Modern Mining
Condition Monitoring | Environmental Monitoring | Quality and Safety Control
Data analytics and control features
Deploy standalone condition monitoring sensors, or ingest existing data to analyse temperature, vibration, pressure, and acoustic noise, to monitor wear, imbalances and other degradation of machine or process performance.
Monitoring tank levels for capacity and filling/emptying events
Volumetric flow data to capture emptying events with high accuracy
High-resolution heat map of dust and noise over a geographic area
Object detection to identify and track objects, such as machinery, vehicles and personnel
Real-time monitoring of dust and noise levels against predefined safety and regulatory thresholds
Impact analysis evaluates the effectiveness of dust suppression and noise reduction measures.
Additional features
Reporting
What does it achieve?
Reduced Downtime
Minimises unexpected equipment failures, ensuring continuous operations.
Cost Savings
Reduces maintenance costs by preventing catastrophic equipment breakdowns.
Waste Reduction
By identifying and correcting inefficiencies, AI Vision technology helps reduce waste and optimise resource use.
Increased Equipment Lifespan
Regular, predictive maintenance extends the life of mining equipment.
Improved Worker Health and Safety
Reduces the risk of respiratory and hearing issues among workers by managing dust and noise levels.
Regulation Compliance
Ensures adherence to environmental regulations, avoiding fines and legal issues.
Sustainable Practices
Proactive environmental monitoring supports sustainable mining practices, enhancing the company’s reputation and community relations.
Consistent Product Quality
Automated quality control ensures that only high-quality ore is processed, improving overall product quality and customer satisfaction.
Utilise Machine Learning and AI
Predictive Maintenance of Haul Trucks
Machine learning models analyse data from haul trucks such as engine temperature, oil pressure and vibration patterns. The models predict when components like engines or transmissions are likely to fail, enabling timely maintenance interventions.
Noise Reduction Recommendations
AI provides suggestions for noise reduction, such as modifying equipment operation times or installing sound barriers.
Predictive Dust Management
AI models predict high dust concentration events, triggering dust suppression systems such as water sprays or mist cannons.
Hazard Detection
Vision AI identifies potential hazards in real-time, such as unauthorised personnel in restricted areas or malfunctioning equipment.
Safety Compliance
AI systems monitor worker behaviour to ensure compliance with safety protocols, reducing the risk of accidents.
Quality Control
Vision AI systems inspect ore quality during extraction and processing, ensuring that only high-quality material is processed further.
Anomaly Detection
Use algorithms like Principal Component Analysis (PCA) or Autoencoders to detect abnormal behaviour in equipment.
Customer Case Study
In the fast-paced world of meat processing, accuracy and efficiency are paramount. When a leading meat processing company faced challenges with their label verification process, they turned to CapitalAI for an innovative solution. This success story showcases how our cutting-edge NexVision technology transformed their operations, setting a new standard in the industry.
Use Cases
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