Mithun NagabhairavaSenior manager, data scienceRockwell Automation
USA
In a landscape marked by significant labor shortages, hundreds of material compositions, and complexities inherent in tire manufacturing, maintaining consistent tire quality poses a formidable challenge due to variations in raw materials, production conditions, and rheological properties that affect material flow and behavior. However, advancements in artificial intelligence and machine learning (AI/ML) combined with well-established bedrock of optimal control theory can help address these challenges effectively. During this session, we'll delve into real-world examples showcasing how AI/ML technologies are transforming tire manufacturing, resulting in enhanced quality and efficiency. By leveraging advanced closed-loop optimization and machine vision capabilities, manufacturers optimize various stages of production, from mixing to final inspection.
What the audience will learn
- Progressing towards Autonomous Tire manufacturing through AI integration.
- Utilizing AI from mixing to ensuring consistent weight measurements during extrusion to minimizing out-of-tolerance events at tire building machines and optimizing vulcanization properties during curing.
- Best practices for the responsible deployment of AI capabilities in tire manufacturing, ensuring alignment with industry standards and ethical considerations.