India’s manufacturing is struggling to breathe during the second wave of the Covid-19 virus. Before the pandemic, the sector was estimated to contribute 25 per cent to the country’s GDP by 2025. The Central Government’s ‘Make in India’ and ‘Atmanirbhar Bharat’ initiatives signalled to the world that becoming a global manufacturing hub was a top priority. The 2021 Union Budget’s Production Linked Incentive (PLI) Scheme to boost local manufacturing attracted three of Apple’s top manufacturers to India — Foxconn, Wistron, and Pegatron. Nineteen global and 14 domestic companies have filed under the PLI scheme . The economy was picking up — that is before the second wave hit. Once again, manufacturers today are facing great uncertainty. Employees continue to succumb to the virus, and states are imposing varying levels of restrictions — some instituting total lockdowns. And with experts anticipating a third wave, why isn’t manufacturing automating faster to protect employees and operations?
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Several Foxconn employees in India recently tested Covid-19 positive. Wistron shut down operations temporarily for the same reason. The cycle of disrupted operations is bound to continue as infection rates soar. Leading automotive manufacturers like Hero Motor Corp., Toyota Kirloskar Motor, and Tata Motors stopped operations or are operating at minimal capacity to prevent the spread. India’s top manufacturing hubs — the Mumbai-Aurangabad belt, Pune, NH-48 Gurugram corridor, Noida, Bangalore, Tamil Nadu, Ahmedabad, and Hyderabad — have been badly affected. Tamil Nadu announced a ‘total lockdown ’ permitting manufacturing of only essential goods. Other states may follow suit. Robots can help with social distancing, ease the burden from state mandates on partial operations, and are, most importantly, immune to the virus and any mutations.
It’s not as if the interest to automate isn’t there. A record $50 billion was invested in robotics companies globally in 2020. As soon as the pandemic hit, leading investment firms like Pegasus Ventures and Lux Capita l announced their intentions to invest more in teams looking to power automation and robotics. Last year, over 50 per cent of CFOs expressed their intent to accelerate automation (PwC Covid-19 CFO Pulse Survey). High-profile leaders like Jeff Bezos and Elon Musk expressed keen interest in developing hyper-automated factories.
The world of manufacturing is begging for more automation. Most tasks require low-skilled labour and are highly repetitive — prime candidates for automation. Globally, almost $15 trillion is spent on manual labour wages for low-skill, repeatable work (McKinsey). In comparison, the amount spent on automation is only $150 billion . The total number of industrial robots used across factories worldwide is only 2.7 million . And while India doubled the number of industrial robots used over the last five years, the total number of operational robots is still just 26,300 . So, manufacturing leaders agree that automation is needed and investments are pouring in. But why don’t we see more automation in manufacturing?
The biggest hurdle to more automation is the lack of adaptability in today’s robots. In a factory, most tasks are ‘Picking, Orienting and Placing’ objects, but these objects often occur in a clutter. These activities are too simple for humans but too complex for robots. For example, robots today cannot take a screw from a bin, orient it at the right angle, and turn it correctly. Screws, nuts, bolts, etc., are called fasteners. A car has about 3,500 fasteners, and a jet plane has almost three million. Imagine the efficiencies if robots could only learn to pick and place objects from clutter!
Robots with advanced machine vision to see, and a ‘brain’ to understand, grasp, and manipulate objects like humans can transform the landscape of industrial automation.
Without adaptability, many robots are too cost-prohibitive. Today, only 20-30 per cent of the upfront cost of automation is for the robot arm itself. The rest 70-80 per cent is to customise the robot arm to perform one specific task. Imagine investing in a washing machine and paying five times the cost to customise for cotton. And next, if you want to run a load of delicates, you will need a team of specialists again. Unfortunately, a manufacturer often has to pay up to five times the cost of the robot for additional equipment, re-calibration, end-of-arm tooling, robot specialists, and quality control tests.
The business case for more robots can only work if the situation is reversed. 70-80 per cent of the upfront costs should be reusable, and 20-30 per cent can be non-reusable. Based on consumer demand and global competition, product life cycles are getting shorter and shorter. And even small design changes can cause significant delays to operations and increase costs. Robot arms need to be product-agnostic, not design-specific. Otherwise, the return on investment or ROI is too low and the entire exercise is frankly, not worth the hassle.
For India to be the lifeblood of the world’s manufacturing, we need to disaster-proof the sector immediately. Intelligent robots that perform object manipulation tasks offer manufacturers greater resilience, higher ROI, and ultimately, the most urgent need of the hour — a breath of fresh air.
(The author is CEO of CynLr)