Growing significance of AI in augmenting human capabilities in manufacturing operations. Manas Agrawal writes a guest column.
For decades, manufacturing businesses have been involved in digitizing their processes and connecting their plants to improve visibility. While this has helped in improving productivity, it has not helped manufacturers keep up the pace with the fast-changing landscape.
In many manufacturing companies, machine and plant operators still rely on using manual adjust settings and parameters to ensure improved operational efficiencies. If this does not change quickly, manufacturers will be surrounded by challenges to effectively compete in a global scenario that has completely metamorphosed since the pandemic.
As the world tries to limp back to normalcy, manufacturers will look at making their operations more resilient by adopting technologies that can help them automate their processes and analyse vast volumes of information from the plant shop floor to detect any issue in production processes. Thanks to AI, these processes will be refined on a continuous basis as AI learns and unlearns to improve overall efficiency.
A McKinsey report states that in advanced manufacturing processes, AI can improve forecasting accuracy by a factor of 10 to 20 percent. McKinsey says that this can translate into a potential 5% reduction in inventory costs and a revenue increase of 2-3%.
AI is also being used by manufacturers to proactively reduce downtime through predictive maintenance. Manufacturers can also utilise AI to forecast demand and help make judicious inventory management decisions, thus preventing overstocking and understocking. AI can help manufacturers better optimize their supply chains through accurate inventory tracking, production, and management.
Research firm, Gartner, says that the COVID-19 pandemic has amplified the need for supply chain organizations to use Artificial Intelligence (AI) and advanced analytics to dig through the vast amounts of data they generate to understand what is happening in their business. The research firm says that by 2024, 50% of supply chain organizations will invest in applications that support Artificial Intelligence and advanced analytics capabilities. AI can also be used for predicting the most efficient delivery route by combining different variables such as weather, traffic reports and vehicle or driver performance.
AI’s role in Manufacturing 5.0
While AI’s role in Industry 4.0 is already well known, in the future, AI will be used to augment the capability of humans. For example, there may be certain manufacturing operations that require the domain expertise of humans who can then input the probable causes of failure into AI models, and further improve efficiencies. While Industry 4.0 was mostly about automation, Industry 5.0 is about using the combined power of humans and machines to work together for favourable outcomes.
Industry 5.0 will use the creative and intuitive power of humans to create better and more efficient products. For example, a tractor manufacturer can co-create a customized tractor by allowing the customer to customize the product and directing the manufacturer to produce the tractor.
This deep collaboration allows manufacturers to create customized and highly personalized tractors. This can be extended to every possible product – from cars to washing machines, laptops, or even mobile phones. A case in point is Ferrari which allows its customers to configure every last detail of their car to be tailored according to their personal preferences.
While human intervention is required for their creative and cognitive abilities, AI can suggest an aesthetic design or the right model that helps the customer to co-create the product easily.
AI-powered collaborative Cobots are also an example of Manufacturing 5.0. Universal Robots, a manufacturer of AI-powered robots has deployed more than 50,000 collaborative robots in different production environments around the world.
Blue Star, one of India’s most popular brands, uses the company’s Cobots to handle its complex task of copper tube expansion. Using AI, the centre of each copper tube is calculated, and the coordinates are then passed on to the cobot to guide it to a correct position. The cobot has managed to eliminate stress as the operator no longer has to track and measure the coordinates of each tube. This is just one example of the power of collaborative robots, and the huge potential of Manufacturing 5.0.
There are an infinite number of possibilities that can be explored, as Cobots can be reprogrammed for different applications, as the need arises. These Cobots can also be operated by frontline workers and more complex activities can be done by human beings.
In conclusion, AI’s role in Manufacturing 5.0 will be huge, as it will enable a powerful combination of using the consistency, speed, and scalability powers of robots with the skill and creative ability of humans.
(Manas Agrawal is the CEO and Co-founder of Affine)
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