Caso de estudio: DataMind AI™ identifica daños en los dientes del engranaje de un molino de bolas y garantiza la continuidad operativa
By Razor Labs 5 min read SHARE DataMind AI™ was installed at an iron ore mining site in Australia to monitor critical equipment, including the Ball Mill. The site had historically faced recurring gearbox failures, leading to costly unplanned downtime and safety risks. Shortly after installation, DataMind AI™ flagged the Ball Mill gearbox with an “Alarm” […]
Razor Labs en el Consorcio Trust.AI: Pioneros en la Investigación sobre Toma de Decisiones con IA
Predictive maintenance is equipment maintenance that is based on the ability to predict equipment failures, by leveraging real-time data from various sensors and applying AI algorithms.
Estudio de Caso: DataMind AI™ Detecta Problemas Ocultos de Bombeo y Previene Costosos Paros de Operación
By Razor Labs 5 min read SHARE DataMind AI™ was installed at a coal mining site in Africa to monitor critical equipment, including slurry pumps. The site had historically relied on manual periodic vibration testing. Shortly after installation, DataMind AI™ flagged a pump with an “Alarm” status, raising concerns since manual vibration testing had not […]
Cómo la IA y los Flujos de Trabajo por Voz Están Transformando la Minería en Mining Indaba 2025
By Razor Labs 4 min read SHARE https://youtu.be/vkBX3Ia-K6I How AI & Voice Workflows Are Transforming Mining At Mining Indaba 2025, Michael Zolotov, CTO of Razor Labs, and Joseph Starwood, Worldwide Mining Industry Leader at Microsoft, discussed how AI-driven predictive maintenance is reshaping the mining industry. Companies are seeking smarter ways to improve efficiency, enhance safety, […]
Serie de Expertos de Razor Labs: La Innovación Detrás de la Fusión de Sensores de IA, David Refael, VP de I+D
By Razor Labs 2 min read SHARE https://youtu.be/01rk5DoS4Vo Razor Labs Expert Series is episodes of interviews in which the company’s specialists share insights into their unique experience in the fields of AI, Digital Transformation, Industry 4.0, product management, business, innovation, and market disruption. Episode 3: The Innovation Behind AI Sensor Fusion, David Refael, VP R&D […]
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 […]
Razor Labs y Microsoft Discuten el Futuro del Mantenimiento Minero y la IA en MinExpo 2024
By Razor Labs 4 min read SHARE https://www.youtube.com/watch?v=7aCezBLTlMU The Future of Mining: Leveraging AI Sensor Fusion and Automation for Predictive Maintenance As the mining industry faces increasing pressure to improve operational efficiency, reduce costs, and address looming labor shortages, advanced technologies are stepping in to bridge the gap. Automation, AI-driven solutions, and sensor fusion are […]
Boletín Resumen de Razor Labs Q2 2024
By Razor Labs 5 min read SHARE Welcome to Razor Labs‘ Q2 2024 Newsletter! As our implementation expand across the globe, so does the impact of our solution. Navigating the ever-evolving mining and industrial sector, where efficiency, safety, and sustainability are crucial, our team remains dedicated to revolutionizing maintenance practices and empowering mining companies to unlock their full […]
Transformando la Confiabilidad del Equipo Minero con Mantenimiento Predictivo
Predictive maintenance is equipment maintenance that is based on the ability to predict equipment failures, by leveraging real-time data from various sensors and applying AI algorithms.
Mantenimiento predictivo y el auge de la IA en la minería
We look at how AI is reshaping predictive maintenance in the mining industry, helping cut costs and streamline efficiencies as the sector responds to increased production pressures.
