ALCHIMIA Project: Preliminary Study on the Correlations Between Thermal Analysis and Brake Disc Quality

In the foundry industry, one of the recurring challenges is reducing scrap parts, which pose obstacles in terms of both costs and sustainability. At Fonderia di Torbole, however, innovation is at the core of every activity, and to address these challenges, the ALCHIMIA Project continues with the goal of improving product quality through a more accurate analysis of data from various production processes. 

This advanced system, which utilizes artificial intelligence software, will be able to analyze and correlate a vast amount of data, allowing for an in-depth understanding of the dynamics that influence the quality of brake discs produced by our foundry. The real challenge lies in collecting, analyzing, and transforming this data into useful information to optimize production and reduce waste. 

The Objectives of ALCHIMIA Project at Fonderia di Torbole 

ALCHIMIA is part of a broader context of sustainability and green transition, with its primary objective being the creation of a system that, through the analysis of data from the melting and quality control phases, can predict the final quality of the casting. With the aid of artificial intelligence, the project aims to determine the correlations between melting parameters and brake disc quality, providing real-time decisive results for the continuous improvement of production processes. 

How ALCHIMIA Impacts at Fonderia di Torbole 

The ALCHIMIA system has a significant impact on various stages of the production process. In particular, its use is focused on the melting department, where hourly and final laboratory controls are carried out with greater precision and timeliness. Every hour, an operator performs a chemical analysis to determine the composition of the metal alloy, analyzing the metal from various foundry furnaces. The obtained data is then processed to generate the exact chemical composition using a mass spectrometer. 

At the same time, thermal analysis plays a fundamental role in observing the cooling curve of the metal and its first derivative, which indicates the cooling rate. These parameters are crucial for predicting the final quality of the piece, particularly in identifying potential defects such as porosity or cementite. Additionally, finished casting controls are carried out using natural frequency tests to evaluate the structural quality of the product. 

The Impact of Artificial Intelligence: A Step Towards for the state of the art of quality 

Thanks to the integration of ALCHIMIA, process and product data have been implemented into software capable of continuously monitoring the entire production process. This approach has already led to concrete results, including the introduction of new variables to monitor for quality assessment. 

One of the most promising innovations is the ability to predict the quality of the casting in the early melting stages, using only the chemical and thermal data collected from the inline furnaces. This step represents a true revolution, as it enables the anticipation of potential quality issues and timely interventions, thereby reducing waste and optimizing the production process. 

Conclusions: a revolution for the product quality 

ALCHIMIA Project stands as a clear example of how technology and artificial intelligence can be leveraged to enhance the quality of foundry products, reduce costs, and promote a more sustainable resource management approach. The concrete application of this system at Fonderia di Torbole not only ensures consistently higher quality in brake disc production but also opens new possibilities for the future, making the company more competitive and at the forefront of the global metallurgical industry.