OPTIMIZING EXCAVATOR AVAILABILITY USING LEAN SIX SIGMA AND PREDICTIVE INVENTORY MANAGEMENT: A CASE STUDY OF PC1250 AT SAMARINDA COAL MINE

Abstract

This study investigates the improvement of Physical Availability (PA) in Komatsu PC1250 hydraulic excavators operating at a coal mining site in Samarinda, where PA was initially recorded at 73%, below the customer target of 85%. The main contributors to low PA were unplanned downtime, delayed troubleshooting, and low On-Time In-Full (OTIF) performance in spare parts delivery. To address these challenges, Failure Mode and Effects Analysis (FMEA) was applied to identify dominant failure modes, while the Lean Six Sigma DMAIC framework was used to design targeted process improvements. Predictive inventory management, supported by Vendor Held Stock (VHS), was also integrated to enhance forecasting accuracy, reduce stock-out risks, and shorten lead times. The implementation delivered measurable improvements: PA increased from 73% to 83%, MTTR was reduced from 34 hours to 24 hours (−29%), MTBF extended from 92 hours to 117 hours (+27%), and OTIF performance improved from 69% to 95% (+26 pp). These results confirm that a structured, data-driven improvement framework can significantly enhance equipment reliability and operational resilience. The model provides a scalable approach for similar mining operations and supports PT United Tractors’ commitment to achieving higher efficiency in product support services.