Optimizing Excavator Physical Availability Using Lean Six Sigma and Predictive Inventory Management: A Case Study of PC1250 at Samarinda Coal Mine - Satria Adi Prabowo; Gembong Baskoro; rer. nat. Filiana Santoso (Fakultas Teknik Universitas Islam Makassar, 2026)
The coal mining industry faces critical challenges due to the low Physical Availability (PA) of heavy equipment, leading to excessive downtime costs and unmet production targets. This study investigates the optimization of Komatsu PC1250 excavator availability at a Samarinda coal mining site by applying the Lean Six Sigma DMAIC framework combined with Predictive Inventory Management. Baseline data indicated PA at only 73%, below the 85% target, with an average Mean Time To Repair (MTTR) of 34 hours and spare parts On-Time In-Full (OTIF) of 78%. Using analytical tools such as Failure Mode and Effects Analysis (FMEA), Fishbone diagrams, 5-Why analysis, and a predictive inventory system through two-bin Kanban and Vendor Held Stock (VHS), this study successfully reduced MTTR to ≤24 hours, improved Mean Time Between Failures (MTBF) by 18%, and increased OTIF for critical parts to 95%. As a result, PC1250 availability rose significantly to 83%, approaching the corporate target. The findings confirm that integrating Lean Six Sigma with predictive inventory systems provides practical solutions for mining contractors to enhance productivity while reducing operational costs.