Indian tyre manufacturer CEAT Ltd is using Amazon Web Services (AWS) to build smart factories, achieve cross-plant monitoring and also enhance customer experience.
The company has reduced the time to market and also the time to deploy new IT infrastructure from two months to 12 hours.
CEAT’s digital and analytics head, Ganesh Bhat, told iTnews Asia that, using AWS, the firm has improved manufacturing efficiencies and created new products, like “intelligent tyres”, much faster.
In addition, the company has also made data-driven decisions in all categories including consumer experience, sales transformation, connected products and smart plants.
Before migrating to AWS, the manufacturer’s on-premises infrastructure could not scale to keep up with the demand for new digital services, Bhat said.
Also, with the previous factory setup lacking aids to provide visibility and insights across plants, the tech team had looked to build “smart” factories with solutions to securely connect and ingest data to a central store from operational data sources like machines and industrial assets, he added.
CEAT embarked on its digital transformation journey with AWS and other partners in 2017 with the aim to build a smart factory, Bhat said.
As a first step to improve agility and accelerate innovation, CEAT implemented a modern SAP S/4HANA enterprise resource planning (ERP) platform on AWS.
For example, by using Amazon Redshift, a cloud data warehouse, and Amazon SageMaker, CEAT was able to develop a solution that automatically recommends which tyres the dealers should order based on history and real-time supply, improving customer experience, he added.
Similarly, for after-sales, the solution can assist in registering warranties, and claims where the customer only needed to click images of purchased tyres and the implemented artificial intelligence/machine learning (AI/ML) solution would identify defects.
Bhat said the company had also introduced other initiatives like a universal chatbot, mobile application and distributed portal to assist a customer “entirely” from lead generation to service through analytics.
Intelligent tyres
Bhat explained that with data analytic insights, CEAT developed “intelligent tyres” with built-in telemetry sensors connected to the cloud to record tyre data like pressure, and temperature, to detect leaks and predict tyre failure.
“This insight minimises fleet operators’ vehicle downtime and prevents road accidents,” he said.
With the Amazon QuickSight service, CEAT could easily set up real-time analytics dashboards using factory and enterprise data.
To digitise its manufacturing processes, which require 250 raw materials, CEAT connected production machines, like curing presses, to the cloud and built a data lake on Amazon Simple Storage Service (Amazon S3).
This lake securely stores structured and unstructured data from across its operations; improving the view of factory operations and helping line managers closely monitor the factory’s functioning.
For example, CEAT uses Amazon SageMaker for building, training, and deploying machine learning models quickly in the cloud and at the edge to predict leaks in tyre-curing presses. This prediction decreases tyre waste by reducing factory line stoppages and improving tyre quality.
Smart factory
Bhat said the firm envisioned a smart factory that is connected to continuously manage traditional data along with new sensor-based data either in real-time or batch and collaborate across departments.
CEAT had a wide range of feature requirements like reliability, predictability, anomaly identification and resolution, automated restocking and replenishment, early identification of supplier quality, flexibility in scheduling changeovers, implementation of product changes and support to configurable factory layouts and equipment.
To overcome these challenges, “we used AWS industrial edge architecture enabling operational technology (OT) and information technology (IT) integration,” Bhat added.
AWS IoT services, Greengrass and SiteWise provide secure industrial connectivity, data ingestion and transformation.
“We created a data platform to run industrial applications and machine learning models in factories for low latency and production critical use cases,” he said.
Bhat added that this ecosystem was helping to understand industrial data and to perform gateway management and remote deployment from the central AWS console across all plants.
Speaking on future plans, Bhat said CEAT is now in the process of implementing the industry 4.0 use cases which entail the use of analytics, IoT and point-to-point solutions for niche areas.
