Visualization of logistics processes with generative artificial intelligence

Abstract

The article presents the results of research on the application of visualization technologies in logistics and supply chain management. The relevance of the work is due to the wide use of visualization methods in logistics and supply chains, which will simplify and accelerate the perception of information flow, providing end-to-end transparency of the chain and the ability to respond quickly to changes in the business environment by providing analytical information in real time. The importance of choosing the right visualization method to prevent loss of valuable information is emphasized. Interactive visualizations increase the speed of decision-making and simplify data analysis. Modern approaches to supply chain management, for example, Supply Chain Control Tower (SCCT), are based on interactive online forms of visualization, which allows users to monitor supplies in real time, identify vulnerabilities in the chain and promptly respond to emerging threats. The integration of artificial intelligence (AI) and predictive analytics into visualization systems contributes to supply chain visibility and leads to optimization of logistics processes. In the empirical part of the study, the authors demonstrate the potential of generative AI for automated data visualization in logistics. It is shown that AI can be effectively used to create block diagrams of logistics processes, intelligence maps, Gantt charts, ER- and UML-diagrams. Special attention is paid to automatization of visualization development using Mermaid library and their text descriptions. Examples of automated generation of visualizations are given. The results of the study confirm the hypothesis that the introduction of AI and interactive visualizations in logistics simplifies the perception of complex information and helps to improve the efficiency of supply chain management.