Case Study: Real-time conveyor and material monitoring. DataMind AI uncovers crusher liner issues and prevents downstream equipment failures.

conveyor belt monitoring

By Razor Labs 5 min read SHARE Crusher liners are essential to the effective operation of any crusher. Wear of the crusher liners and inaccuracies in the crusher gap calibration can result in oversized ore going unnoticed, potentially causing harm to downstream equipment, like the grinding circuit.  Early detection of these potential issues allows for […]

Case Study: Breakthrough in Critical Ball Mill Failure Prediction with DataMind AI

In our latest article, we delve into the remarkable advancements achieved through the utilization of DataMind AI in predictive maintenance. Learn how our recent case study titled “Breakthrough in Critical Ball Mill Failure Prediction with DataMind AI” revolutionized the industry’s approach to anticipating and preventing critical failures in ball mills. Discover the fascinating insights and outcomes of this groundbreaking study.

Case Study: Leading gold miner reduces unscheduled crusher downtime with DataMind AI

gold miner crusher case study

By Razor Labs 5 min read Download PDF SHARE The challenge The customer faced significant reliability challenges related to the site’s crushing circuit. The site experienced an average annual downtime of 250 hours. The financial impact of this unscheduled downtime and the associated lost throughput was estimated at $22,000/hour. The recurring failures resulted in increased […]