Data-Driven Production Planning and Supply Chain Management: A Brief Review

PASCAL, GUADALUPE; TORNILLO, JULIAN; ROSSIT, DANIEL ALEJANDRO; REDCHUK, ANDRÉS

Congreso; 2023 4th International Conference on Data Analytics for Business and Industry (ICDABI); 2023

Nowadays, the industry is constantly evolving. Digital transformation has become an enormously important catalyst, profoundly reshaping companies’ operations management, particularly in production planning and supply chain management. Underlined by the advent of Industry 4.0 and Industry 5.0, it requires a strategic orchestration of technologies, including the Industrial Internet of Things (IIoT), Big Data (BD), Digital Manufacturing (DM), and Artificial Intelligence (AI), among others. In this sense, the role of data-based methodologies is crucial since they facilitate precision and efficiency within the processes. Decision support tools that leverage data-driven technologies empower industries to tackle complex challenges, such as manufacturing a wide range of products within tight lead times, recognizing forecast patterns, specific predictive maintenance activities, and optimizing production planning and supply chain management. In this context, this work aims to recognize and characterize the primary research in data-driven production planning and supply chain management that has taken place in recent years. The proposed methodology adopts a Systematic Literature Review (SLR). Preliminary findings indicate a sustained growth in research interest beginning in 2017, with Germany, the United States, and China emerging as leaders. International collaborations underscore the global nature of this field of research while demonstrating a relative regional centrality and a vacancy in Latin America. Besides, the most predominant emerging topics are recognized. The discussions of this research refer to the evolution of the scientific activity of these disciplines in the regional context and provide an overview of the evolution of research on data-driven production planning and supply chain management.