AI in the Production Line

AI in the Production Line

The digital transformation of manufacturing

One of the primary disruptive effects of the COVID-19 pandemic was the rapid integration of Artificial Intelligence into almost every aspect of industry, including healthcare, education, finance and life sciences among several others. This can be regarded as an acceleration in an already-existing process, with several previous surveys already noting a rapid expansion of AI adoption in India.

The Growth of Manufacturing AI

Continuing a trend that had already been put into motion in the previous two years, the industry which has (probably) benefited the most from AI adoption in 2020 is the manufacturing sector. In fact, according to the IDC 2019 Cognition AI Adoption Survey, almost 37% of AI spending in India was already being carried out by the manufacturing and BFSI verticals. Improvements in process quality, optimisation of supply chains and improved flexibility have all been instrumental in further pushing the numbers towards the right direction over the course of the last few months.

Internet-of-Things (IoT) platforms are expected to rise from $745 billion and hit the $1 trillion- mark India by 2022, thereby facilitating the production and analysis of very large volumes of data using machine learning. According to Entrepreneur, “the manufacturing industry spawns around 1800 petabytes of data every year, which is higher than various industries such as finance, retail, etc.”

“The ongoing COVID-19 pandemic has opened doors to newer opportunities for the country to be self-reliant. Today, with initiatives such as ‘Make in India’ and ‘Atmanirbhar Bharat’, the country is gearing towards becoming a manufacturing hub.”

However, in order to compete in a market economy where manufacturing powerhouses such as China and the United States are already at the forefront of technological development, it is crucial for the manufacturing sector in India ‘to adopt novel technologies such as AI and to develop efficient and systematic processes’ that can facilitate competition on a global scale.

A major prevailing problem that the manufacturing sector will have to repair, however, is improper inventory management. “The imposition of lockdown during the COVID-19 epidemic caused mayhem in the inventory management and supply chain of various commodities in the market. Transformation to digital solutions and next-generation technology to manage inventory stock is obligatory to meet the growing demands of consumers in the volatile environment.”

The ‘How?’

AI has found rampant usage in manufacturing across a plethora of sectors. It assists manufacturing companies by reducing the risk of recall for products by using AI solutions like machine vision in order to monitor even minor defects in production: thereby even mitigating reputational risk. This aspect has proven to be especially beneficial in the highly stringent pharmaceutical industry: to trace and track products from the production line to the end patient to ensure all regulations are being adhered to. In fact, according to Forbes, automated quality testing carried out by using machine learning can almost double existing detection rates. This is especially important in quality control in industries such as semiconductor manufacturing, where McKinsey estimates put the cost of testing and failures as high as 30%.

AI has also helped in leading automobile firms such as Maserati and Volvo, where real-time data and virtual simulations have been provided as inputs to AI to reduce design time and increase operational efficiency. Self-driving cars using AI is another major development in the automobile manufacturing sector, which is expected to see much growth in the coming years.

A 2018 survey by PWC found that only 9% of companies in manufacturing were using AI for operational decision-making. By 2026, estimates place this number to rise to almost 83%, with AI worth almost $17 billion. According to an Entrepreneur report: “Companies in the coming two-three years will capitalize fully on the hybrid and connected smart systems for optimization of production, costs, inventory or inspection, to predict sales and prices or perform predictive maintenance. This doesn’t mean that automation technologies like AI will outplace the human workforce.

“Instead, these novel technologies have only created more jobs. There was an era when computers were considered a threat to the workforce but with passing time these technological advancements have benefited humankind and business in general, making upskilling a necessity and not a luxury. In fact, as per the World Economic Forum, half of the workers in the manufacturing field would require some degree of reskilling and upskilling in the next five years as AI will potentially automate 30 per cent of jobs. Hence it will become imperative for employers to invest heavily in the upskilling of their workforce to make them future-ready.”

© 2024 Praxis. All rights reserved. | Privacy Policy
   Contact Us