Quality Management Tool for Remote Factory Operations & Automation is Ready by IIT Kharagpur

IIT Kharagpur and TCS has jointly developed novel Industry 4.0 to maintain effective industrial operations. The benefits of controlled operations have a bigger impact especially in the context of Atma Nirbhar Bharat in delivering quality output at low costs.

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At the time of pandemic when staffing has restrictions due to the hygiene and social distancing norms, IIT Kharagpur has developed a technology for remotely controlled factory operations. It is real-time quality correction technology during industrial production and manufacturing.

IIT Kharagpur and TCS has jointly developed novel Industry 4.0 to maintain effective industrial operations. The benefits of controlled operations have a bigger impact especially in the context of Atma Nirbhar Bharat in delivering quality output at low costs.

The present innovation upgraded the industrial process of friction stir welding to a multi-sensory system of Industry 4.0. It has not only set the course for remotely controlled operations in the Indian industrial sector but has also enabled real-time quality check and correction during the production process.

Emphasizing on the need for such technologies to achieve the ‘Make in India’ goal, the Director Prof. Virendra K Tewari said, “While we are aiming to boost indigenous production and exports, our primary goal should be the quality output with minimum disruptions. Be it consumers in India or abroad, these are the two basic needs our industrial sector, which we must address for procuring orders in large volumes.”

The innovative technology will acquire real-time information about the welding process through multiple sensors and enable online control of weld quality by means of cloud-based communication with the friction stir welding machine.

Prof. Surjya K Pal, Professor in-charge at the Centre of Excellence in Advanced Manufacturing Technology said, “Welding is at the heart of any industrial operations. Our multiple sensor process involves various signal processing and machine learning techniques to predict the ultimate tensile strength of the weld joint is fabricated.”

This technology is connected with a vast experimental knowledge base to conform to a standard system and prediction of the weld joint strength. Any defect identified during the monitoring procedure is corrected in real-time by sending modified parameters to the machine thus ensuring the standardized quality of the process, he added.

According to K Ananth Krishnan, Executive Vice President and Chief Technology Officer, “the Embedded Systems & Robotics, IoT and ICME platform teams from TCS Research and Innovation are working closely with IIT Kharagpur’s CoE towards AI-driven prediction/control of weld strength using a scalable and robust platform. Academic partnerships are an important part of TCS Research and TCS Co Innovation Network (TCS CoIN) in creating real-world solutions with scientific rigour.”

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