Funded by the European Union – Next Generation EU
The production of Michelin tires is a complex process that requires a rigorous selection of materials, constant monitoring of production phases, and effective storage management to ensure high quality standards. Currently, significant challenges arise related to the need to reduce diagnostic times, minimize the use of solvents, and optimize warehouse inventory management.
The project adopted an approach in line with Industry 4.0 principles, focusing on increasing sensor technology and automation through the use of advanced technologies and artificial intelligence algorithms. Activities focused on four main technological areas. The first is quality control of talc application, implemented through an artificial vision system based on Edge AI, capable of detecting anomalies in talc distribution and preventing production defects. The second area involved solvent tracking, with the integration of ATEX sensors for continuous monitoring of octane consumption, to improve environmental sustainability and energy efficiency. The third area involved predictive diagnostics, utilizing acoustic analysis of machinery to predict potential failures and thus reduce downtime. Finally, a semi-automatic inventory management system was developed, based on the use of drones assisted by machine learning algorithms, allowing for more precise and rapid detection of warehouse status.
The introduction of these technologies has the potential to generate significant benefits both operationally and economically. The adoption of artificial intelligence and computer vision has contributed to a reduction in waste and an improvement in product quality. Solvent consumption has been reduced by 2%, with an estimated economic saving of 181,000 euros per year. Additionally, production efficiency has increased, along with operational safety, thanks to the integration of automated and intelligent systems. Inventory management has also been optimized, with greater precision and reduced risk for operators. The project has also promoted the enhancement of internal digital skills and contributed to a reduction in environmental emissions, improving the overall sustainability of the process.
Funded by the European Union – Next Generation EU
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