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Energy-Efficient Digital Twins for Circular Economy Implementation

Year: 2025

Type: article

Abstract: As industries accelerate their transition toward sustainability, integrating energy efficiency into Circular Economy (CE) strategies becomes a key priority. Digital Twins (DTs) are virtual counterparts of physical systems that enable real-time monitoring, simulation, and optimization of energy performance across product life cycles. This paper proposes a structured framework that integrates DT technology, Artificial Intelligence (AI), and predictive analytics to enhance energy efficiency and circularity in industrial operations. The proposed model enables real-time data collection, simulation, and decision-making for sustainable production and end-of-life management. A simulated manufacturing process demonstrates that DT-based optimization can achieve energy reductions of approximately 10–12% while improving recycling and reuse metrics. The framework aligns with ISO 50001 standards and the EU Circular Economy Action Plan, providing a practical path for scaling digital sustainability tools in manufacturing.

Source: Springer Link (Chiba Institute of Technology)

DOI: 10.1051/e3sconf/202568000085/pdf

Authors: Abderrahman Mansouri, Idriss Bennis, Ali Siadat, Fatiha Akef

Institutions: Arts et Métiers, Laboratoire de Conception Fabrication Commande, École Normale Supérieure de l'Enseignement Technique de Mohammedia, Université Hassan II Mohammedia, University of Hassan II Casablanca

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production, Affordable and clean energy, Climate action

Open Access status: green

OpenAlex ID: W7116724206

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