This project examines the critical role of asset management and reliability engineering in optimizing physical assets at a Brazilian bauxite mining company. It shows how these disciplines raise availability, cut costs, and improve safety. The work explores event historians, machine learning (ML), and artificial intelligence (AI), benchmarking global ROI. Industry 4.0 tools for mobile assets like trucks and tractors are applied through a tailored approach, combining proven methods with innovative solutions. A pioneering application uses an event historian with ML and AI to predict failures, optimize maintenance, and improve effectiveness, reducing costs. Case studies demonstrate gains in performance, efficiency, safety, and training, while challenges and future integration are also addressed.