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AI can usher in era of sustainable manufacturing

Neeraj Kanwar explores how AI can make manufacturing in tyres and the wider automotive industry more sustainable and efficient

It is being feted as the future of everything from medical research to journalism. But artificial intelligence (AI) could have a bigger, more positive impact on automotive manufacturing than most other sectors—particularly around sustainability.

As the COVID-19 pandemic abated and economic activity started to return to normal, global emissions rose 6.4% to a new high in 2022, according to the IMF. Manufacturing was one of the leading culprits. Consulting firm McKinsey believes that around 60% of a vehicle’s emissions will come from material production by 2040—up from 20% for a gasoline car, now— unless the industry makes serious changes. However, AI can create the urgent sustainability impetus that is needed.

Tyre manufacturing is very energy intensive. But using machine learning and AI in compound mixing, for example, can reduce energy consumption by 5% or more. AI analysis and data sharing can identify the main sources of carbon emissions and allow firms to address them.

Tyre production
Tyre manufacturing is very energy intensive

Apollo Tyres recently set up digital innovation hubs in Glasgow and Hyderabad, which are working on ways AI can help reduce the amount of scrap materials produced in manufacturing. They are also focusing on AI solutions to reduce production bottlenecks and to facilitate preventative maintenance. AI has already substantially improved efficiency in Apollo’s Hungarian plant and will play a key role in achieving carbon neutrality aims by 2050.

The future of AI in tyre production could include uses such as identifying and testing more sustainable raw materials, and predicting changes in companies’ environment, including water-use patterns and customer demand. Manufacturers will be able to adjust their operations, accordingly, to be more efficient.

Similar uses for AI can be found in wider automotive manufacturing. Audi already uses AI for things like checking pressed parts to detect cracks. BMW has more than 200 AI uses in production. This includes quality assurance, where preventing faulty parts going out to consumers reduces avoidable repairs and waste‚—whether that’s making a replacement part or even just having to drive a car back to a dealer.

AI has improved efficiency in Apollo’s Hungarian plant, shown here

Manufacturers can make increasing use of AI to analyse the efficiency of production processes and to monitor equipment so that maintenance is timely, extending equipment’s life. Firms can optimise their supply chains, using AI data on things like inventory levels, to make sure the right items are available in the right quantities, when needed—again cutting waste. AI-assisted robots can carry out tasks such as welding and painting more accurately, reducing the amount of paint or energy used.

The automobile industry can spend more than US$1bn on product development, with no guarantee that the public will like their new car or truck. AI could help design vehicles based on analysis of what looks and features have appealed to customers in the past, saving the need to make several prototypes and jet around the world doing customer research. Realtime feedback from cars could provide insights into how people drive in the real world, allowing firms to optimise production processes.

The potential for AI is something of a blank page, at present. But it is certain that if the automotive industry is to change from one of the more problematic sectors for the planet to one that is helping it to thrive, AI has a vital part to play.

The opinions expressed here are those of the author and do not necessarily reflect the positions of Automotive World Ltd.

Neeraj Kanwar is Vice Chairman and Managing Director at Apollo Tyres Ltd

The Automotive World Comment column is open to automotive industry decision makers and influencers. If you would like to contribute a Comment article, please contact

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