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Unlocking Machine Insights with Apollo Tyres’ AI-Powered Manufacturing Reasoner

Transforming Manufacturing with Generative AI: The Apollo Tyres Journey with Amazon Bedrock


A Collaborative Approach to Digital Transformation

Co-authored by Harsh Vardhan, Global Head, Digital Innovation Hub, Apollo Tyres Ltd.

Apollo Tyres is spearheading a digital transformation journey, leveraging generative AI and advanced data analytics through collaboration with Amazon Web Services to optimize its manufacturing processes. This post explores their innovative solutions and the significant impacts on operational efficiency.

Transforming Manufacturing with AI: Apollo Tyres’ Journey Towards Operational Excellence

This is a joint post co-authored with Harsh Vardhan, Global Head, Digital Innovation Hub, Apollo Tyres Ltd.

Apollo Tyres, a leading global tire manufacturer headquartered in Gurgaon, India, has embarked on an ambitious digital transformation initiative. With a rich product portfolio that spans passenger cars, trucks, agricultural, and specialty tires, Apollo Tyres serves customers in over 100 countries under its brands Apollo and Vredestein. Their recent efforts highlight the integration of advanced digital technologies to enhance operational efficiency and streamline manufacturing processes.

A Bold Digital Transformation

To further its digital journey, Apollo Tyres has collaborated with Amazon Web Services (AWS) to create a centralized data lake. This enables the company to harness data-driven insights using generative AI powered by Amazon Bedrock. One standout innovation from this initiative is the Manufacturing Reasoner, an advanced solution that automates complex, multi-step tasks while seamlessly integrating with existing systems and data sources.

The Challenge: Optimizing Dry Cycle Time

Before deploying the Manufacturing Reasoner, plant engineers conducted manual analyses to identify bottlenecks in the dry cycle time (DCT) of curing presses. This exhaustive process consumed an average of 7 hours per issue, making timely corrective actions nearly impossible. The analysis also required expertise from multiple departments, slowing down the entire process.

Impact of the Solution

Apollo Tyres’ Manufacturing Reasoner not only reduces the DCT root cause analysis (RCA) time from hours to mere minutes but also enhances the quality and speed of decision-making. Using generative AI, plant engineers can interact with machine data naturally, enabling them to retrieve insights and recommendations effectively. Evaluations across various parameters such as machine types and suppliers have seen an impressive 88% reduction in effort, ultimately driving cost savings of approximately 15 million Indian rupees annually in the passenger car radial division.

The Benefits

The Manufacturing Reasoner provides several key benefits:

  • Real-Time Analysis: Continuous monitoring of the dry cycle time enables prompt corrective actions, fostering a proactive approach to manufacturing.

  • Empowerment of Plant Engineers: Staff can now make informed, data-driven decisions, significantly enhancing operational efficiency.

  • Preventative Measures: Real-time triggers help in identifying anomalies for immediate actions, minimizing downtimes.

As Harsh Vardhan points out, “This generative AI solution is about amplifying human intelligence, not replacing it.”

Solution Overview

Apollo Tyres’ innovative Manufacturing Reasoner uses multiple AWS components to ensure efficiency:

  1. Natural Language Interaction: Engineers can ask questions in simple English through a user-friendly UI.

  2. Multi-agent Framework: Various agents work together to understand queries, run analyses, and present insights effectively.

  3. Dynamic Visualization: The solution generates real-time visualizations of data, making it easier for engineers to understand and act on insights.

Lessons Learned

Apollo Tyres’ journey was not without challenges. Initial response times for data processing were slow, averaging over a minute. However, strategic optimizations led to significant improvements. The team’s commitment to iterative refinement—particularly regarding code generation for large datasets—ensured the reliability and performance crucial for accurate insights.

Next Steps

With these successes, Apollo Tyres plans to scale its solution across different manufacturing processes while exploring additional applications of generative AI for operational excellence. The company aims to tackle industry challenges as it moves toward the goal of Industry 5.0—an era characterized by advanced human-machine collaboration.

Conclusion

In conclusion, Apollo Tyres’ digital transformation journey showcases the profound impact of generative AI in manufacturing. By converting raw machine data into actionable insights, they have significantly enhanced decision-making capabilities and operational efficiency. The integration of the Manufacturing Reasoner has not only streamlined operations but is paving the way for intelligent factories of the future.

“By embracing this agentic AI-driven approach, Apollo Tyres is unlocking hidden capacity and redefining operational excellence,” says Harsh Vardhan.

For those interested in exploring the potentials of Amazon Bedrock, our continued journey serves as a testament to the power of technology in shaping the future of manufacturing.


About the authors

  • Harsh Vardhan: Global Head of Digital Innovation at Apollo Tyres, dedicated to fostering AI-first transformation in manufacturing.
  • Gautam Kumar and Deepak Dixit: Solutions Architects at AWS, specializing in innovative cloud solutions and generative AI.

If you have feedback about this post, leave a comment in the comments section!

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