Digital Twins for Real-time Monitoring and Operation of Coffee Value Chain and Supply Chain
Year: 2024
Type: article
Abstract: There has been significant effort and a growing need to develop innovative and costeffective 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.
Authors: Le, Chi An, Le, Chi Hieu, Nguyen, Van Duy, Zlatov, Nikolay, Le, Tan Hung, Nguyen, Tien Anh, Chu, Anh My, Mahmud, Jamaluddin, Le, Van Dang, Nguyen, Ho Quang, Ramesh, Dharavath, Mengistu, Samueal, Behera, Amar, Packianather, Michael S
Institutions: University of Greenwich, Nha Trang University, Bulgarian Academy of Sciences, Institute of Mechanics, Trường Đại học Khoa học và Công nghệ Hà Nội, Hanoi University of Science and Technology, Le Quy Don Technical University, Universiti Teknologi MARA System, Universiti Teknologi MARA, Agency for Science, Technology and Research, Advanced Remanufacturing & Technology Centre, Indian Institute of Technology Dhanbad, Indian Institute of Technology Kanpur, Cardiff University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4402997966