A REVIEW OF LITERATURE ON CURRENT TRENDS AND ADVANCED TECHNOLOGIES IN DIGITAL TWINS IN THE FOOD INDUSTRY

Abstract

This paper presents a literature review on the current trends of advanced digital twin technologies in the food industry.The increasing demand for fresher and better quality food products has prompted researchers to search for solutions in this field. Apart from increasing production volumes, it is also important to improve the efficiency of logistics processes to reduce waste. An optimized food supply chain not only reduces the final cost to consumers, but also increases producer profits, reduces environmental impact and delivers fresher and healthier food. Collecting and analyzing data on traceable products and the needs of those involved in the process can improve supply chain performance, providing valuable information for managers. Technology solutions such as the Internet of Things (IoT), artificial intelligence (AI), digital twin (DT), and distributed ledger technology (DLT) have been proposed to monitor products and analyze data to help in management decision making. However, the integration of these technologies, especially DT, intelligent models and DLT, has not yet been sufficiently explored. In recent years, the digital twin (DT) paradigm, evolving in the context of Industry 4.0, has attracted increasing attention from both researchers and professionals due to its dynamic capabilities. Most research in this area remains theoretical and focuses on hypothetical analysis, while there are significantly fewer empirical studies of real-world application cases. Despite this, DT is actively used to analyze and improve performance in food processing companies (FPCs), although its impact on business strategies is still poorly understood.