Title: An artificial intelligence approach to assessment and guidance for circular transition

Authors: Júlio Dias do Prado; Jonny Carlos da Silva; Lucila Maria de Souza Campos; Marina Ilka Baumer-Cardoso

Addresses: Department of Mechanical Engineering, UFSC – Federal University of Santa Catarina, 1850 Lauro Linhares St, Florianópolis, Santa Catarina, 88070-260, Brazil ' Department of Mechanical Engineering, UFSC – Federal University of Santa Catarina, 1850 Lauro Linhares St, Florianópolis, Santa Catarina, 88070-260, Brazil ' Department of Production Engineering, UFSC – Federal University of Santa Catarina, 1850 Lauro Linhares St, Florianópolis, Santa Catarina, 88070-260, Brazil ' Department of Production Engineering, UFSC – Federal University of Santa Catarina, 1850 Lauro Linhares St, Florianópolis, Santa Catarina, 88070-260, Brazil

Abstract: Manufacturing companies face several challenges to sustainable production. Companies and governments face complex challenges beyond climate change, for example, the scarcity of resources, difficulty accessing raw materials, pandemic scenarios, or international conflicts. By adopting circular practices, companies can operate in a closed production cycle, contributing to an economic balance and greater efficiency in the use of natural resources. The use of artificial intelligence (AI) can help companies in the challenges of finding a more sustainable production. Knowledge-based systems (KBS), a subarea of AI, are systems that use human knowledge to solve specific problems in a given domain that companies in both public and private companies can use. The objective of this article is to present the development of a KBS prototype, which assists in the assessment and guidance for the transition to a circular economy. The proposed KBS focuses on a key industrial field which is the metal-mechanical sector.

Keywords: artificial intelligence; circular economy; overall circularity effectiveness; metal-mechanical sector; knowledge-based systems; KBS.

DOI: 10.1504/PIE.2025.148044

Progress in Industrial Ecology, An International Journal, 2025 Vol.18 No.1, pp.1 - 23

Received: 07 Jun 2024
Accepted: 01 Oct 2024
Published online: 15 Aug 2025 *

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