Why India’s Manufacturing Sector Needs

India’s manufacturing segment can’t continue to follow their traditional, Industry 3.0 based processes anymore. Digitization of data is a must followed by identifying the right AI solution to act on it

The Good News

India’s manufacturing sector has been steadily growing thanks to growing Foreign Direct Investments, Government of India’s initiatives like Make in India, reduction of Income Tax for companies with up to Rs 250 crore turnover, among others. According to IBEF (India Brand Equity Foundation), the Government of India’s objective is to increase the manufacturing sector’s contribution to 25% of the country’s GDP by 2022 and also create 100 million new jobs in the process. This dream run can only continue if the manufacturing sector also starts embracing next- gen technologies like AI (Artificial Intelligence), to combat its existing hurdles. Unfortunately, India’s manufacturing sector still has a long way to go in AI adoption as compared to other sectors. Only a small percentage of companies have actually deployed AI, while a majority either have their plans mostly on paper, or don’t have any plans at all.

The good news however is, that AI can have a significant impacton India’s manufacturing sector and in fact, there’s a strong need for it, according to a recent CyberMedia Research (CMR) survey of large manufacturers. The main thing is to understand the key challenges and then identify the right AI solution that fits the need.

The Way Forward

One common challenge most manufacturers face is to get the right data from their plant’s machinery to feed into an AI system. Machinery is typically a capital-intensive investment, so unless you’re setting up a greenfield manufacturing plant, chances are that most of your machinery would be many decades old and would therefore lack sensors and network interfaces to send data over the network to a common application. Being able to add such interfaces and sensors so that the data can be digitised is therefore the first step to an AI journey.

The next step is to be able to do the integration between plant machinery and an AI system. Currently, according to a CMR survey, the manufacturing sector feels that there’s a lack of solutions to do this, and it’s even more challenging to choose the right AI vendor from the available ones.

Another point to understand is that one size doesn’t fit all when it comes to AI. The solution has to be devised keeping in mind every organisation’s specific pain points. So start by identifying the key hurdles unique to your organisation before identifying AI based solutions to overcome them. What are required here are efforts on both sides. Manufacturers should start small and then grow as they taste success. Vendors need to create more awareness about their solutions at a sub-vertical level. Everybody for instance, understands how AI can help manufacturers, but how does it help say a textile manufacturer is very different from how it benefitsauto- components manufacturers. Use cases at a sub-vertical level are therefore missing, which is something that vendors need to work on, by possibly identifying similar global ones.

Rising raw material costs, declining margins and stiff competition are some other common challenges that every manufacturer faces. On top of that, customers now demand greater customisation with reduced lead times. Being able to control costs, improving supply chain efficiency and enhance production efficiency is therefore a constant endeavor in manufacturing. AI can play a key role here as well. What’s required is to identify the right use case and build an RoI model around AI for it. A lot of plant machinery for some manufacturers for instance can be very costly to cold-start if it shuts down. If an AI solution could predict its failure well in advance, then the cost of shutdown could be enough to cover the cost of the solution. It’s best therefore to identify how AI can help your business.

The bottomline is that India’s manufacturing segment can’t continue to follow their traditional, Industry 3.0 based processes anymore. Digitisation of data is a must followed by identifying the right AI solution to act on it. The government is also supporting AI adoption by bringing out an AI policy, conducting workshops on AI for MSMEs, etc.

What’s required is for the manufacturers to take cognizance and start moving forward.

While the onus will be on the individual initiative to keep upskilling oneself, even enterprises and the government will need to intervene and strategise on how to enable an AI-inclusive world