Evolution of mining technology

1. COLLEGE OF TECHNOLOGY
AND
ENGINEERING, UDAIPUR
DEPARTMENT OF MINING ENGINEERING
Seminar report on
EVOLUTION OF MINING
TECHNOLOGY
Guided by-
Submitted by-
Dr. S.C. Jain
Chetan Nagar

2. CONTENT:
• Introduction
• Modernization of Mining Techniques
• Emerging Technologies in Mining
• Challenges and Opportunities in Future of Mining
technology

3. INTRODUCTION:
Over the course of human history, mining has played a pivotal role in the development and
progress of civilizations. From the early days of simple tools and manual labor to the
modern era of advanced machinery and technology, the evolution of mining technology
has been a remarkable journey of innovation and efficiency.
Need For Advancements in Mining Technology
• Resource Efficiency
• Safety and Health
• Environmental Sustainability
• Exploration and Discovery
• Social Responsibility

4. MODERNIZATION OF MINING TECHNIQUES
• Introduction to Electricity
• Drilling Technology
• Ventilation Systems
• Safety Regulations and Practices
• Automation and Robotics
• Digitalization and Data Analytics
The modernization of mining techniques has significantly enhanced the
efficiency, safety, and sustainability of mining operations. The introduction of
electricity, advanced drilling methods, ventilation systems, safety regulations,
automation, and digitalization have propelled the industry forward. These
advancements have allowed for higher productivity, reduced environmental
impact, improved worker safety, and better resource management, ensuring
the continued evolution of mining practices in the modern era.

5. EMERGING TECHNOLOGY IN MINING

6. AUTOMATION AND ROBOTICS
• Automation and robotics are transforming the
mining industry by introducing advanced
technologies that enhance efficiency, safety,
and productivity. Here are some key
applications of automation and robotics in
mining
1. Autonomous Haulage Systems (AHS):
Autonomous haulage systems involve the use of
self-driving trucks and other vehicles to
transport materials within the mine site. These
vehicles are equipped with advanced sensors,
GPS, and communication systems to navigate
and operate safely without human intervention.
AHS technology optimizes haulage operations by
improving truck utilization, reducing fuel
consumption, and increasing overall productivity

7. 2. Remote Control Mining: Remote control mining
allows operators to control mining equipment from a
remote location, away from the hazardous mining
environment. Using advanced teleoperated systems,
operators can control equipment such as loaders,
drills, and excavators, improving safety and reducing
the risks associated with manual operation. Remote
control mining also enables operations in challenging
environments where human presence may be difficult
or dangerous.
3. Drones/UAVs for Surveying and Monitoring:
Unmanned Aerial Vehicles (UAVs) or drones have
become valuable tools for surveying, mapping, and
monitoring mining operations. Drones equipped with
high-resolution cameras and sensors can quickly and
accurately survey large areas, collecting data for
geological mapping, topographic surveys, and
stockpile volume calculations. They can also monitor
operational activities, inspect infrastructure, and
assess environmental impacts, providing real-time

8. ADVANCED DATA ANALYTICS AND
ARTIFICIAL INTELLIGENCE
Advanced data analytics and artificial intelligence (AI) are playing a
crucial role in transforming the mining industry. By leveraging vast
amounts of data collected from sensors, equipment, and geological
surveys, mining companies can gain valuable insights and optimize
various aspects of their operations. Here are some key applications of
advanced data analytics and AI in mining
1. Predictive Maintenance: Predictive maintenance uses data analytics
and AI algorithms to monitor the condition of mining equipment and
predict potential failures or maintenance needs. By analyzing sensor
data and historical maintenance records, AI systems can identify
patterns and anomalies that indicate equipment deterioration or
impending failures. This enables proactive maintenance scheduling,
reducing unplanned downtime, and optimizing equipment
performance.

9. 2. Machine Learning for Ore Grade Estimation: Machine learning algorithms can
analyze geological data, including drilling samples, assay results, and historical
production data, to estimate the ore grade of a mining deposit. By training
algorithms on existing data, these systems can predict the mineral content and
quality of ore deposits in real-time. This information helps optimize mining
operations, enabling selective mining, efficient resource allocation, and improved
production planning.
3. Optimization of Mining Operations: Advanced data analytics and AI techniques
can optimize various aspects of mining operations, including production
scheduling, resource allocation, and material flow management. By considering
factors such as ore grade variability, equipment availability, and market demand,
AI algorithms can generate optimized plans and schedules to maximize
production efficiency, minimize costs, and meet quality targets. This optimization
ensures the optimal utilization of resources and enhances overall operational
performance.
4. Environmental Monitoring and Sustainability: Data analytics and AI systems can
assist in monitoring and managing the environmental impact of mining
operations. By integrating real-time data from environmental sensors, these
systems can detect and predict potential environmental risks such as air and water
quality, noise levels, and land degradation. Mining companies can use these
insights to implement proactive mitigation measures, minimize ecological

10. 5. Safety and Risk Management: Advanced data
analytics and AI can enhance safety and risk
management in mining. By analyzing data from various
sources, including sensors, monitoring systems, and
incident reports, AI algorithms can identify patterns
and trends related to safety hazards and risks. This
information enables the implementation of proactive
measures to prevent accidents, improve workplace
safety, and ensure compliance with safety regulations.
6. Energy Efficiency and Sustainability: Data analytics
and AI can help optimize energy consumption and
promote sustainability in mining operations. By
analyzing energy data and equipment performance, AI
systems can identify opportunities for energy efficiency
improvements, optimize power usage, and reduce
carbon emissions. These technologies can also support
the integration of renewable energy sources into
mining operations, further enhancing sustainability.

11. VIRTUAL AND AUGMENTED REALITY IN
MINING
Virtual reality (VR) and augmented reality (AR)
technologies are making significant strides in
the mining industry, offering innovative
solutions for training, remote collaboration,
and visualization of complex geological data.
Here are some key applications of VR and AR
in mining
1.Training Simulations: VR and AR
technologies provide immersive and realistic
training environments for mining personnel.
Virtual training simulations allow operators to
practice operating mining, such as haul trucks
or excavators, in a safe and controlled virtual
setting. These simulations help improve
operator skills, reduce training costs, and
enhance safety by allowing individuals to gain

12. 2. Remote Collaboration and Communication: VR and AR enable remote
collaboration and communication among mining teams located in different
geographical areas. Using VR headsets or AR devices, geographically dispersed
teams can virtually meet and interact, visualizing and discussing mining plans,
geological data, and operational scenarios in a shared virtual environment. This
fosters efficient decision-making, enhances teamwork, and reduces the need for
travel, saving time and costs.
3. Visualization of Geological Data: VR and AR technologies provide interactive
and immersive visualization of complex geological data. Geologists and mining
engineers can use these technologies to explore and analyze geological models,
mine plans, and exploration data in a 3D virtual environment. This enhances their
understanding of geological structures, mineral deposits, and potential hazards,
leading to better-informed decision-making and optimized resource extraction.
4. Safety Training and Hazard Identification: VR and AR can be utilized for safety
training and hazard identification in mining. Virtual environments can simulate
hazardous conditions, such as confined spaces, rock falls, or chemical spills,
allowing workers to experience and learn how to respond to such situations safely.
AR can overlay real-time safety information onto the physical environment, such
as warning signs, escape routes, or gas concentration levels, aiding in hazard
identification and risk mitigation.

13. 5. Mine Planning and Design: VR and AR technologies facilitate mine
planning and design by providing visual and interactive
representations of mine layouts and infrastructure. Mining
professionals can create and manipulate 3D models of mines,
equipment, and infrastructure, enabling them to assess different
design options, evaluate potential bottlenecks or clashes, and optimize
the layout for efficiency and safety. These technologies aid in
communicating design concepts and facilitating stakeholder
engagement
6. Maintenance and Repairs: VR and AR can assist in maintenance and
repair activities by providing real-time visualizations, instructions, and
guidance to technicians. AR devices can overlay virtual instructions and
graphics onto physical equipment, guiding technicians through repair
procedures or maintenance tasks. This improves efficiency, reduces
errors, and minimizes equipment downtime.

14. 3D PRINTING AND ADDITIVE
MANUFACTURING IN MINING
1. Rapid Prototyping: 3D printing enables rapid prototyping of mining
equipment and components. Traditional manufacturing processes often
involve time-consuming and costly prototyping methods. With 3D
printing, mining companies can quickly create physical prototypes of
equipment, tools, or parts directly from digital models. This speeds up
the design and development process, allowing for iterative improvements
and reducing time-to-market.
2. Customization of Parts: Mining operations often require specialized
and custom-designed parts that may not be readily available through
traditional manufacturing methods. 3D printing enables the
customization of parts, allowing mining companies to design and
produce components tailored to their specific needs. This capability
facilitates equipment modifications, replacement of obsolete parts, and
adaptation to unique mining conditions, ultimately improving operational

15. 3. Supply Chain Optimization: 3D printing has the potential to
optimize the supply chain in the mining industry. By utilizing 3D
printers on-site or near mining operations, companies can produce
parts and tools as needed, reducing dependency on external suppliers
and mitigating supply chain disruptions. This decentralized
production approach can reduce lead times, transportation costs, and
inventory requirements, resulting in improved overall supply chain
efficiency.
4. Lightweight and Complex Designs: 3D printing allows for the
creation of lightweight and complex designs that are difficult or
impractical to achieve with traditional manufacturing methods. By
utilizing advanced additive manufacturing techniques, such as lattice
structures or hollowed components, mining equipment and parts can
be optimized for weight reduction without compromising strength or
functionality. This leads to improved energy efficiency, reduced
material consumption, and enhanced performance.
5. On-Demand Spare Parts: Mining operations often rely on a vast
inventory of spare parts to support maintenance and repairs. 3D
printing offers the potential to produce spare parts on-demand,
eliminating the need for extensive storage and reducing costs
associated with inventory management. When a part is needed, it can
be 3D printed locally, minimizing downtime and improving

16. IOT (INTERNET OF THINGS)
1. Remote Monitoring: IoT devices and sensors can be deployed
throughout mining operations, including vehicles, machinery,
infrastructure, and even workers' personal protective equipment (PPE).
These sensors collect real-time data on parameters such as
temperature, pressure, humidity, vibration, and location, allowing
operators to monitor equipment health, detect anomalies, and
proactively address maintenance issues before they result in costly
breakdowns.
2. Asset Management: By equipping mining assets with IoT sensors,
mining companies can track and manage their equipment more
effectively. This includes monitoring utilization rates, tracking
equipment locations, optimizing maintenance schedules, and ensuring
compliance with safety regulations. Improved asset management leads
to reduced downtime, increased productivity, and enhanced cost-
efficiency.

17. 3. Environmental Monitoring: IoT enables
comprehensive environmental monitoring in mining
operations. Sensors can measure parameters like air
quality, water quality, noise levels, and dust
concentration, helping mining companies stay
compliant with environmental regulations. Real-time
data collection and analysis enable early detection of
environmental impacts, facilitating proactive
mitigation measures and reducing the ecological
footprint of mining activities.
4. Connectivity and Communication: IoT networks
facilitate seamless communication and data exchange
between different mining components, including
equipment, vehicles, control systems, and personnel.
This connectivity allows for real-time collaboration,
remote monitoring, and centralized control of mining
operations, regardless of the geographical location. It
also enables the integration of IoT with other
emerging technologies like artificial intelligence (AI)

18. CHALLENGES AND OPPORTUNITIES IN FUTURE OF
MINING TECHNOLOGY
• Challenges
1. Environmental Sustainability: Mining operations have a significant
environmental impact, including habitat destruction, water pollution, and carbon
emissions. Balancing resource extraction with environmental sustainability is a key
challenge.
2. Resource Depletion: As easily accessible mineral deposits become depleted,
mining companies must explore and extract minerals from more remote and
challenging locations. This poses logistical and operational challenges.
3. Social License to Operate: Mining companies face increasing scrutiny and
pressure to obtain social acceptance and engage with local communities. Gaining
and maintaining a social license to operate is crucial for sustainable mining
practices.
4. Technological Adoption: Embracing new technologies and integrating them into
existing operations can be challenging for the mining industry. Implementation
requires investment, training, and overcoming resistance to change

19. • Opportunities:
1. Automation and Robotics: Advancements in automation and robotics can enhance
operational efficiency, reduce costs, and improve worker safety by replacing or augmenting
human labor in hazardous or repetitive tasks.
2. Advanced Data Analytics and Artificial Intelligence: Leveraging data analytics and AI
algorithms enables better decision-making, predictive maintenance, and optimization of
mining processes, leading to improved productivity and resource efficiency.
3. Renewable Energy Integration: Integrating renewable energy sources, such as solar and wind
power, into mining operations can reduce reliance on fossil fuels, lower emissions, and
contribute to sustainable energy practices.
4. Circular Economy Approaches: Adopting circular economy principles, such as recycling and
reusing materials, can reduce waste generation and promote resource efficiency within the
mining industry.
5. Stakeholder Engagement and Community Development: Engaging with local communities,
indigenous groups, and other stakeholders fosters trust, promotes transparency, and
contributes to sustainable community development.
6. Advanced Exploration Techniques: Utilizing advanced exploration technologies, such as
remote sensing and geophysical surveys, enhances the efficiency and accuracy of mineral
exploration, optimizing resource discovery and extraction.
7. Safety and Health Innovations: Implementing advanced safety technologies, real-time

20. THANK YOU