• Autonomous Robotics
• Blockchain for supply chain trace-
ability
Why India Needs Manufacturing
4.0
India has long been perceived as the
back office of the world, primarily
because of its dominance in IT and
services. However, this created an
imbalance. Manufacturing, which
has historically been a major driver
of
economic
growth
globally,
contributed only about 17% to
India's GDP far below its potential.
With over 65% of India’s popula-
tion below the age of 35, the need
for large-scale employment genera-
tion is pressing. Traditional manu-
facturing alone cannot absorb the
influx of labor. Moreover, global
supply chains are being restructured
due to geopolitical shifts, and India
has the opportunity to emerge as an
alternative to China.
Manufacturing 4.0 offers India a
dual benefit:
1. Competitive Advatage:Through
automation,
predictive
mainte-
nance,
and
AI-driven
quality
control, India can boost productivi-
ty and reduce operational costs.
2. Employment Through Innova-
tion: Contrary to fears of job losses,
advanced
manufacturing
creates
new roles in robotics, AI develop-
ment, cybersecurity, and data analy-
sis.
AI: The Brain Behind Smart
Manufacturing
Artificial Intelligence serves as the
nervous system of Industry 4.0. In
India’s context, it is being deployed
across several key functions:
1. Predictive Maintenance
AI algorithms analyze sensor data
to predict machine failures, reduc-
ing downtime and maintenance
costs. Companies like Tata Steel
have
implemented
predictive
analytics to improve equipment
reliability.
2. Quality Inspection
AI-based computer vision systems
are replacing human inspection with
highly accurate, real-time defect
detection in textiles, auto compo-
nents, and electronics.
3. Supply Chain Optimization
With disruptions becoming more
frequent, AI helps in demand
forecasting, inventory management,
and route optimization. Startups
like Locus are building AI platforms
tailored to Indian logistics challeng-
es.
4. Human-Machine Collaboration
Collaborative robots or cobots,
guided by AI, are assisting workers
in complex tasks. They enhance
productivity
without
replacing
human input ideal for India's
labor-intensive environment.
5. Process Automation
From
welding
to
packaging,
AI-driven
robots
are
making
production lines faster and more
consistent, especially in sectors like
automotive and electronics.
Key Sectors Leading the Charge
1. Automotive
The Indian automotive sector, with
giants like Mahindra, Tata Motors,
and Maruti Suzuki, is heavily
investing in AI for autonomous
testing, precision assembly, and
supply chain intelligence.
2. Pharmaceuticals
AI is being used to accelerate drug
discovery, manage manufacturing
compliance, and ensure traceability.
During COVID-19, Indian pharma
used AI for vaccine logistics and
production scalability.
3. Electronics
India’s drive to become a global hub
for electronics manufacturing (e.g.,
Make in India, PLI schemes) is
being bolstered by AI-enabled SMT
(Surface Mount Technology) lines,
chip testing, and fault analytics.
4. Textiles & Apparel
AI is transforming traditional looms
with smart sensors and computer
vision to enhance fabric quality, cut
waste, and ensure faster delivery
cycles.
Startups
&
Innovators:
The
Grassroots Engine
A unique aspect of India’s AI-pow-
ered industrial revolution is the
startup ecosystem. While conglom-
erates are leading on capital invest-
ments, startups are the innovation
torchbearers. Companies like:
• GrayMatter Robotics: Deliver-
ing robotic automation solutions
tailored for Indian MSMEs.
• Cimpress India: Using AI for
customized
printing
and
mass
personalization.
•
Grene
Robotics:
Offering
end-to-end AI platforms for smart
manufacturing.
These
innovators
are
making
advanced
manufacturing
more
accessible, modular, and affordable
key for India's small and medium
manufacturers who form 45% of
industrial output.
Challenges on the Road to Manu-
facturing 4.0
Despite the promise, India’s journey
to AI-led manufacturing isn’t with-
out hurdles.
1. Digital Infrastructure Gap
Many factories lack the basic digital
backbone stable internet, sensors, or
automated machinery needed to
deploy AI.
2. Skills Deficit
There is a significant mismatch
between available skills and those
needed
for
Manufacturing
4.0.
While IITs and private institutions
are creating talent pipelines, reskill-
ing the existing workforce remains
a challenge.
I F
NDUSTRY OCUS
49 | June 2025 | www.industrialoutlook.in