Predictive Maintenance: Bridging the Data Gap in Global Mining

About this episode

In this episode, Rob Tyson interviews Charlie Forrest about predictive maintenance in the mining industry and the challenges of utilizing data effectively.

In this episode, we chat with Charlie Forrest, CEO of Dingo, an award-winning Enterprise Predictive Maintenance Software solution for the Mining industry, that helps reduce major component failures, improve the reliability of assets and safely boost production while decreasing maintenance costs In this episode, we dig into what’s really holding maintenance teams back, from fragmented OEM systems and underused data to the challenge of turning early warnings into actual decisions on the ground. We also explore what Charlie is seeing across different operations, where AI is genuinely starting to move the needle, and what the best-run sites are doing differently when it comes to reliability If you care about getting beyond dashboards and into real operational impact, this is a conversation worth paying attention to. KEY TAKEAWAYS Many mining operations are inundated with data and dashboards but lack the time or tools to translate that information into actionable maintenance decisions. Effective predictive maintenance requires combining fluid analysis, telemetry data, and visual inspections to build a comprehensive picture of asset health. Successful sites like Newmont integrate…

People in this episode

Host: Rob Tyson

Guest: Charlie Forrest

Topics covered

• predictive maintenance
• mining industry
• data analysis
• AI in operations
• asset reliability
• maintenance strategies

Keywords

• predictive maintenance
• mining
• data
• AI
• asset health
• maintenance costs
• reliability

Mentioned in this episode

Organizations: Dingo, Newmont

Products: Enterprise Predictive Maintenance Software

Places: global

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