Enhancing Manufacturing Efficiency: AI-Driven Optimization in Tire Production
In the article ‘AI for Manufacturing Process Optimization and Improvement’, published in the Industrial magazine Interempresas, AI-PROFICIENT partner Aitor Arnaiz from Tekniker explains the surrogated data-based model developed to optimise the extrusion process in a Continental production line, where changes in recipes often necessitate line stoppages and restarts, resulting in significant time and material losses. Aitor Arnaiz highlights the role of IoT and Big Data in improving production quality and efficiency. He emphasises that while these advancements are beneficial, they require a deep understanding of the processes and the application of AI, Big Data, and Machine Learning.
The AI-PROFICIENT solution design breaks down the initial problem into two distinct sub-problems: first, identifying the precise timing for extrusion, and then proposing optimized setpoints to ensure a stable process. This optimized approach leads to a remarkable level of stability, resulting in significant savings.
This article showcases how AI and data-driven models can effectively address complex manufacturing challenges, particularly in a dynamic production environment like Continental’s tire manufacturing line.