| Abstract Scope |
This study implements Lean 4.0, or digital Lean, by integrating Data Science into the Bauxite and Alumina Business System (BABS) tools at Hydro’s Paragominas Mining. Two critical BABS tools, central to strategic information, were enhanced using Machine Learning (ML) and Natural Language Processing (NLP). The A3 methodology guided the process, covering problem analysis, goal setting, solution development, action planning, and monitoring. Key tools included MS Power Automate, SQL, Power BI, R programming, and a Big Data framework, resulting in a Microsoft 365-integrated application. This provided real-time insights for decision-making. An unsupervised ML algorithm with NLP and cluster analysis evaluated user interactions, linking tool usage to improved company performance. Correlation analyses confirmed that increased tool usage by client areas positively impacted key performance indicators, demonstrating the effectiveness of digital Lean in enhancing operational efficiency and strategic decision-making at Paragominas Mining. |