AI powered LCA for process management: a case study in the stone industry

Nowadays, the growing focus on environmental issues has led industries to assess their impact on the planet and develop sustainable solutions. The ornamental stone industry, that has a crucial role in global construction and manufacturing sectors, faces significant environmental challenges related to raw material extraction, processing, transportation, and waste management. This thesis analyzes the ornamental stone sector through the Life Cycle Assessment (LCA) approach, exploiting a combination of primary data from stone industrial partners and secondary data from datasets. The objective is to evaluate the environmental impact of specific production processes and propose strategies to enhance the sector’s sustainability. The analysis starts with an examination of European regulations on sustainability and industrial digitalization, an overview of the stone sector in Italy with a focus on the Veneto region, and a description of the LCA methodology. The case study focuses on a stone processing plant in Veneto, applying LCA to identify the process stages with the highest environmental impact and propose optimization solutions. The results highlight how the integration of digital tools and artificial intelligence can improve the life cycle management of stone, reducing waste and energy consumption. This thesis provides a scientific foundation to support strategic decisions aimed at making the ornamental stone sector more sustainable and aligned with European environmental directives.