Resumen
Tailings Storage Facilities (TSFs) are critical structures due to their construction volume and storage capacity. A robust design, supported by rigorous quality control during construction and adequate operation and monitoring, contributes to reducing the risks associated with the structural performance of dams. In this context, the objective of this research was to implement a data-driven quality control system based on geotechnical test data that enables efficient data processing and interactive dashboard visualization to strengthen decision-making related to the reliability of geotechnical and structural performance during the construction phase. The methodology comprises four components: (i) data extraction, transformation, and loading (ETL) from the testing process; (ii) data analysis and quality control; (iii) visualization; and (iv) application to a case study. The system was implemented during the construction of the Tundayme tailings storage facility dam at the Mirador mine, integrating data from in-place field density tests using the water replacement method, grain-size distribution analysis, moisture content, and shear strength of cohesive soils. As a result, 26,500 tests were processed between August 2021 and June 2025, significantly reducing processing time compared to traditional spreadsheet-based workflows. Challenges were identified related to initial investments in technological infrastructure and staff training; nevertheless, the benefits obtained through the implementation of this methodology outweigh the required investment. This approach represents a significant advancement toward the digitalization of quality control processes in civil engineering.
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Derechos de autor 2026 Bryan Alexis Muela Llanga, César Alfredo Vásquez Ramírez, Jorge Estuardo Carrasco Avendaño, Anahi Elizabeth Ordoñez Pardo, Estanislao Luis Lojano Sozoranga, Jean Dario Pardo Rodriguez
