Tata Technologies’ use of AI/ML reduced power consumption by 18% on shopfloor

The integration of Artificial Intelligence (AI) and Machine Learning (ML) models in vehicle shop floors has revolutionised manufacturing processes.

By Radhika Dave calendar 30 Sep 2023 Views icon13376 Views Share - Share to Facebook Share to Twitter Share to LinkedIn Share to Whatsapp
Tata Technologies’ use of AI/ML reduced power consumption by 18% on shopfloor

Tata Technologies is using artificial intelligence and machine learning to make its manufacturing processes more robust for its clients. The company is consistently using new technologies to reduce downtime and curtail pollution as well. Yogesh Deo, Senior VP and Delivery Head, ER&D (Engineering Research and Development), Tata Technologies explains how this has been achieved. 

"Essentially, we studied the entire related process data for a year, and with the use of AI/ML models, we were able to reduce power consumption by 18 percent, there was an improvement in the process quality and a reduction in fuel consumption by another 10 percent and chemical consumption reduction by another 8 percent,” Deo told Autocar Professional.

Further assessing the importance of using AI, Deo explained how they have been able to identify anomalies to reduce downtime on the shopfloor. Taking the case of the paint shop blower, he said that if one of them goes down, it results in the entire process getting halted, and the repairs take anywhere from 7-8 hours to get it running at an optimal state.

“You can call it in like an anomaly detection just before the failure or actual shutdown. So that means we are not even waiting for the actual shutdown or failure to happen, but the moment when we are able to identify the anomaly. Then we are able to understand it and then we can take the corrective action there and there itself,” he added.

He also explained how for tooling, artificial intelligence was used to predict tooling failure in the case of dye design. “Here what we have done in the case of dye design is that we have gone through the historical operational data and prepared a model, which you can compare with the current operational data and then you can predict whether the dye will perform to its optimal position or it may fail. So we were able to correlate the operational data and failure cases and thereby we are able to determine the remaining useful life of the dye.

The company is "putting a lot of effort and investment into building a Centre of Excellence for AI technology," he said without divulging more information at the moment.

RELATED ARTICLES
Apollo Tyres' APMEA President Satish Sharma to retire

auther Autocar Pro News Desk calendar14 May 2024

Satish Sharma is the president of Apollo Tyres Asia Pacific, Middle East, and Africa division.

Apollo Tyres' FY24 net profit up 65%; Q4 profit down 14% YoY

auther Autocar Pro News Desk calendar14 May 2024

The tyre maker’s consolidated net profit for the full financial year came in at Rs 1,722 crore, while its profit for the...

Tata Motors sees recovery in small commercial vehicles after bottoming out

auther Autocar Pro News Desk calendar14 May 2024

"The transformation in (SCV) pickup is underway, and we should start seeing results as we go ahead," said Girish Wagh.