A method for choosing adapted life cycle assessment indicators as a driver of environmental learning: a French textile case study. Issue 1 (16th February 2020)

• Record Type: Journal Article
• Authors: Reyes, Tatiana; Gouvinhas, Reidson Pereira; Laratte, Bertrand; Chevalier, Bruno
• Is Part Of: AI EDAM. Volume 34:Issue 1(2020)
• Page Start: 68
• Page End: 79
• Publication Date: 2020-02-16
• Subjects: Life cycle assessment, -- knowledge, -- learning, -- choice of LCIA indicators and methods, -- eco-design tools; Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S0890060419000234
• Languages: English
• ISSNs: 0890-0604

Abstract

Abstract: Despite alefforts for a sustainable production system, many companies are still struggling to implement environmental aspects in their daily product development processes. Among the evaluation and improvement methods, life cycle assessment (LCA) is one of the most popular tools to achieve this goal. Up to date, LCA has been applied to many products, services, and industrial systems to evaluate their environmental impact aspects. However, there is a wide range of indicators available to be applied for LCA, and choosing an inappropriate indicator may lead the product designer to achieve wrong and weak results. Therefore, this paper proposes to overcome this difficulty by developing a method that can be used as a knowledge transfer to product designers and LCA practitioners in order to help them to make the most appropriate choice of LCA indicators. This method should have some characteristics, such as (a) to be adaptable to a given context and (b) to be dynamic, scalable, and easy to learn. The purpose of this paper is to present the Evaluation Method for Choosing Indicator (EMCI) developed to facilitate the learning process of LCA methods and to quickly select their most appropriate indicators. To validate the EMCI method, a case study on a French textile industry has been implemented. The focus was to evaluate how LCA indicators and methods were chosen to be integrated into the suitable eco-design LCA tool.