case Studies

Case Study

Endpoint MP2 Pilot Saves >$10M: Early Fault Detection Prevents Major Mining Failures

This case study details a four-month pilot program where GreaseBoss tested its Endpoint MP2 device on mining excavators and ancillary equipment 1 .

  • Prevent major equipment failures and save over $10 million in downtime and repair costs.
  • Detect critical lube system faults, like pump electrical issues, significantly faster than OEM monitoring systems.
  • Identify hidden problems such as mistuned autolube systems leading to uneven greasing and incorrect timer settings causing over-greasing.
  • Gain system-wide insights by indirectly detecting failures (like bypassing injectors) on components not directly monitored.  
Case Study

Eliminating Costly Mining Sizer Bearing Failures with Precision Lubrication

  • Eliminate costly grease-related bearing failures and associated production losses.
  • Achieve exceptional ROI with $60m in forecasted annual savings from a $50k investment.
  • Ensure precise lubrication with real-time data comparing planned versus actual grease volumes.
  • Proactively detect equipment issues like failing autolube pumps before they cause major damage.  
Case Study

ELIMINATING EXCAVATOR PIN & BUSH FAILURES

A Tier 1 Australian coal mine was experiencing regular excavator pin and bush failures, costing up to $10 million AUD in downtime plus significant repair costs, due to a lack of visibility into actual grease application. GreaseBoss’s Critical Point Monitoring system provided this crucial data, quickly identifying issues like bypassing injectors and incorrect grease volumes, enabling early intervention.  

  • Prevent catastrophic excavator pin and bush failures and associated multi-million dollar downtime losses.  
  • Gain essential visibility into actual grease volumes delivered to critical excavator lubrication points.  
  • Identify lubrication system anomalies and injector faults far earlier than standard equipment monitoring allows.  
  • Reduce expensive repair costs and minimise equipment downtime through proactive, data-driven maintenance.