• Data Acquisition Gateway with sensors measure different
parameters (temperature, pressure, or electrical output).
• Airtel Edge Gateway with Sensor
Integration
• IoT integration hub for centralized
and analytics plateforms data
• Equipment Monitoring of industrial equipment, leading to • Variety of Tracking Solutions
proactive maintenance, reduces the breakdown by 25%
and improves the MTTR by 25% .

Airtel Business Benefits Unique Features

C Connectivity
Technology
• Future Readiness – 5G networks allow deploying
Industry 4.0 use cases like Autonomous Mobile Robots,
Smart Surveillance, and OT connectivity.
• Enhances customer experience through a
• Private 5G Network with a reduced
blind spot
• Centralized Wi-Fi setup
• Carrier-Grade security and
• digital environment and seamless internet. compliance
• Cost Efficiency for Wi-Fi controllers and AAA
(Authentication, Authorization, and Accounting)
infrastructure making it a pay-as-you-grow service model.

Airtel Business Benefits Unique Features

A Application
Cloud
Collaboration
• Scalable Infrastructure – Nxtra by Airtel offers the largest
network of secure, scalable, and sustainable data centers.
• Targeted marketing - Airtel Martech, AI / ML powered
platform for fast, reliable, secure communication.
• Strategic Data Centre Locations
• AI / ML-powered Marketing platform
• 24x7 operational Enterprise-Grade
Support
• Cloud Collaboration - Data Center Security for physical and
virtual servers in on-premise, hybrid, and cloud-based data
centers. .

Airtel Business Benefits Unique Features

N Network
Technology
• End-to-end network management through Enterprise
Network Operations Centre
• Secure sharing of data between different organizations,
such as Enterprise Resource Planning
• Centralized network management
• Integration with Siebel ER
• Maximized CRM application usage

• Uniform Network Connectivity with MPLS and internet

network offerings bundled with SDWAN

16 Whitepaper 2024-25 © Zamun 2024

Bibliography
1. https://www.mordorintelligence.com/industry-reports/india-manufacturing-sector-market
2. https://www.angelone.in/blog/india-manufacturing-sector-potential-growth-drivers-and-challenges
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Manish Sinha, leads Zamun - a Marketing Abhishek Khamrai is an industrial

strategy firm focused on B2B Engineering engineer with 15 years of experience cutting
and Tech firms. He has over 25 years of across manufacturing, business consulting
experience across consulting, operations, and technology research.
tech startups and public enterprises in
India, Europe and the US.

Aradhika Mehta is an accomplished Akshita Kabra holds a Master’s in

marketing professional with 15 years of Microbiology and has over 4 years of
experience of leading iconic lifestyle experience in scientific and technical writing.
brands and startups. She builds brands Having worked at CSIR-NBRI, she excels
to drive high growth and premium results in creating well-researched, precise, and
across diverse industries. engaging content across various technical
domains.

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