Apollo Tyres increases productivity by 9% with IoT technology

London - Apollo Tyres is seeing major gains under a new digital strategy designed to transform its manufacturing processes, according to a case study published recently by Amazon Web Services (AWS).

With seven standalone manufacturing plants in Asia and Europe, the Indian-based tire maker faced limited insight into the performance of its equipment, explained the AWS report issued in May.

Apollo’s machines were equipped with SCADA systems, which collect data on production capacity and other metrics. 

However, this data was siloed, offering a window into the performance of individual machines only, with no basis for comparison between machines or plants.

This limited visibility was particularly concerning in the case of Apollo’s tire rubber mixers, which are highly capital-intensive - costing about $24 million each, including related infrastructure - as well as labour- and energy-intensive. 

The Indian group, therefore, decided to work with AWS partner Deloitte to implement an IoT solution for the connection of its production equipment to a “data lake.” 

Deloitte joined the project to leverage its expertise in building secure, scalable IoT solutions to develop the solution architecture with AWS using various AWS services. 

These included AWS IoT SiteWise, a managed service for collecting and analyzing data from industrial equipment, running on AWS IoT Greengrass, a cloud service for building, deploying, and managing device software at the edge. 

The capabilities enabled the input and processing of a very large volume of raw data packet streams from Apollo’s equipment into an AWS ‘data lake’.

“With the help of Deloitte, we could shine a light and show our teams how the data could help them improve,” said Shibu George, global head, advanced manufacturing at Apollo Tyres.

The complete solution now consists of a smart manufacturing platform with a centralised dashboard, according to AWS. 

To test the proof of concept, Apollo started with its mixers, feeding data from the mixers into the AWS ‘data lake’, while Amazon Redshift enabled data visualisation on the dashboard, presenting ‘near real-time’ views of equipment metrics.

“When we started streaming data to AWS, we could compare the performance within the plant, and across plants. That was a unique opportunity,” commented George.

With seamless access to mixer data, Apollo could identify performance discrepancies and take corrective actions and - with deeper analytics - was able to improve productivity by 9%. 

The higher productivity from Apollo’s mixers also reduced its energy usage by 3%, a considerable saving given that a single mixer has an energy load of about 10 megawatts. 

Reducing CO2 emissions in this energy load by just 3% is equivalent to cutting emissions from 4,000 vehicles traveling for an entire year, AWS further pointed out.

Apollo then explored doing more with its data using artificial intelligence and machine learning, such as predicting compound properties and testing process improvements. 

It also started streaming data from other equipment, including its curing presses and tire-building machines: ultimately realising a 50% reduction in idle-time on curing presses.

With more projects in the works, Apollo sees “virtually limitless potential from its ability to continue unlocking value from its machine data,” concluded AWS.