REYES, Tatiana; GOUVINHAS, Reidson Pereira; LARATTE, Bertrand; CHEVALIER, Bruno

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REYES, Tatiana
Centre de Recherches et d'Etudes Interdisciplinaires sur le Développement Durable [CREIDD]

GOUVINHAS, Reidson Pereira
Universidade Federal do Rio Grande do Norte [Natal] [UFRN]

LARATTE, Bertrand

APESA [Pau]

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Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 2019-09-16p. 12

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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 indicatorsand methods were chosen to be integrated into the suitable eco-design LCA tool.< Réduire

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Life cycle assessment

knowledge

learning

choice of LCIA indicators and methods

eco- design tools

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A method for choosing adapted life cycle assessment indicators as a driver of environmental learning: a French textile case study

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