DIGITAL TWINS & INDUSTRY 5.0 ON FOOD MANAGEMENT (Book Chapter)

Abstract

Digital twins have the potential to transform agri food production systems and supply chains, addressing critical challenges such as greenhouse gas emissions, food waste, and malnutrition1. These virtual representations of physical entities exist in silicon, continuously updating based on real-time sensor data. By simulating physical systems, digital twins can optimize behaviour and advise control strategies for their physical counterparts. For instance, they can help estimate and predict food quality, enabling stakeholders to make dynamic decisions about supply chain logistics and storage conditions to reduce spoilage and wastage. Additionally, digital twins support end-to-end visibility and traceability, enhancing supply chain management by overseeing complex moving parts and building nonlinear supply chain models. The function of digital twins (DT) in the context of industry 5.0 is thoroughly explored in academics. Industry 5.0’s digital twin models minimize operational hazards, increase productivity for human users, and lessen wear and tear on real-world equipment. This study attempts to investigate the effects of the use of virtual twins. The way businesses conduct business is changing as a result of the rapid rise in the adoption of digital twin technology. In the past few years, digital twins have been extensively used in many important commercial applications, and it is expected that the equipment will expand to other businesses, scenarios of use, and applications. The purpose of this study is to evaluate the literature and look into how Industry 5.0 and Digital Twins can make intelligent automation easier in a variety of industries.