Subrata Karmakar, President, Robotics & Discrete Automation Division, ABB India.

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

Over the past decade, the adoption of robots and cobots in the manufacturing sector has witnessed significant growth, driven by various factors and resulting in substantial changes within the industry. As of 2023, the global average robot density reached a record high of 162 units per 10,000 employees, more than double the figure from 2016, as noted in the World Robotics 2024 report. This surge highlights a broader trend towards automation, spurred by escalating labour costs across industries worldwide. These costs, influenced by stringent government regulations, supply and demand imbalances, and a shortage of skilled labour, have made automated solutions increasingly attractive. Automation not only provides a more economical choice but also plays a critical role in the expansion of the Industry 4.0 market, which aims to enhance functionality, controllability, and safety in industrial environments.

India's robotics market exemplifies this rapid growth, with a record installation of 8,510 industrial robots over the past year, marking a 59% increase from 2022. The automotive sector significantly contributes to this growth, experiencing a remarkable 139% rise in demand and achieving 3,551 robot installations. A notable example is ABB’s PixelPaint technology, which ensures quality and efficiency while minimising waste in EV production.

Consequently, India has climbed to the seventh position globally in annual robot installations, signaling strong potential for continued automation growth into 2024 and 2025. Several factors drive this surge, including the Production Linked Incentive (PLI) schemes designed to promote local manufacturing, need for flexibility, quick changeovers, and ‘batch size one’ production. Moreover, medium and small-sized companies are increasingly adopting automation to improve efficiency and quality, navigate economic uncertainties, and address sustainability concerns.

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

Robotic automation is making significant inroads into several industries, with the automotive sector leading the charge in India. Advancements in artificial intelligence, generative AI, mechatronics, vision, and mobility are driving this trend. Traditionally restricted to structured operations, robots in automotive settings are now managing unpredictable tasks, such as sorting varied parcels in logistics centers. This capability has expanded automation to construction, warehouses, logistics, pharmaceuticals, and agriculture. ABB Robotics has partnered with an additive manufacturing solutions provider to advance 3D printing technologies for the Indian construction sector. This collaboration aims to help construction companies build structures faster, more sustainably, and safely.

AI-enabled robotics is also transforming sectors beyond manufacturing – healthcare, life sciences, retail, and construction. In construction, these robots enhance productivity, improve safety, and support sustainable practices like on-site assembly and modular construction. As these technologies continue to evolve, robotic automation is poised to drive innovation and operational efficiency across diverse industries.

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

The rise in collaborative robots (cobots) versus traditional industrial robots is driven by labour shortages and the need for flexible automation solutions. By 2023, cobots made up 10.5% of industrial robot installations globally. They are popular due to their easy programming – often through intuitive hand-guiding or tablet interfaces – and typically need no additional safety measures, allowing seamless integration into existing production spaces without the need for fencing. A prime example is ABB's GoFa™ cobots, which feature the Ultra Accuracy capability, delivering the highest precision level in cobots, with over 10 times greater path accuracy, making them ideal for industries with high accuracy demands, such as electronics and assembly.

Cobots are especially beneficial for companies lacking engineering expertise, those with smaller production runs, or industries with constantly changing production requirements, thanks to Plug & Play technologies. The shortage of skilled workers has further propelled the shift towards automated solutions, often bringing manufacturing closer to consumer markets.

Cobots are expanding into new applications – from handling and welding to painting and assembly – as machine learning systems enhance their capabilities. These systems enable cobots to learn and operate unattended, increasing their versatility. Future advancements in sensors, vision technology, and AI will further improve cobots' ability to adapt to environmental changes, ensuring safe and effective collaboration with human workers.

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

AI, machine learning, and vision systems elevate robotic capabilities in manufacturing by enabling greater autonomy, precision, and accessibility. AI enhances tasks like gripping and navigating dynamic environments, while technologies such as ABB’s Visual SLAM allow robots to map and adapt to surroundings, reducing infrastructure needs and facilitating flexible production. Additionally, ABB OmniCore™ unified robotics control platform enhances control to boost efficiency, productivity, and sustainability for businesses of all sizes through a modular, scalable solution.

Generative AI interfaces lower the entry barrier by allowing non-coders to program robots using natural language, making robotics more accessible to a broader workforce, including small to medium-sized businesses. AI’s predictive capabilities enhance operational efficiency through predictive maintenance, crucial in reducing costly downtime, particularly in automotive sectors. Machine learning optimises processes by analysing task data, boosting productivity. These innovations make robotics more efficient and user-friendly, promoting widespread adoption across industries.

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

While automation may lessen the demand for certain manual roles, it simultaneously creates new positions in the design, programming, maintenance, and management of robotic systems. The accessibility and user-friendliness of modern robots, enhanced by AI, are reducing entry barriers. This trend empowers even small- and medium-sized businesses to adopt robotics for improved productivity and competitiveness, with advancements like generative AI potentially allowing for voice-controlled operations in the future.

To address workforce transition challenges, companies must invest in workforce training and education. This involves developing programs that equip employees with the necessary skills to operate alongside advanced robotic systems. A focus on reskilling and upskilling is crucial, fostering adaptability and technical proficiency, ensuring that workers can thrive in an increasingly automated environment. Such initiatives not only help businesses embrace robotics effectively but also ensure workforce stability and growth during this technological shift.

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

As AI accelerates progress in industrial robotics, it enhances capabilities such as gripping, picking, and navigating dynamic environments, with technologies like ABB’s Visual Simultaneous Localisation and Mapping (Visual SLAM) enabling new levels of autonomy and a shift from linear production lines to dynamic networks. The potential of AI-enabled robotics is expanding beyond manufacturing into sectors like healthcare, life sciences, retail, and construction. For instance, in the construction industry, AI-enabled robots could significantly boost productivity, improve safety, and support sustainable practices like on-site assembly. Additionally, as advancements in AI and robotics make robots easier to program and use, education is shifting from programming skills to enhancing human-robot collaboration, increasing accessibility and creating new job opportunities, particularly in small to medium-sized manufacturing companies.

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