Mine Automation & Data Analytics Course | IIT(ISM) Dhanbad | Prof. Radhakanta Koner

Course Details

Mine Automation and Data Analytics: The Future of Smart Mining

The mining industry stands on the brink of a technological revolution. The integration of automation, data analytics, and artificial intelligence is transforming traditional operations into intelligent, efficient, and safer ecosystems. To equip the next generation of engineers with these critical skills, Prof. Radhakanta Koner from IIT(ISM) Dhanbad offers a comprehensive 12-week course: Mine Automation and Data Analytics.

Meet Your Instructor: Prof. Radhakanta Koner

Prof. Radhakanta Koner brings a wealth of expertise and practical experience to this course. An Assistant Professor at IIT(ISM) Dhanbad since 2016, his research focuses on cutting-edge areas like geomechanics, slope stability, and the application of machine learning and wireless sensor networks in mining. A recipient of the prestigious DST Young Scientist Award and the MGMI Bronze Medal, Prof. Koner has published extensively and leads a dynamic research group of nine members. He has established dedicated labs for UAV Image Processing and Rock Slope Engineering, and is currently executing R&D projects sponsored by SERB and Coal India Limited, ensuring the course content is grounded in real-world, industry-relevant research.

About the Course

This undergraduate-level course provides a comprehensive overview of state-of-the-art mining automation and imparts practical skills in artificial intelligence and digital technologies. It is meticulously designed to bridge the gap between academic theory and industrial application, preparing students and professionals to implement Industry 4.0 principles directly at mining sites and processing plants.

Who Should Enroll?

• Intended Audience: Undergraduate students in Mining Engineering, as well as students from other disciplines interested in smart mining technologies.
• Prerequisites: While introductory knowledge of Mine Machinery and Mining Methods is beneficial, it is not mandatory. The course is structured to be accessible to motivated learners.
• Industry Support & Relevance: The course is highly relevant for professionals at major industry players like Coal India Limited (CIL), Sandvik Mining, Vedanta, and Epiroc Mining.

Detailed 12-Week Course Layout

The course is structured to take learners from fundamental concepts to advanced applications through a logical progression of modules.

Weeks 1-3: Foundations of Automation

• Introduction to automation principles and strategies.
• Essential elements of automated systems.
• Deep dive into Autonomous Haulage, Drilling, and Fleet Management Systems (TDS).
• Computerised Maintenance Management Systems (CMMS) and ERP for mining.
• Introduction to mine robotics and remote operations.

Weeks 4-6: Sensing, Communication & Immersive Tech

• Proximity sensors, radar systems, and RFID technology.
• Geo-fencing and CCD cameras for safety.
• Global Navigation Satellite Systems (GNSS) for production planning.
• Automated communication with Image Processing and SCADA.
• Extensive coverage of Virtual Reality (VR) for equipment design, safety training, and operation simulation.

Weeks 7-9: Core Data Analytics & Statistics

• Descriptive Statistics and Probability Distributions.
• In-depth study of Inferential Statistics and Hypothesis Testing.
• Regression Analysis and ANOVA.

Weeks 10-12: AI, Machine Learning & Big Data Applications

• Introduction to Machine Learning.
• Key algorithms: Perceptron, Support Vector Machines (SVM), Neural Networks, and Clustering.
• Application of Big Data Analytics and AI in mining.
• Practical case studies on Cognitive Maintenance, Orebody Modelling, and Mine Design.

Recommended Books & Resources

The course curriculum is supported by authoritative texts, including:

• The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman.
• Applied Statistics and Probability for Engineers by Montgomery and Runger.
• Mine Mechanization & Automation by Almgren, Kumar, and Vagenas.
• A General Introduction to Data Analytics by Moreira, Carvalho, and Horvath.

Why This Course is Essential

The mining sector is rapidly evolving towards sustainable and efficient practices. This course offers a unique blend of theoretical knowledge and practical insights into the technologies driving this change. By learning from an expert like Prof. Koner, who is actively engaged in frontier research and industry projects, participants gain an unparalleled understanding of how to leverage automation and data to solve real-world mining challenges, enhance safety, and boost productivity.

Enroll in Mine Automation and Data Analytics to future-proof your career and become a leader in the new era of intelligent mining.

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