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25-048
Integrating a Drill Rig into the Digital Mine 4.0 Ecosystem
Max Friedemann
TU Bergakademie Freiberg, Germany
Anna Gustafson
Luleå University of Technology, Sweden
Håkan Schunnesson
Luleå University of Technology, Sweden
Alexandros Bousdekis
Information Management Unit (IMU),
Institute of Communication and Computer Systems
(ICCS), National Technical University of Athens
(NTUA), Athens, Greece
Helmut Mischo
TU Bergakademie Freiberg, Germany
ABSTRACT
Many devices used in mining are not monitored by sensors
or do not have their own intelligence. By retrofitting sen-
sors and real-time data processing, machines can be inte-
grated into an existing digital infrastructure.
Within the project Mine.io funded by the European
Union a Sandvik DE110 exploration drill rig is being digi-
tized using various AI algorithms at research and educa-
tion Mine “Forschungs- und Lehrbergwerk Reiche Zeche
(FLB)” of TU Freiberg. The aim is to increase the produc-
tivity of drilling with real-time evaluation of the current
rock to be drilled and the current maintenance status of
the drill rig. The drill rig is equipped with a speed sensor,
pressure sensors in the hydraulics, 3-axis vibration sensor,
borehole length measurement and temperature sensor. The
sensors are additionally attached to the drilling rig and no
structural changes on the drill rig are necessary. All data
are processed real-time at a server structure outside of the
mine using AI algorithms to analyze which rock (ore or
host rock) is being drilled and to perform predictive main-
tenance. Processed Data are visualized for the operator to
optimize the workflow and the productivity.
Introduction
As global demand for raw materials continues to rise, min-
ing faces growing pressure to meet production goals while
also addressing environmental and social responsibilities.
Digital solutions are essential to achieve a balanced approach
that supports these demands through efficient, low-impact
operations. Moreover, by leveraging digital communication
systems, companies can improve coordination across dif-
ferent sites, even in remote locations, to ensure a smoother
flow of information and resources. Enhanced data trans-
parency allows informed decision-making and aligns with
regulatory requirements that prioritize environmental pro-
tection and community welfare. Thus, digitalization is not
merely a trend but a critical necessity to develop mining
industry towards a safer, more productive, and sustainable
future. [9, 10]
Digitization in mining represents a transformative shift
towards smarter, safer, and more sustainable operations. In
a sector, which is traditionally known for labor-intensive
and high-risk processes, digital tools have introduced auto-
mation and real-time data insights that can significantly
improve efficiency and safety. Technologies such as IoT,
artificial intelligence, and big data analytics allow for bet-
ter monitoring of equipment, predictive maintenance, and
optimized resource allocation. These advancements reduce
unplanned downtime, enhance productivity and minimize
operational costs. Additionally, digitalization supports sus-
tainable practices by enabling precise resource extraction,
lowering waste, and reducing the environmental footprint
25-048
Integrating a Drill Rig into the Digital Mine 4.0 Ecosystem
Max Friedemann
TU Bergakademie Freiberg, Germany
Anna Gustafson
Luleå University of Technology, Sweden
Håkan Schunnesson
Luleå University of Technology, Sweden
Alexandros Bousdekis
Information Management Unit (IMU),
Institute of Communication and Computer Systems
(ICCS), National Technical University of Athens
(NTUA), Athens, Greece
Helmut Mischo
TU Bergakademie Freiberg, Germany
ABSTRACT
Many devices used in mining are not monitored by sensors
or do not have their own intelligence. By retrofitting sen-
sors and real-time data processing, machines can be inte-
grated into an existing digital infrastructure.
Within the project Mine.io funded by the European
Union a Sandvik DE110 exploration drill rig is being digi-
tized using various AI algorithms at research and educa-
tion Mine “Forschungs- und Lehrbergwerk Reiche Zeche
(FLB)” of TU Freiberg. The aim is to increase the produc-
tivity of drilling with real-time evaluation of the current
rock to be drilled and the current maintenance status of
the drill rig. The drill rig is equipped with a speed sensor,
pressure sensors in the hydraulics, 3-axis vibration sensor,
borehole length measurement and temperature sensor. The
sensors are additionally attached to the drilling rig and no
structural changes on the drill rig are necessary. All data
are processed real-time at a server structure outside of the
mine using AI algorithms to analyze which rock (ore or
host rock) is being drilled and to perform predictive main-
tenance. Processed Data are visualized for the operator to
optimize the workflow and the productivity.
Introduction
As global demand for raw materials continues to rise, min-
ing faces growing pressure to meet production goals while
also addressing environmental and social responsibilities.
Digital solutions are essential to achieve a balanced approach
that supports these demands through efficient, low-impact
operations. Moreover, by leveraging digital communication
systems, companies can improve coordination across dif-
ferent sites, even in remote locations, to ensure a smoother
flow of information and resources. Enhanced data trans-
parency allows informed decision-making and aligns with
regulatory requirements that prioritize environmental pro-
tection and community welfare. Thus, digitalization is not
merely a trend but a critical necessity to develop mining
industry towards a safer, more productive, and sustainable
future. [9, 10]
Digitization in mining represents a transformative shift
towards smarter, safer, and more sustainable operations. In
a sector, which is traditionally known for labor-intensive
and high-risk processes, digital tools have introduced auto-
mation and real-time data insights that can significantly
improve efficiency and safety. Technologies such as IoT,
artificial intelligence, and big data analytics allow for bet-
ter monitoring of equipment, predictive maintenance, and
optimized resource allocation. These advancements reduce
unplanned downtime, enhance productivity and minimize
operational costs. Additionally, digitalization supports sus-
tainable practices by enabling precise resource extraction,
lowering waste, and reducing the environmental footprint