Mumbai, April : In a notable instance of grassroots innovation, a 17-year-old student from Mumbai has developed a low-cost artificial intelligence system that could improve efficiency in India’s manufacturing sector, particularly among small and medium enterprises.
Kcavyan Agarwal, a student at the Dhirubhai Ambani International School, has designed an AI-powered tool wear prediction device tailored for machine shops. Built at a cost of under ₹500, the system enables real-time monitoring of tool wear in lathe machines, reducing reliance on manual inspection methods that often disrupt production and increase costs.
In many MSME workshops, operators depend on experience or periodic microscopic checks to assess tool condition—approaches that can lead to premature tool replacement or unexpected downtime. Agarwal’s system addresses this gap by providing continuous, real-time insights without interrupting operations.
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The device combines a physics-informed neural network (PINN) with an affordable sensor setup. Using vibration and acoustic data collected through low-cost components, the system estimates tool wear during machining. It is built on an Arduino platform and incorporates inputs from MPU6050 and LM393 sensors.
The model is backed by field data collected during visits to machine shops in Mumbai and Navi Mumbai’s MIDC belt, where Agarwal spent over 30 hours observing operations and gathering machining data. Developed with guidance from a researcher at IIT Bombay, the system integrates key physical variables influencing tool wear into its predictive framework.
Initial validation tests have shown encouraging results, with most readings closely matching actual tool wear levels. Trials also indicated that operators could extend tool life by several hours, leading to improved planning and reduced downtime.
Agarwal is now working towards deploying the system in live industrial settings and is collaborating with engineers at Hindustan Forgings. Future plans include expanding the dataset, refining the model, and seeking validation from established industry bodies.
With its focus on affordability and real-world application, the innovation highlights the potential of accessible AI solutions in advancing Industry 4.0 adoption across India’s MSME sector.
