Case Study: Leading Coal Mining Company reduces unanticipated in-field failures with GE Digital Data Science

Mining Company Uses Data Science To Minimize Unanticipated, In-Field Failures

Leading Coal Mining Company, operating around the clock with data from 200 mines and a fleet that includes 50 Caterpillar trucks (valued at about $5M each), was suffering major production losses from unanticipated in-field failures. Although root-cause signals existed in their asset utilization and work management data, the customer lacked the tools and expertise to extract actionable insights, so they engaged GE Digital's Data Science team.

GE Digital applied text-mining techniques to identify the top 10 failure modes, generated component-level survival distributions, aggregated mean time between failures (MTBF) estimates, and predicted remaining useful life (RUL). Based on those findings GE Digital recommended inter-inspection time changes and fleet best practices; the customer implemented these actions to meaningfully reduce unplanned failures and optimize maintenance operations across its 200-mine footprint and 50-truck fleet.