Digital twins for real-time monitoring and operation of coffee value chain and supply chain

Le, Chi An, Le, Chi Hieu, Nguyen, Van Duy, Zlatov, Nikolay, Le, Tan Hung, Nguyen, Tien Anh, Chu, Anh, Mahmud, Jamaluddin, Le, Van Dang, Nguyen, Ho Quang, Ramesh, Dharavath, Mengistu, Samueal, Behera, Amar and Packianather, Michael S. ORCID: https://orcid.org/0000-0002-9436-8206 2024. Digital twins for real-time monitoring and operation of coffee value chain and supply chain. International Journal of Mechatronics and Applied Mechanics I7 , pp. 114-124. 10.17683/ijomam/issue17.13

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Abstract

There has been significant effort and a growing need to develop innovative and cost-effective solutions for real-time monitoring and operation of value chains and supply chains, especially to enhance the predictability and optimisation of complex production systems for a better adaptation to disruptions and market fluctuations as well as improved sustainability. This is particularly important when taking into account the impacts and emerging advancements of smart agriculture, smart manufacturing, Digital Twins, and Industry 5.0, where data-driven solutions and AI-enabled decision-making play an important role for improving real-time monitoring, quality control and management, and operational efficiency. This study presents a conceptual framework for integrating Digital Twins into a smart agriculture platform, focusing on the real-time monitoring and operation of the coffee value chain and supply chain, to demonstrate the potential of Digital Twins in advancing smart agriculture and digital supply chains.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
ISSN:	2559-4397
Date of First Compliant Deposit:	20 January 2025
Date of Acceptance:	4 September 2024
Last Modified:	21 Jan 2025 12:30
URI:	https://orca.cardiff.ac.uk/id/eprint/174607

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