About the Project
Digital Reverse Logistics Twin 5.0 (DigiRL 5.0)
Digital Reverse Logistics Twin 5.0 (DigiRL 5.0) explores how disruptive technologies and methodological integration can enable a human-centric transformation of reverse logistics in Industry 5.0. The project develops a Digital Reverse Logistics Twin, a system-level digital platform that integrates product information with data-driven analytics, optimization, simulation, and smart automation to support decision-making and collaborative operations in reverse logistics systems. The project emphasizes the role of human intelligence in collaboration with technologies, analytics, AI, and automation, enabling more efficient, flexible, and sustainable management of end-of-life products. Through interdisciplinary research combining smart logistics, analytical modeling, simulation, industrial automation, and human-centered design, DigiRL 5.0 aims to advance both theoretical understanding and practical implementation of human-centric digital reverse logistics systems.
- WP1 – Conceptual Framework
Development of the conceptual framework for the Digital Reverse Logistics Twin, with a focus on human-centricity and sustainability in digital reverse logistics transformation. - WP2 – Data-Driven Decision-Support System
Development of an integrated decision-support system combining data analytics, optimization, and simulation to support human-centric planning and management of reverse logistics networks. - WP3 – Human-Centric Flexible Recycling Operations
Design and implementation of a collaborative human–machine recycling system with flexible automation, enabling safe and efficient recycling processes. - WP4 – Responsible Use of Generative AI
Evaluation of the effective and ethical use of generative AI and large language models in developing the digital logistics twins, as well as other smart logistics operations. - WP5 – Project Management and Dissemination
Coordination of project activities and different WPs and dissemination of results to academic, industrial, and societal stakeholders.
The project partners include: the National University of Singapore and Southwest Jiaotong University.
