Razor Labs’ Post

Razor Labs' CTO, Michael Zolotov on why vibration analysis alone is not enough for a full machine failure coverage: Relying solely on vibration analysis for mining equipment monitoring isn't sufficient to prevent all equipment failures. While it's an essential tool, several critical aspects are often missed, leading to recurring issues. Here’s why: ✅ Slow-Moving Machines: Certain equipment, like mill trunnions in gold and copper mining, operate too slowly for vibration sensors to detect issues effectively. In such cases, oil analysis is more suitable, providing insights into the condition of slow-moving parts. ✅ Material Monitoring: Vibrations don't account for issues with the material being processed. Factors like oversized materials, clay content, or humidity can cause blockages and equipment wear, issues not detectable by vibration analysis alone. Advanced monitoring using cameras can identify these problems by analyzing the material's size, composition, and other characteristics. ✅ Root Cause Analysis: Often, the material itself is the root cause of failures. For instance, oversized ore can lead to crusher blockages, which aren't detected by traditional vibration sensors. DataMind AI™ uses AI sensor fusion, combining data from various sensors, including cameras, to provide a comprehensive view of equipment health and predict potential failures before they occur. ✅ Integrated Monitoring: Effective predictive maintenance requires integrating data from multiple sources—vibration, oil analysis, cameras, and more. This holistic approach, like that offered by DataMind AI™, ensures early detection of issues that single-sensor systems might miss, reducing downtime and maintenance costs. #mining #predictivemaintenance #reliabiltiy #conditionmonitoring #vibrationanalysis #vibrationsensors #assetmanagement #miningtechnology #ai #sensors #sensorfusion

The AI intelligent warning explosion-proof intrinsic safety camera is an intelligent belt management system based on AI video monitoring, analysis, and recognition. The system improves the efficiency of real-time analysis by pre installing artificial intelligence recognition algorithms in the front end of the camera, achieving the goal of rapid on-site identification, analysis, and warning. It provides visual safety production guarantee for the mining belt transportation system. The system has achieved visual stall monitoring, coal stacking monitoring, deviation monitoring, personnel protection monitoring, temperature trend analysis monitoring, and belt bearing displacement monitoring for transportation belts.

Awesome spending some time with Tru-Trac Rollers (Pty) Ltd at Electra Mining Africa today, where the company is introducing a range of innovative conveyor system solutions. A case in point is the Rip Prevent+ system, an advanced monitoring technology that detects and addresses conveyor belt issues early. Dustin Schiller tells me that, using a data-driven model and artificial intelligence (AI), the system can detect anomalies or rip events on any conveyor belt type, including metal cord, pipe and fabric belts. This AI, combined with an innovative algorithm, detects anomalies and rips, generating data and signals that allow customers to stop the conveyor line before significant damage occurs. The system's model computes data 50 times per second and can generate a signal to the Programmable Logic Controller (PLC) within 0.2 seconds, reducing the impact of rip events. Learn more in the Sep-Oct issue of Quarrying Africa! #electramining #conveyorsystems

Have you considered applying AI to your #mining conveyor belts for increased productivity and reduced costs? Our recent article offers a use case where we apply #MachineLearning models for anomaly detection in conveyor belts, providing cost-effective, efficient, and scalable solutions for #PredictiveMaintenance and monitoring. Our SIENTIA™ platform by aignosi can tune tailor-made #AI models for each conveyor belt in minutes, detecting anomalies 30 minutes ahead, preventing unplanned downtime, and increasing productivity. Implementing AI-driven anomaly detection systems can identify issues early, allowing for timely maintenance, extended equipment life, and increased profitability. Don't let poor data quality, technical challenges, and difficulties integrating AI into existing systems hinder your AI initiatives. Discover the potential of AI in mining, and leverage our #SIENTIA™ platform to enhance your operational excellence, sustainability, and safety. Please read the full article on how to scale AI for #AnomalyDetection in conveyor belts and join the mining innovation journey with us: https://lnkd.in/eU7pgX7C #IndustrialAI #MiningInnovation #PredictiveMaintenance #OperationalExcellence #Sustainability #Safety #SIENTIA #aignosi

🌐 Leveraging Data Acquisition & Sensor Monitoring for Engineering Excellence! In the era of digital transformation, the mining industry is harnessing the power of real-time monitoring and advanced sensor technologies to revolutionize safety, efficiency, and sustainability. These innovations are pivotal for adapting to the challenges of complex geographic locations, extreme climates, and the demand for sustainable practices. Through the integration of low-cost sensor technologies, mining activities are being monitored to mitigate socio-environmental impacts, enhance water efficiency, and minimize accident risks, marking a significant leap towards smart mining . Real-time data acquisition and analysis play a critical role in identifying operational inefficiencies and preventing costly breakdowns, thereby promoting equipment longevity. The intelligence derived from this data, through the application of AI and machine learning, enables predictive decision-making and operational optimization. This not only enhances safety measures but also contributes significantly to environmental sustainability efforts. By anticipating problems before they occur, mining operations can optimize resource use, ensure workforce safety, and reduce their environmental footprint, all while improving productivity and cost-effectiveness . As we embrace these technological advancements, the future of mining looks brighter, safer, and more sustainable. The industry's shift towards integrating real-time monitoring, intelligence, and earth observation data signifies a transformative approach to mining operations, setting new standards for operational excellence and environmental stewardship. #EngineeringInnovation #DataAcquisition #SensorMonitoring #FutureOfEngineering"

📢 We are thrilled to be featured in the recent TheMarker AI magazine issue. Last year has been phenomenal for Razor Labs! We've made significant strides in the global mining market, securing key clients and establishing long-term collaborations, entered the energy sector, and are now getting ready to explore additional industries. Behind our recent achievements lies a visionary ambition: to bring cutting-edge technology to the asset-intensive industries. As the demand for minerals surges, Razor Labs' cutting-edge Predictive Maintenance solution, powered by cutting-edge AI Sensor Fusion technology, is set to revolutionize machine maintenance. By reducing machinery downtime, our AI diagnostics mirrors the precision of medical imaging for mining equipment, ensuring more efficient, energy-saving, and environmentally friendly operations. Click on the link in the first comment to read my full interview. #ArtificialIntelligence #MiningIndustry #predictivemaintenance #conditionmonitoring #assetmanagement #reliabilityengineering #maintenance #mining #miningequipment #miningtechnology #miningnews

The mining industry is on the brink of a revolutionary transformation with the integration of Artificial Intelligence (AI). Here’s how AI is reshaping the future of mining: 🔍 Detection of Hazards: AI technologies can detect hazardous gases, toxic dust, and radiation in mines, significantly enhancing safety and reducing risks for workers. 🤖 Autonomous Samplers: AI-driven samplers can collect samples of minerals and toxic materials without the need for human access to dangerous areas, ensuring safer operations. 🔬 AI-based Mineral Sorting: Advanced AI systems can precisely differentiate useful minerals from waste based on various physical, chemical, or mineralogical properties, improving efficiency and reducing waste. ⛏️ Reduction of Hazardous Tasks: By automating perilous tasks such as blasting, transporting, and logistics, AI reduces the risk of accidents and fatalities, eliminating exposure to dangerous gases and dust. 🛠️ Autonomous Support Systems: Cutting-edge research is focused on AI-based systems that can autonomously support mining operations, minimizing the need for human intervention in delicate and high-risk processes. AI is not just a tool but a transformative force that enhances safety, boosts efficiency, and paves the way for a smarter, safer mining industry. 🌟 Reach out to us on: www.minception.com #Mining #exploration #miningindustry #sustainablemining #minception #ResourceExtraction #MiningInnovation #MiningInnovation #AIFuture #SmartMining #SafetyFirst #MiningEfficiency #AutonomousMining #TechInMining #FutureOfMining #MiningSafety #AIRevolution

Soft sensors utilize data that are readily available to give operation insights into the process, which is practically not possible to measure directly. Recently, we have developed and implemented JK CycloPS, which provides real-time measurements of cyclone’s key operational parameters such as cut size, water and mass split, and more importantly, circulating load by particle size. If you are interested in knowing more about our soft sensors and range of other solutions for real-time monitoring and automation, please send me an email. #automation #softsensors #realtimemonitoring

In the dynamic industry of mining, artificial intelligence (AI) emerges as a game-changer, unlocking unparalleled potential across efficiency, safety, and sustainability. The industry's challenges, from dispersed deposits to rising costs, find solutions in AI's data science and machine learning. Examples abound: from precision-enhancing automated drilling to the cost-slashing impact of driverless trucks, AI is revolutionizing the mining landscape. Predictive maintenance ensures equipment issues are nipped in the bud, while smart sensors and cameras bolster security and streamline operations. Responsibly, AI minimizes environmental impact by remotely targeting rich ore deposits, aligning with ESG goals. Excitingly, the mining sector is investing significantly, with firms projected to spend $218 million on AI platforms by 2024¹. Embrace the future with AI, where innovation meets sustainability, driving growth and responsible resource management in mining. Font: 1. GlobalData Marketing Solutions, 2023 www.martin-eng.com.my #MartinEngineering #MartinEngineeringMalaysia #BulkMaterialHandling #ConveyorBelt #Engineering #Safety #Efficiency