Automation in LCA, reconciliation of inventory data: case study on manufactured products subject to the French RE2020 building regulation to validate the proposed method

Among the different stages of LCA (Life Cycle Assessment), the data reconciliation and modeling phase is identified as the most complex, time-consuming, and costly. Automation of this phase appears necessary today. Our objective is to propose a methodology for automatic data reconciliation by considering all possible reconciliation scenarios. Our approach involves analyzing automation methods from the literature. We propose data reconciliation through semantic analysis and the development of a cluster database (materials and processes) that serves as a bridge between the BoM (Bill of Material) and the environmental database. This proposal is then translated into a coded tool to automate the process. A case study was conducted involving different panels (novices and experts) to compare the choices and assumptions made in modeling an EEE (Electrical and Electronic Equipment) building component, both with and without the approach of selecting a similar material. This case study validates the proposed solution. This paper will present our research aimed at meeting the requirements of the EEE regulation in France by automating data reconciliation. This constitutes a practical and innovative solution for manufacturers while contributing to effective communication about the environmental performance of products.