Mine Automation and Data Analytics

By Prof. Radhakanta Koner | IIT(ISM) Dhanbad

Learners enrolled: 244 | Exam registration: 2

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.

Summary

Course Status :	Upcoming
Course Type :	Core
Language for course content :	English
Duration :	12 weeks
Category :	Metallurgy and Material science & Mining Engineering
Credit Points :	3
Level :	Undergraduate
Start Date :	20 Jan 2025
End Date :	11 Apr 2025
Enrollment Ends :	27 Jan 2025
Exam Registration Ends :	14 Feb 2025
Exam Date :	04 May 2025 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

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 13: Automated 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.

Books and references

1) Hastie, Trevor, et al. The elements of statistical learning. Vol. 2. No. 1. New York: Springer, 2009.

2) Montgomery, Douglas C., and George C. Runger. Applied statistics and probability for engineers. John Wiley & Sons, 2010

3) G. Almgren, U. Kumar, N. Vagenas: Mine Mechanization & Automation 1st Edition

4) J. O'Shea M. Polis: Automation in Mining, Mineral and Metal Processing (1st Edition), Proceedings of The 3Rd Ifac Symposium, Montreal, Canada 18-20 August 1980

5) João Moreira, Andre Carvalho, Tomás Horvath: A General Introduction to Data Analytics, Wiley, 2019

6) Thomas A. Runkler, Data Analytics: Models and Algorithms for Intelligent Data Analysis, Vieweg+Teubner Verlag, 2012

Instructor bio

Prof. Radhakanta Koner

IIT(ISM) Dhanbad

Prof. Radhakanta Koner has been working as Assistant Professor at IIT(ISM) Dhanbad since 2016. His area of research includes geomechanics, slope stability, machine learning in mining allied applications, wireless sensor networks in geo- structure health monitoring, etc. He teaches Mine Automation and Data Analytics, Mine Simulation, and Data Analytics and Remote Sensing and Digital Image Processing in the Winter Semester. He teaches Open-pit Slope Analysis and Design, Surface Mine Slope Stability, and Design in the Monsoon Semester. Professor Koner is executing two R&D projects sponsored by Science Engineering Research Board (SERB) New Delhi and Coal India Limited (CIL) R&D Board, Kolkata, at present. Professor Koner completed one R&D project from SERB, New Delhi, and one sponsored consultancy project from ECL, Sanctoria. Professor Koner steered and established two dedicated research labs: UAV Image Processing and Rock Slope Engineering Lab at IIT(ISM) Dhanbad. At present, his research group strength is Nine. In 2013, Koner was awarded DST Young Scientist under the FAST TRACK Scheme for Young Scientists of Science Engineering Research Council (SERC), New Delhi. He was also awarded MGMI Bronze Medal. Professor Koner has published more than twenty research papers in internationally reputed journals and conferences. Professor Koner supervised two PhD, actively worked with two PhD students, and supervised eight Master's theses. Professor Koner served as Time Table in In-charge of the Mining Engineering Department of IIT(ISM) Dhanbad for more than five years. Professor Koner also served as a Dual Degree Advisor of (BTech Mining+ MBA) and (BTech Mining+MTech Mining) for three years.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: May 4, 2025 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.

Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team