Case Study: US-Based Leading Mining Company achieves 50% reduction in unplanned downtime and $10M savings with Hexaware

Leading Mining Company Increases Operational Efficiency

US-Based Leading Mining Company, a top global producer of copper, gold and silver, faced overwhelming telemetry from 200 sensors per truck across 252 haul trucks (about 10,000 readings/sec and ~10 TB over 3 years). The client needed reclassification and prioritization of ~173K alarm instances from the Mobile Equipment Monitor, reduction of sudden engine failures and optimal oil-replacement intervals, and decreases in haul-truck cycle and idle times. Hexaware was engaged to solve these analytics and operational challenges.

Hexaware extended the customer’s Teradata EDW with a 17-node Hortonworks Data Platform (Hadoop) cluster, adapted BO universes to Hive, unified sensor and enterprise data, and used R and machine‑learning models (Random Forests, Logistic Regression) for prediction and analysis. The solution reclassified alarms into five priority classes—reducing maintenance effort fourfold—cut unplanned downtime by 50% in pilot sites, identified optimal oil-change timing and standardized practices, reduced cycle/idle times, and delivered an estimated USD 10 million in savings via run-rate reductions, CAPEX avoidance and improved productivity.