Manufacturing can be significantly improved as a result of using AI
Published on : Tuesday 13-02-2024
Professor Satyandra K Gupta, Smith International Professorship, Aerospace and Mechanical Engineering, USA.
AI has captured the popular imagination globally. Speaking specifically about manufacturing, what is the potential AI offers to industry?
AI or artificial intelligence is expected to play a big role in various facets of manufacturing. People are excited about it in the context of operational efficiency. You know where AI could improve your operational efficiency quite a bit, people are also excited about how we manage the entire maintenance pipeline, how the entire equipment gets managed, and AI can play a huge role in that context. A lot of things which are difficult to automate can now be automated once you bring in AI. People are excited about training people in a much faster way using AI technologies, and next generation user interfaces which are enabled by AI. So there are lots of different ways in which overall manufacturing can be significantly improved as a result of using AI.
In manufacturing India is trying to catch up with China and the gap is too wide. Can AI help India to bridge this gap?
China’s early history of gaining dominance in the field of manufacturing was via people willing to work in manufacturing. But now that’s not necessarily the required route. Robots and 3D printing can actually eliminate the need for people to do really tedious and economically challenging things. At the same time, once you start deploying robots and 3D printers, the quality and consistency that you get out of the process is world class, if you can manage your operations well. So this starts opening up new opportunities for places like India where you don’t have to now kind of catch up with other countries in developing the labour pool and you know basically getting people to do tasks which they absolutely do not wish to do. It opens up new opportunities.
A recent PWC survey has some interesting insights – 38% of the companies that participated in the survey admitted they do not have a digital strategy but among manufacturing companies the trend of adopting analytics and AI is 54%. Is there a sort of a contradiction here?
It makes sense; when people talk about digital, a lot of people are doing digital without using AI. Some people are doing digital plus AI. Some manufacturers are still struggling to do that, but on the other hand, as the survey indicates, the majority has got onto this idea about using digital technology and digitising things because that’s a precursor to using AI. So that’s a very good sign and I think the momentum is building towards it; people want to do digital and therefore they want to embrace AI more.
There exists a huge digital divide today. While large companies and MNCs have the most modern plants, the SMEs are struggling in the absence of resources. How can they benefit?
True. You know, people at all scale or size of companies can definitely benefit from deploying modern digital technology, better sensors, and therefore can be more sustainable. Issue comes down to resources because when you are trying to modernise your machines, you have to put sensors in it, collect the data and you have to make decisions, so on and so forth. So as long as the resources can be marshaled, everyone can actually go ahead and do this.
Another aspect is manufacturing versus skills, especially when manufacturing is no longer a high profit industry. Can the subsidies given to manufacturing be better utilised for funding education and acquisition of skills?
I think both things are going to be important. Because people consume manufactured goods on a daily basis, right? So it’s not like people are not consuming manufactured goods – so one has to kind of have to do both things at the same time. You have to really make sure that you can do as much manufacturing as possible. So that you are meeting your own needs and you don’t have to import manufactured goods. At the same time, you have to make sure that you have the workforce and the talent pipeline which can feed your manufacturing operations.
Another dilemma is the increasing use of automation and robotics in a country like India with a huge manpower pool. How will this impact the employment scene as we automate progressively?
So, I mean if you look at it right now, I am not upto speed on the India numbers but I know the US numbers. Currently the US uses about 2.85 robots – you can approximate to 3 robots – per 100 workers in the manufacturing sector. India’s robot density is much less. The world No.1 is Korea, using about 10 robots per 100 workers, and that still means that there are a large number of people working in manufacturing. It’s just that, the physical work which requires you to basically do things consistently by force, that’s where you want to move humans away from it and let them play a role in decision making, let them optimise the process, let them do some other meaningful part of manufacturing as opposed to doing the very challenging physical work. So if you take out all the physically challenging tasks, there are still lots of useful things for humans to do. So there is a lot of opportunity for people to be employed in the manufacturing sector. So I don’t think the issue of using AI and robots more in manufacturing reduces the number of human positions available. I mean it grows because once you become a world class economy and you are creating more products, it actually creates more jobs for people. So in a way by using robots and automation, you are creating more jobs for your people.
The world learnt some hard lessons during Covid, especially the supply chain disruption. How would things look in future as the US resorts to onshoring and self reliance?
Yes, so obviously there are two aspects to it. I mean one aspect is the US itself wants to do as much onshoring as they can because they don’t want to rely on any single source where if supply chain disruption were to happen, it’s going to cause havoc for them. So the strategy is to make use of smart manufacturing, AI, automation, robotics, etc. As a result then you can go ahead and produce in the US. So that’s the strategy that’s being used. Now obviously as other countries like India start offering more manufactured products, that also deals the whole thing for the world, because now you are not relying on a single source. You have viable alternatives, and once you have viable alternatives, it simply means that you can take a portfolio approach and purchase from one party, or you can purchase from some other party. Should a disruption occur in future, hopefully, you still kind of adjust and do well.
AI also comes with certain risks and even Sam Altman, for example, is for increased government supervision, so where do we stand today?
So again, let's dissect it now to different layers of the risk, where the risks are coming from and how each of the risks is going to be managed. So, when we take a look at cybersecurity risks, clearly there are several bodies which are making standards, there are several things for which certification being issued, whether your system is so vulnerable to cybersecurity.
Then there are issues related to when you have these AI systems, were they extensively tested or not? Did we basically have the right way of certifying things, are there data biases, which will then create some other, you know, challenges or create defective products and somebody has been blamed for it and so on, so forth. So that space, there is realization, there has to be some regulation, because again, without knowing to what standards we have tested things, just rolling out an AI based product, without really rigorously testing it, as per some standard would be a bad idea. So I think the conversations have started. And basically, I think regulation is going to come in that space.
Dr Satyandra K Gupta holds Smith International Professorship in the Aerospace and Mechanical Engineering Department and the Department of Computer Science in the Viterbi School of Engineering at the University of Southern California. He is also the founding director of the Center for Advanced Manufacturing at the University of Southern California. Prior to joining the University of Southern California, he was a Professor in the Department of Mechanical Engineering and the Institute for Systems Research at the University of Maryland, College Park.
https://viterbi.usc.edu/directory/faculty/Gupta/Satyandra
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