Operador Minero Global. Optimización con Ciencia de Datos para el Rendimiento de la Flota Caterpillar 777.
Optimizamos el rendimiento de una flota de camiones de acarreo Caterpillar 777 analizando la telemetría GPS, los eventos de inactividad y los patrones de combustible. La operación sufría de un tiempo de inactividad excesivo en las estaciones de reabastecimiento y de rutas no óptimas. Mediante el uso de predicciones basadas en ML, corredores de velocidad optimizados y un cambio al reabastecimiento parcial, aumentamos los ciclos de acarreo efectivos en un 3-7 % y redujimos el tiempo de inactividad en 15-25 minutos por evento de reabastecimiento, con cero gastos de capital.
01 —The Impact
The results, up front.
3–7% increase in effective haul cycles 15–25 minutes less downtime per fueling event Annual savings and productivity impact of $2M–$6.2M Achieved entirely via process and analytics — no CAPEX
02 — The Challenge
Where they started.
The operator’s fleet encountered bottlenecks at refueling points and inefficient routing, leading to long idle times and fewer productive hauling cycles. Telemetry data existed but was not utilized to drive operational optimization. We conducted a full analysis of GPS tracks, speed curves, idle events, fuel levels, and historical cycle times. ML models were used to recommend optimal speed corridors, predict cycle time windows, and forecast fuel demand precisely enough to shift away from full-tank fueling. We also introduced high-pressure fueling complexes and developed a DS Advisor tool to assist dispatchers with real-time routing and fueling decisions. The project delivered a step-change in efficiency, all through process excellence and data-backed decisioning — requiring no new CAPEX.
04 — Approach & Methodology
How we got there.
The data revealed that full-tank fueling drastically increased refueling downtime and that trucks often queued unnecessarily. Predictive fuel-demand modeling enabled partial fueling at optimal times, which significantly decreased wait time and increased cycle availability.
Routing adjustments based on recommended speed corridors further improved predictability and reduced cycle-time variance.
05 —In Practice
Project samples.
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