ABOUT THE COURSE:This course will cover mine automation and data analytics applicable to mining systems. The students will gain a comprehensive overview of state-of-the-art mining automation and practical skills in artificial intelligence and other digital technologies used in the mining industries. The course would also benefit the researcher working on implementing Industry 4.0 in the Mining site and the Mining Industry. The lectures would sequentially expose the students to the practical challenges of implementing automation in the Mining field and processing plants with researched case studies.INTENDED AUDIENCE: Undergraduate students of Bachelor of Mining Engineering and students of other disciplines interested in the research to implement Industry 4.0 in Mining Engineering applications in the field/mine site would be the potential audience for the course.PREREQUISITES: An introductory course on Mine Machinery and courses on Mining Methods (Underground Mining, Surface Mining, Coal Mining, Metal Mining, etc.) would be preferred. This will be suitable for this student having exposure to the subjects mentioned above. However, as a pre-requisite of this course, all of the subjects mentioned above are optional.INDUSTRY SUPPORT: Sandvik Mining, Vedanta, and Epiroc Mining are the potential takers of this online course. The course would be beneficial and relevant for the executives of Coal India Limited, the largest coal-producing company in the world.
Mine Automation and Data Analytics
IIT (ISM) Dhanbad and NPTEL via Swayam
This course may be unavailable.
Overview
Syllabus
Week 1: Lecture 1: Introduction to Automation, Principles and Strategies of Automation and enhancement of Productivity Lecture 2: Essential Elements of an Automated System
Week 2: Lecture 3: Autonomous Mining System I: Autonomous Haulage Systems Lecture 4 :Autonomous Mining System II: Automated Drilling System Lecture 5: Autonomous Mining System III: Fleet Management System: TDS
Week 3: Lecture 6: Computerised Maintenance Management System, ERP for Mining Industry Lecture 7 :Mine Robotics: Mining Remote Operations & Control
Week 4: Lecture 8 Proximity Sensors and Control Systems Lecture 9 Radar Systems, RFID in Mining Engineering Lecture 10 Geo-fencing, CCD camera in Mining for safety and management
Week 5: Lecture 11 Global Navigational Satellite System in Mining production planning and efficient control of the machine Lecture 12 Automated Communication and Tracking Technologies: Image Processing
Week 6: Lecture 13Automated Communication and Tracking Technologies: SCADA Lecture 14 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 1 Lecture 15 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 2
Week 7: Lecture 16 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 3 Lecture 17 Descriptive Statistics: Introduction
Week 8: Lecture 18 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 1 Lecture 19 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 2 Lecture 20 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 3
Week 9: Lecture 21 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 4 Lecture 22 Regression & ANOVA
Week 10: Lecture 23 Machine Learning: Introduction Lecture 24 Perceptron: Linear Classifier Lecture 25 Support Vector Machine
Week 11: Lecture 26 Concepts of Supervised Learning: Neural Networks, Deep learning Lecture 27 Unsupervised Learning and Challenges for Big Data Analytics: Clustering
Week 12: Lecture 28 Application of Big Data Analytics and Artificial Intelligence (AI) in Mining
Lecture 29 Case studies on Cognitive Maintenance of Mining Systems Lecture 30 Case studies on Orebody modelling and Mine Design etc.
Week 2: Lecture 3: Autonomous Mining System I: Autonomous Haulage Systems Lecture 4 :Autonomous Mining System II: Automated Drilling System Lecture 5: Autonomous Mining System III: Fleet Management System: TDS
Week 3: Lecture 6: Computerised Maintenance Management System, ERP for Mining Industry Lecture 7 :Mine Robotics: Mining Remote Operations & Control
Week 4: Lecture 8 Proximity Sensors and Control Systems Lecture 9 Radar Systems, RFID in Mining Engineering Lecture 10 Geo-fencing, CCD camera in Mining for safety and management
Week 5: Lecture 11 Global Navigational Satellite System in Mining production planning and efficient control of the machine Lecture 12 Automated Communication and Tracking Technologies: Image Processing
Week 6: Lecture 13Automated Communication and Tracking Technologies: SCADA Lecture 14 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 1 Lecture 15 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 2
Week 7: Lecture 16 Virtual Reality Applications: Mining Equipment Concept development, Mine Safety Applications, Mining operation simulations – Part 3 Lecture 17 Descriptive Statistics: Introduction
Week 8: Lecture 18 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 1 Lecture 19 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 2 Lecture 20 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 3
Week 9: Lecture 21 Probability Distributions and Inferential Statistics: Hypothesis tests – Part 4 Lecture 22 Regression & ANOVA
Week 10: Lecture 23 Machine Learning: Introduction Lecture 24 Perceptron: Linear Classifier Lecture 25 Support Vector Machine
Week 11: Lecture 26 Concepts of Supervised Learning: Neural Networks, Deep learning Lecture 27 Unsupervised Learning and Challenges for Big Data Analytics: Clustering
Week 12: Lecture 28 Application of Big Data Analytics and Artificial Intelligence (AI) in Mining
Lecture 29 Case studies on Cognitive Maintenance of Mining Systems Lecture 30 Case studies on Orebody modelling and Mine Design etc.
Taught by
Prof. Radhakanta Koner
