Dor Lila, Author at Razor Labs

Case Study: Aftercooler Core Degradation Detected by DataMind AI in Komatsu 930E

By Razor Labs 5 min read SHARE Aftercooler and charge-air system failures in large mining haul trucks reduce engine air density, increase combustion temperatures, and accelerate component wear across multiple engine systems. These failures often develop gradually and can be masked when individual parameters remain within their alert thresholds. DataMind AI continuously monitors intake manifold […]

Boletín Resumen de Razor Labs – Segundo Trimestre 2025

By Razor Labs 5 min read SHARE We’re proud to share Razor Labs‘ highlights from Q2 2025 – a quarter marked by strategic growth, real-world impact, and deeper global engagement. Powered by AI and guided by our mission to advance predictive maintenance, we continue to turn insights into action. From award-winning innovation to new deployments and field […]

Fragmento de Estudio de Caso: Fusión de Sensores Identifica Degradación Mecánica en Ventilador de Sinter Antes de la Falla

By Razor Labs 5 min read SHARE Unexpected sinter fan failures in alloys production can cause major operational downtime and financial losses. To avoid these risks, a leading site implemented DataMind AI™ to monitor critical equipment in real time and flag early signs of mechanical deterioration. In early March 2025, DataMind AI™ detected elevated axial […]

Estudio de caso: Prevención de fallas en el motor de la bomba de lodo mediante detección temprana con DataMind AI™

By Razor Labs 7 min read COMPARTIR Overview Razor Labs DataMind AI™ was monitoring critical rotating equipment at a vanadium mining site, including one of the site’s main slurry pumps. This pump is a critical component in one of the site’s two parallel processing lines. A failure would have forced a shutdown of the entire […]

Estudio de caso: Prevención de fallas en el motor de la bomba de lodo mediante detección temprana con DataMind AI™

By Razor Labs 7 min read COMPARTIR Overview Razor Labs DataMind AI™ was monitoring critical rotating equipment at a vanadium mining site, including one of the site’s main slurry pumps. This pump is a critical component in one of the site’s two parallel processing lines. A failure would have forced a shutdown of the entire […]

Estudio de caso: Prevención de fallas en el motor de la bomba de lodo mediante detección temprana con DataMind AI™

By Razor Labs 7 min read COMPARTIR Overview Razor Labs DataMind AI™ was monitoring critical rotating equipment at a vanadium mining site, including one of the site’s main slurry pumps. This pump is a critical component in one of the site’s two parallel processing lines. A failure would have forced a shutdown of the entire […]

De los Datos a la Acción: Revolucionando las Operaciones Mineras con Mantenimiento Predictivo con IA

Taking a central stage at IMARC 2024: Real-Life Examples of AI Sensor Fusion-Based Predictive Maintenance in Mining By Razor Labs 6 min read SHARE https://www.youtube.com/watch?v=7gBGJZoErbA Michael Zolotov, CTO and co-founder of Razor Labs, recently delivered a keynote at the IMARC 2024 conference that drew a large audience of mining maintenance professionals. Known for his pioneering […]

Estudio de caso: Prevención de fallas en el motor de la bomba de lodo mediante detección temprana con DataMind AI™

By Razor Labs 7 min read COMPARTIR Overview Razor Labs DataMind AI™ was monitoring critical rotating equipment at a vanadium mining site, including one of the site’s main slurry pumps. This pump is a critical component in one of the site’s two parallel processing lines. A failure would have forced a shutdown of the entire […]

Boletín Resumen de Razor Labs – Segundo Trimestre 2025

By Razor Labs 5 min read SHARE We’re proud to share Razor Labs‘ highlights from Q2 2025 – a quarter marked by strategic growth, real-world impact, and deeper global engagement. Powered by AI and guided by our mission to advance predictive maintenance, we continue to turn insights into action. From award-winning innovation to new deployments and field […]