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Artificial Intelligence and Machine Learning in Mining, Energy and Resources
Artificial Intelligence and Machine Learning are transforming the mining and energy sectors by enhancing yield, speeding up production, and improving workflow and operational efficiency. Their adoption has notably improved safety by enhancing risk management and safety procedures, facilitating real-time monitoring, and enabling predictive analytics to preemptively address hazards, aligning with the industry’s goal of achieving zero harm.
Rad Anandakumar is a leading expert in data analytics, machine learning, and AI, with a career spanning more than 2 decades. As an AI + Data Technology Strategist, he has led digital transformations and AI-driven business solutions, working with cutting-edge technologies like Generative AI, IoT, and predictive analytics.
Predict and Prevent OH&S Incidents Using Artificial Intelligence and Machine Learning
Monitor
Monitor Real-time IoT and Machine Vision-based alerts (including personal protective equipment, hazards, and mobile equipment risk) to ensure safety compliance. Use Digital Twins for real-time visualisation and scenario modeling. Leverage AI in mining to enhance predictive capabilities and improve safety standards.
Predict
Predict OH&S incidents by creating forward-looking machine learning-based ‘Dynamic Employee Risk Profiles’ to calculate employee’s chances of being involved in an incident on any upcoming day.
Intervene and Prevent
Prevent incidents by retraining, proactively removing employees from potentially dangerous situations, and sending live compliance alerts to employees to immediately eliminate dangerous working conditions. Explore how AI Consulting Group’s advanced AI safety solutions are revolutionizing workplace safety through predictive analytics and real-time monitoring.
Real Time + Sensor Based IoT Monitoring
Noise, Vibration, Movement, Lighting, Hydration
Hydration, Fatigue, Inattention
Temperature, Machine Speed, RPM, Torque, Coolant Temperature
Chemical Detection, Air Quality, C02
Real-time data on Recent Hours Worked, Overtime/Sick Leave, Role Risk Rating, Years of Experience
Machine Vision Based Monitoring
Monitor proper use of safety equipment
- PPE (hard hats, high visibility vests, eye protection)
- Hazardous Material Security (locks, unauthorised access, appropriate safety equipment)
- Dust, Liquid Spills, Trip Hazards
- Proximity Detection, Location Awareness
- Poor Mobile Equipment Practices
Understand complex video events in real-time
- Traffic flow and people movements
- Weather events, Accidents, incidents, and threats
- Tracking, Inspections and defect reduction
- Environmental assessments, Drone footage assessment, including techniques for how to estimate crowd size from aerial images, which can be especially valuable in large-scale event monitoring or emergency response planning.
Optimise Operations & Plant:
We can expedite the delivery of your outcomes using IP and accelerators.
Optimise Throughput and Smart Preventative Maintenance
Artificial Intelligence (AI), ML, Machine Vision, and Data Science-based mining circuit optimisation, using real-world physics simulators, deep learning (ML), and gaming engines to understand and monitor mining circuit inputs, settings, and materials to optimise throughput. These advanced systems often leverage data mining in AI to uncover patterns and insights from vast operational datasets, driving smarter, faster decisions in mining environments. Sensors can also be deployed to monitor asset health and alert operators for conditions that typically preceded downtime events in the past. Similar projects generate ROIs greater than 900% or $90m annually in some cases.
Location Awareness
IOT-based Location Awareness and Analytics to understand team locations, asset utilisation, and interactions. This results in the optimisation of plant, equipment, and people (including cost reductions, time-saving by minimising proximity for next likely use, scheduled cleaning, and maintenance).
Asset Safety
Predict catastrophic equipment failure that could lead to injury or fatality by understanding causes of failure, the likelihood of failure, and predict failure events. Identify defective equipment using machine vision and IoT and determine safe asset use via statistical analysis and optimise asset safety. Use Critical Control Monitoring to identify asset and process failures in advance.
Risk Culture, Safety Culture, Engagement & Psychological Wellbeing Surveys
Various surveys across mining to identify areas of risk or concern based on questions around Risk Culture, Safety Culture/Compliance, Engagement and Phycological Health. Results facilitate drilling to problem departments, locations and sited to focus training and remediation activates and maximise training/remediation outcomes.
Automated Site Assessments
Machine Vision to generate and deliver automated building and site progress data and safety insights. The project involves using robots, drones, and other autonomous equipment to monitor sites to minimise human movement/risk and maximise reporting accuracy.
Mining and Resources Specialisation
We’ve collectively delivered exceptional value/ROI in Mining and Resources:
Dr. Joe Walsh
Physics, PHD, Dip. Management, Dip. QA; Over 50 International Presentations, Over 100 Peer Reviewed Research Papers;
Head of Data Science and Data Engineering
Kris Hampel
Eng (Hons) Major in Mining Engineering; Various mining roles including Drill & Blast Engineer (Downer EDI), Engineering Consultant (MEC Mining)
Project Lead and Technical Consultant
Rad Anandakumar
Comm, MBA, GAICD; Various mining projects (South 32, Newcrest, FMG, MMG, St Barbara, Evolution Mining, RIO, PYBAR, Anglo Gold, Adaro)
Management Consultant & Data/AI Strategist
Collective Mining Project Experience
- Reducing mining risks through predictive analytics around OH&S to prevent workplace incidents (WA HQ Mining).
- Artificial Intelligence, ML, Machine Vision and Data Science based mining circuit optimisation platform, using real world physics simulators, deep learning (ML) and gaming engines generating annual savings in excess of $50m (VIC HQ Mining).
- Machine Learning to reduce copper production circuit wastage (WA HQ Mining, Minerals, Metals).
- Mining – Preventative maintenance using temperature, speed, vibration, moisture and other variables (VIC HQ Mining).
- Mobile Equipment Safety (PH Mining & Energy– in progress).
- PoC ingestion, reporting and analysis for production levels against geological and blast fragmentation models with integration for fleet telemetry (QLD HQ Mining).
- IoT Edge solution to prevent excess time on site whilst core samples were being analysed (VIC HQ Mining).
- Drill and Blast Optimisation to balance blasting cost and production dig rate to deliver cost reductions (NSW HQ Mining).
- Data Estate Modernisation, Azure, GCP, AWS, data lake, data warehouse, Power BI, Databricks, ML, AI, automating data from historians and mining equipment, master data management, real-time streaming and more (Various Mining, Minerals, Energy, Metals).
- Risk Culture, Safety Culture, Engagement & Psychological Wellbeing Surveys.
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Rad Anandakumar is a leading expert in data analytics, machine learning, and AI, with a career spanning more than 2 decades. As an AI + Data Technology Strategist, he has led digital transformations and AI-driven business solutions, working with cutting-edge technologies like Generative AI, IoT, and predictive analytics.
