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Lookup NU author(s): Kwabena Adu-DuoduORCiD, Stanly Wilson PalathingalORCiD, Yinhao Li, Talea Huraysi, Dr Masoud Barati, Dr Ellis SolaimanORCiD, Professor Raj Ranjan, Dr Tejal Shah
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Efficient management of end-of-life (EoL) products is critical for advancing circularity in supply chains, particularly within the construction industry where EoL strategies are hindered by heterogenous lifecycle data and data silos. Current tools like Environmental Product Declarations (EPDs) and Digital Product Passports (DPPs) are limited by their dependency on seamless data integration and interoperability which remain significant challenges. To address these, we present the Circular Construction Product Ontology (CCPO), an applied framework designed to overcome semantic and data heterogeneity challenges in EoL decision-making for construction products. CCPO standardises vocabulary and facilitates data integration across supply chain stakeholders enabling lifecycle assessments (LCA) and robust decision-making. By aggregating disparate data into a unified product provenance, CCPO enables automated EoL recommendations through customisable SWRL rules aligned with European standards and stakeholder-specific circularity SLAs, demonstrating its scalability and integration capabilities. The adopted circular product scenario depicts CCPO's application while competency question evaluations show its superior performance in generating accurate EoL suggestions highlighting its potential to greatly improve decision-making in circular supply chains and its applicability in real-world construction environments.
Author(s): Adu-Duodu K, Wilson S, Li Y, Oladimeji A, Huraysi T, Barati M, Perera C, Solaiman E, Rana O, Ranjan R, Shah T
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 40th ACM/SIGAPP Symposium On Applied Computing (SAC 2025)
Year of Conference: 2025
Online publication date: 14/05/2025
Acceptance date: 21/11/2024
Date deposited: 19/12/2024
Publisher: ACM
URL: https://doi.org/10.1145/3672608.3707870
DOI: 10.1145/3672608.3707870
