Sameer Gandhi, Managing Director, OMRON Automation, India.

How has the adoption of robots and cobots evolved in the manufacturing sector over the past decade?

Over the past decade, India’s manufacturing sector has seen gradual but steady adoption of robots and cobots, driven by rising labour costs, skill shortages, and global competitiveness demands. Initially, automation was limited to large automotive and electronics firms using industrial robots for welding, painting, and assembly. However, post-2015, the adoption has grown led by many factors such as the initiatives like Make in India, more deployment of automation by SMEs, particularly in packaging, machine tending, and warehousing (accelerated by COVID-19 pandemic) and e-commerce giants and EV manufacturers deploying robots for logistics and production. Despite this growth, India’s robot density remains low (5-6 robots per 10,000 workers as per the International Federation of Robotics) compared to global leaders, mainly owing to high costs and skill gaps. 

Looking ahead, cobots and AI-driven robotics are expected to drive the next wave of automation, especially in pharma, textiles, and food processing. Government schemes like PLI (Production-Linked Incentives) and increasing FDI in manufacturing will boost adoption, while startups are innovating in logistics and smart factories. However, challenges like high upfront costs, labour resistance, and training gaps persist. As India aims to become a global manufacturing hub, robotics and cobot adoption will likely surge, bridging efficiency gaps and enhancing productivity across sectors.

Which industries or manufacturing processes are seeing the most significant adoption of robotic automation?

Over the past decade, India's manufacturing sector has seen the most significant adoption of robotic automation in the automotive and electric vehicle (EV) industries (welding, painting, battery assembly). Other sectors that have seen positive trends are – electronics manufacturing (PCB assembly, precision component handling), pharmaceuticals (packaging, lab automation), and FMCG/food processing (palletizing, sorting). This is mainly driven by the need for precision, scalability, and compliance, alongside rapid growth in e-commerce warehousing (AGVs, sorting robots) due to rising demand for logistics automation. Cobots are gaining traction in SMEs for machine tending and quality inspection. Though adoption remains constrained by high initial costs and skill gaps compared to global leaders like China.

What are the key factors driving the increased use of collaborative robots (cobots) over traditional industrial robots?

The growing adoption of collaborative robots (cobots) over traditional industrial robots in India is primarily driven by their lower cost, flexibility, and ease of deployment, making them ideal for SMEs with limited capital and space. Unlike industrial robots, cobots require no safety cages, can work alongside humans, and are easily reprogrammable for diverse tasks – key advantages in India’s labour-intensive manufacturing landscape. Additionally, rising wages, labour shortages, and government incentives (like PLI schemes) are pushing industries like automotive ancillaries, electronics, and FMCG toward cobots for tasks such as assembly, packaging, and quality inspection, where precision and adaptability matter more than sheer speed or payload capacity. 

How do AI, machine learning, and vision systems enhance the capabilities of robots in manufacturing?

AI, machine learning (ML), and vision systems allow robots to learn from data, adapt to variability (e.g., mixed-product and low-volume-high-mix assembly lines), and collaborate seamlessly with humans – making automation viable even for complex, small-batch production.

They are transforming industrial robotics by enabling autonomous decision-making, precision, and adaptability. AI/ML algorithms optimise robot paths in real-time, predict maintenance needs to reduce downtime, and improve quality control by detecting defects (e.g., in automotive welding or PCB assembly). Vision systems, powered by deep learning, allow robots to recognise irregular objects (like unsorted items in logistics) or perform micron-level inspections (in electronics or pharma).

Are there concerns about job displacement, and how can companies address workforce transition challenges?

Job displacement concerns due to robotics in India are real but manageable, particularly in labour-intensive sectors like textiles, automotive assembly, and low-skill manufacturing. OMRON believes that we can create harmony between people and machines on the floor rather than positioning them against each other. The vision needs to enhance human beings` capabilities with the use of robots. The aim of Robotics deployment is to take over repeated or heavily manual and hazardous tasks and create new high-skilled jobs in return.

Companies can address workforce transition through upskilling programs and internal job shifts; cobot integration – that is using collaborative robots to augment (not replace) workers; and early reskilling – proactively train employees before automation deployment.

In a nutshell, the focus should be on job transformation, not elimination. Manufacturing workforce can evolve alongside automation if reskilling starts early.

Where do you see the biggest innovations in robotics for manufacturing in the next 5-10 years?

In the next decade or so, the robotics sector is expected to witness some good innovations like AI-driven autonomous robots (to be used for self-learning for defect detection), hyper-flexible cobots (voice-controlled for SMEs), and 5G-enabled fleets for electronics/auto sectors). Sustainable robotics (solar-powered AGVs, e-waste recycling bots) and digital twins (simulated factory testing) might gain traction too. Robotic drones are also expected to further transform inventory management, agriculture and pharma logistics (lab sample transport). Key sectors leading adoption will continue to be automotive including EVs, electronics, and pharma.

(The views expressed in interviews are personal, not necessarily of the organisations represented)

Reference

https://ifr.org/ifr-press-releases/news/robot-density-rises-globally