Product environmental impact prediction model based on Life Cycle Assessment integrated with Artificial Intelligence

• Grant number: 22/15134-1
• Support Opportunities: Scholarships in Brazil - Master
• Start date: May 01, 2023
• End date: April 30, 2025
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Diogo Aparecido Lopes Silva
• Grantee: João Victor Encide Salla
• Host Institution: Centro de Ciências em Gestão e Tecnologia (CCGT). Universidade Federal de São Carlos (UFSCAR). Campus de Sorocaba. Sorocaba , SP, Brazil

Abstract

Globalization has allowed greater integration of nations, with the internet being one of the pillars of such progress and, more recently, with emphasis on Artificial Intelligence (AI). Furthermore, the importance of technology and the man-machine relationship can be highlighted in the search for increased ef iciency, quality and reliability, whether for the improvement of production processes, for the increase of communication speed or even to support the business decision making. In line with this speed of global transformation, the importance of aligning and promoting production and consumption habits that have a lower environmental impact emerges. All this, with the aim of reducing the speed of degradation that the environment has been suf ering since the First Industrial Revolution. To this end, it is essential that companies use Life Cycle Thinking in their research and development stages, since it defines the materials that will be used, the obsolescence linked to the product and its components, the target audience, the processes and other characteristics with intrinsic influence on the potential impact of a product in its life cycle. Thus, the importance of tools that are capable of predicting, with a certain level of reliability and speed, the potential impacts of goods and services arises, helping stakeholders in making more sustainable decisions even in the development phase of their products. In this context, the objective of this research project is to develop a prediction model based on Machine Learning that, based on Life Cycle Assessment (LCA) results, is capable of predicting potential environmental impacts. The expected result is the development of a model capable of helping decision makers, so that they can be taken more quickly and assertively, and that take into account the importance of environmental sustainability.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SALLA, JOAO VICTOR ENCIDE; DE ALMEIDA, TIAGO AGOSTINHO; SILVA, DIOGO APARECIDO LOPES. Integrating machine learning with life cycle assessment: a comprehensive review and guide for predicting environmental impacts. INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT, v. N/A, p. 23-pg., 2025-02-21. (22/15134-1)