Information Modelling Guidelines for the Mining Sector

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Information Modelling Guidelines for the Mining Sector
Jyrki Salmi1 and Rauno Heikkilä1
1University of Oulu, Finland
jyrki.salmi@oulu.fi, rauno.heikkila@oulu.fi
Abstract –
Mining is rapidly digitalizing and big data
surrounds mines in their everyday activities and
processes. Building Information Modelling (BIM) has
long since taken an indispensable role in the design
and management of buildings and infrastructures
and is currently widely used as a standard for
information management. Based on the results of the
workshop series organized by the University of Oulu,
a proposal is presented for further development of the
concept of Mining Information Modelling
(MiningBIM or MIM for short). The purpose of the
workshops was to present, prepare and lay the
foundation for the development of modelling
guidelines for the mining sector. From the
participants’ point of view BIM is seen as a
megatrend that there is no point in trying to stop, and
the idea of standardizing BIM in the mining and
tunnelling sector is strongly supported. The results of
the workshops showed that BIM is already a widely
recognized tool and it is worth starting to study and
develop further towards MIM and TIM concepts,
including also international standardization work.
Keywords –
BIM; MIM; TIM; Modelling Guidelines
1 Introduction
Mining Information Modelling (MIM) enables
efficient information management and big data
visualization throughout the mining project life cycle. In
mining, there has traditionally been an inability to
recognize the value of all available information in
different parts of the production and processing chain.
1.1 Background
1.1.1 Big data
Digitalization is everywhere in different industries
and also in our private lives. Barnewold and Lottermoser
[1] describe that “digitalization in the mining industry
refers to the use of computerized or digital devices,
systems and digitized data that are to reduce costs,
improve business productivity, and transform mining
practices.”
The mining world is rapidly digitalizing and big data,
or mass data, surrounds mines everywhere in their
everyday activities and processes. “ With big data, the
key to success is to turn a huge repository of data into a
functional intelligence and get value from it. The mining
industry can significantly benefit from implementing big
data and real-time data analysis” [1].
1.1.2 From data to information models
Data, that is, facts and statistics collected for some
reference, must always be presented somehow. Raw data
itself is worthless, but it is important and worth refining.
“In a mine, the entire tunnel design information”,
according to Koch et al. [2], “is traditionally available in
the form of independent, dispersed, and heterogeneous
data files, and since data sources are barely linked in
practice, unilateral decisions are made that do not
consider all relevant aspects”. So when structured or
unstructured data exists, it often needs to be shared and
combined with other data sources to enable data fusion.
“The project data, that is typically shared among the team
members of organization, varies also in terms of type,
scale, format, and life cycle phase” [2]. Figure 1 shows
the authors’ view of the trajectory from raw data to
advanced target setting.
Figure 1. Trajectory from raw data to advanced
target setting
The use of data makes it possible to make future
actions smarter. The true value of data is determined only
when decisions are made based on the information, i.e.
when some given data or learned data is put into practice
or passed on in some form. All relevant information
collected from the mining process lays the foundation for
the mine’s decision-making process as knowledge, i.e.
data, information and skill combined with an
understanding of the topic. The wisdom gained after that
can be used to achieve the goals set. Analyzing and real-
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time utilizing the relevant information accumulated with
the help of big data is a key part of the mine’s information
management process. Likewise, “stable, economical, and
sustainable design and construction of all underground
facilities requires reliable knowledge regarding the
expected impacts of the used construction method on the
built environment” [2].
Huang et al. [3] state, that “when semiautonomous or
autonomous mining platforms, used for data acquisition
are combined with machine learning, and especially with
deep learning, information of the built environment can
be managed to build knowledge forward and create
values”. According to Willmott [4], “the future for
mining in which many assets are operated by machines
that run automatically or autonomously means, that the
only capability that will matter, is going to be the ability
to make decisions based on the information those assets
provide. Having the right data at the right time and the
tools and capabilities to understand and manage the data
is becoming absolutely fundamental to business success”.
This means that in the future, all relevant industrial
information must be structured, modelled, and visualized
in information models in order to process and manage it
efficiently in the human-machine interaction process.
Figure 2 shows the authors’ view of the pursuit of desired
values based on the benefits of utilizing information
modelling and automation.
Figure 2. The benefits of information modelling
support the benefits of automation to achieve the
desired values
According to Slansky [5], “big data can be used
especially in information modelling to support advanced
analytics applications to discover the flaws and to
achieve continuous process improvements and determine
best practices across the whole design or build lifecycle”.
1.1.3 BIM
The information model is described by Li et al. [6] so
that it is a “3D information integration technology based
on Computer Aided Design (CAD). It is a digital and
visual expression of the physical and functional
information produced in the engineering construction and
management process. Information modelling includes
two main aspects: information integration and 3D
geometrical modelling”.
There are numerous options for describing BIM. The
definition of BIM varies in different contexts and also
from different perspectives. Australasian authors of the
National Guidelines for Digital Modelling [7] defined
BIM in 2009 as “a three-dimensional representation of a
facility based on objects including some information
about the objects beyond the graphical representation”.
In building construction, BIM has long played an
indispensable role in the design and management of
buildings, where it has been widely used as a standard for
information management [8]. In practice, BIM has been
widely applied in design and construction phases, while
applications in the facility management and operation
phases are still at a very early stage [9][10].
According to Hegemann et al. [10] it is important to
“include only those data in the BIM model that are
required for evaluations to avoid overloading the model
and, thus, losing the clarity that makes a BIM model so
valuable”. A collaborative process of information
modelling is defined as OpenBIM that shares process
information and supports seamless collaboration for all
process participants throughout the process lifecycle,
implementing open, neutral data exchange formats [11].
62 research articles related to BIM and 171 case
studies have been reviewed, and it has been found that
BIM plays a much less role in underground tunnelling
than in building construction. Only very few applications
focus on maintenance and much less on tunnel
maintenance [9]. To achieve the benefits of BIM also in
underground tunnelling (Tunnelling Information
Modelling, TIM), approaches have been proposed to
extend the BIM concept to underground infrastructure
projects as well, in order to facilitate design and analysis
tasks and thus increase the productivity in design,
construction, and operation [12][13]. In the same way,
this paper now provides a built infrastructure information
modelling (InfraBIM/I-BIM) approach to increase the
potential of the mining sector to further develop the
concept of Mining Information Modelling (MIM) for
mining as well.
1.2 Mining Information Modelling (MIM)
Fraser [14] states, that “issues related to
communications in mining like data exchange and
interoperability, need to be overcome in future mines and
industry-wide standards need to evolve. Then ultimately,
transformational productivity gains will be realized by
combining an enhanced knowledge of the resource with
the improved control of mining and milling systems, and
an ability to optimize or tailor all mine activities as a
whole-of-business, end-to-end process”.
In Australia CSIRO [15] has stated that “a standard
for data communication and data base architecture must
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be agreed among the mining and tunnelling community
before information exchange is practical between
different data sources of the mine’s production processes.
When instruments and communications comply with the
standard, then the industry will access the benefits of
maximum interoperability allowing machines and
mining systems to model and react to changing
conditions in real time”. CSIRO has named this overall
concept as The Common Mine ModelTM. Also, according
to CSIRO [16] the “first of the seven fundamental
components for the successful operation of the future
mine is a knowledge driven database model that is
common and accessible across all activities of the mining
operation”.
In China, the term Digital Mine is used instead of
BIM, and its essence is Mining Information Model to
store all mine-related information [17]. MIM in that
context is a “digital expression of the mining resources,
mining environment and mining engineering objects and
a digital re-engineering of the mine life cycle’s business
processes to realize information interoperability,
information sharing and collaboration of various
business entities and to solve the problem of information
islands in the mining industry and to improve the
efficiency and quality of the participants” [17].
According to Wang J. et al. [18], “hardware and
software products in the whole life cycle of mines, lack
uniform data standards and specifications and therefore
each system has its own data format and storage file and
the phenomenon of “information islands” is serious.
Therefore, a theoretical framework of Mining
Technology Collaboration Platform (MTCP) has been
proposed. Under the guidance of the BIM idea, the
information island problem, as well as information loss,
redundancy, duplication, inconsistency, and other issues
can be well resolved”. Du et al. [19] also suggest that “for
creating high yield and high efficiency mining
production, mining companies should develop the
formerly mentioned Digital Mine concept rapidly”.
However, the target functionality of most BIM tools
designed for architecture and building modelling is not
very well suited for mining projects. Editing custom
parameter objects and object families becomes inevitable.
“While still pending full standardization, the application
of BIM in tunnel projects requires customized solutions
for many aspects of design and construction phases.
Ground characterization and geospatial location
information are vital to the establishment of as-designed
underground BIM model. The inclusion of ground
conditions and geotechnical data into the BIM model also
improve the quality and the usefulness of the mining
model, not only during the design phase but also, and in
particular, during the construction and the lifecycle
management of the infrastructure, as a support to
decision making process. Geological and geotechnical
issues are thus the most important part of underground
infrastructures design” [20].
In the course of this research, it has become clear to
the author that there is already a fairly well-established
description of TIM in the tunnelling sector. But it has also
become clear that for the mining sector the overall picture
of MIM, and therefore of the real research gap, is not at
all so mature. In mining, certain elements of BIM already
exist, for example, 3D models are widely used, but very
rarely any information is associated with these model
structures.
The route from traditional construction BIM and
GeoBIM domains to InfraBIM and TIM development,
the BIM path is leaning towards more precise MIM
definitions. Based on existing examples and very good
experiences of developing the InfraBIM domain in
Finland since 2013, the need to start further research on
MIM and find out its benefits for the mining sector is
highlighted. Figure 3 shows the authors’ view of the
development path of BIM technology towards MIM and
its potential for utilization, especially in machine control
(MC).
Figure 3. The development path of BIM technology
towards MIM and its utilization possibilities in MC
One of the great advantages of MIM
conceptualization is an open digital model-based
operating environment (ecosystem) that enables the
efficient use of semi-automated, automatic and
autonomous machines and swarms of machines. In the
mining and tunnelling sectors, it would therefore enable
knowledge-driven and model-based production.
1.2.1 MIM prerequisites
Currently, there are no specific BIM guidelines or
other related specifications available for the mining
sector. However, the basic modelling idea of MIM is the
same as that of InfraBIM based on the OpenBIM concept.
The OpenBIM concept is built on the idea that is three
basic prerequisites for a successful BIM process: 1)
Modelling guidelines, 2) Information classification, and
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3) Data transfer formats, see below Figure 4. These key
elements must primarily be sound and consistent for BIM
management and practice to work. In Finland, the success
of the InfraBIM concept implementation is strongly
based on this setup.
Figure 4. Three key elements in the development and
implementation of the BIM process
In this paper, modelling guidelines are discussed
mainly because they make up the bulk of the whole.
Modelling guidelines tell designers what and how to
model. In Finland, these InfraBIM guidelines are called
“Common Infra Model Requirements” (YIV-ohjeet in
Finnish) [21]. They were prepared in the InfraFINBIM
project in 2013 together with companies in the field of
infrastructure construction.
Information classification defines the common
language on which modelling is based on. “Different
stakeholders may use several different data standards and
if no common information classification is used, it can
result in huge amounts of unusable data and difficulties
with exchanging data between different data systems and
databases. For tunnelling sector there already exists
several different coding systems, one also presented
especially for tunnel facility management” [10].
“Common and standard data transfer formats make
work machines in the field and computers to talk with
central IT systems. Data interoperability is enabled in
tunnelling projects with Industry Foundation Classes
(IFC) format, which allows data exchange between
several BIM software” [2]. Because “IFC provides a
well-organized kernel and contains information rich
objects used in the construction industry, it is logical to
apply to the development of the information modelling in
mining, too” [6]. However, there are also many other
common data transfer formats available. For example,
the IM-format (Infra Model) is used in Finland, where
efforts have been made to ensure that all machine control
systems support this common and open form of data
transfer for earthworks. In USA, the Open Mining
Format (OMF) is being developed as an open-source file
definition format that supports the transfer of geological
and tropological data between software systems.
1.3 Aim of the research
The aim of the research is
•to discuss about the challenges of management of
relevant data and information in mines,
•to present the potential of BIM based information
modelling concepts and propose the idea of
applying InfraBIM and TunnellingBIM concepts
into the mining sector, and
•to present the results of the MIM development
workshop series on modelling guidelines in Finland
and propose the next steps for implementing MIM
in the mining sector.
This research paper proposes the introduction of
InfraBIM and TunnellingBIM methods in the mining
environment, either in underground (UG) or open cast
(OC) mines. The idea of creating such a new BIM-based
information ecosystem for the entire mining and
tunnelling sector is ideally based on the rapid growth of
the number of automated and autonomous machines in
mines and tunnel construction sites. Therefore,
translating physical mining infrastructure into digital
infrastructure for machine control purposes is
increasingly necessary to enable automation of both
single machine and a swarm of machines.
2 Materials and methods
In 2021, an extensive Next Generation Mining (NG
Mining) research project funded by Business Finland and
Finnish industry was launched in Finland. The project
focused on enabling the safe, sustainable and productive
use of autonomous and networked non-road mobile
machinery in underground mining environments. As part
of the research project, which also included the
conceptualization of the digital twin, the need to start
exploring the OpenBIM concept suitable for the entire
mining and tunnelling sector was identified and
suggested.
During 2022, the University of Oulu organized a
series of workshops series of a total of six special, three-
hour-long, online workshops, both for all participants in
the NG Mining project and for all key Finnish
representatives of the mining and tunnelling sector. The
workshops were chosen as a research method in order to
create the widest possible discussion of a new topic
among specialists from different fields.
2.1 Workshop series
The main goal of the workshop series was to create a
consensus-based starting point for the development of
new and open Mining & Tunnelling Information
Modelling (MIM&TIM) concepts in Finland. In addition,
goals were to present BIM and its advancements and
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opportunities in the mining and tunnelling sectors, to
evaluate the experience and best practices already
accumulated in InfraBIM and other domains, to stimulate
discussion on the needs and objectives of MIM&TIM
development, and to explore the possibilities, capabilities
and general will to start drafting the development steps
of MIM&TIM concepts.
The workshops were carried out, processed, and
reported by the University of Oulu, Research Unit of
Civil Engineering and Civil Engineering, Digital
Construction and Mining Research Area. The workshop
series covered six main topics, such as 1) Modelling
Guidelines, 2) Information Classification, 3) Data
Transfer Formats, 4) The use of building information
models in work machine automation, 5) The real-time
cloud services of the MIM&TIM process and 6)
Organizing models of MIM&TIM future development.
A total of 107 people participated in at least one of
the six workshops out of a total of 235 invited people. A
total of 54 companies or organizations participated out of
a total of 84 invited companies. Throughout the
workshop series, online and email surveys were utilized
as the most important research tools. A total of 52 BIM-
related orientation presentations and numerous group
assignments were held in the workshops. Each workshop
was recorded and reported in writing with all the results.
For the research results, as much as possible of the
opinions and experiences of the participants were
collected from the workshops, which were then analyzed
and summarized by the authors.
3 Results
In the first workshop, the main theme was modelling
guidelines and the main topic was the definition of the
need for further research and development of the MIM
and TIM concepts in Finland.
The main research method was surveys that were
conducted before, during and after the actual workshop.
The preliminary survey was carried out several days
before the workshop using an on-line Webropol software
tool, which included five (5) questions related to the main
topics of the workshop.
In the actual workshop, the workshop participants
gave six (6) well-prepared orientation presentations,
which presented all workshop participants with ideas for
general BIM and InfraBIM modelling guidelines. After
these presentations, a groupwork section was organized
with 22 questions using an online Mentimeter software.
A total of 53 people from 30 different companies or
organizations participated in the workshop. After the
workshop, the feedback survey was carried out a few
days later using an online Webropol software tool, which
included two (2) questions related to the main topics of
the workshop.
A total of 29 questions were asked about the main
topics and a total of 569 responses were given to these
questions. The results obtained from the participants’
contribution to these questions were carefully analyzed
and compiled in a separate workshop report. The results
are summarized by the author in the following sections
3.1-3.3.
3.1 BIM concept in mining
The workshop participants were asked how well the
BIM concept would be suitable for mining. The
following types of responses were derived and compiled
from the participants’ responses.
“In Finland, the mining and tunnelling sectors lack a
uniform BIM modelling approach. Only minor examples
of the implementation of BIM in tunnelling can be found.
In the global scale, the tunnelling sector has a maturing
BIM approach, but a similar one has not yet been found
in the mining sector.”
Here are some of the participants’ comments on the
further development of the MIM concept in the mining
sector.
•“BIM is a megatrend – a trend that is pointless to
try to stop.”
•“Digital tools and systems developed for BIM
enable the further development of many other areas.”
•“Now is just the right time to move forward with
MIM in the mining and tunnelling sectors.”
•“There is strong support for the idea of
standardizing BIM in the mining and tunnelling
sectors.”
3.2 Current MIM status
The workshop participants were asked what kind of
capabilities are in the MIM implementation. The
following types of responses were derived and compiled
from the participants’ responses.
“The level of BIM expertise may not yet be very
extensive in the mining and tunnelling sector in Finland.
The mining and tunnelling sector definitely has an
interest in starting preparations and research activities in
this area. The possibilities and capabilities of BIM have
already been clearly identified.”
“The use of BIM in other domains has mainly focused
only on the first stages of the entire process chain 1)
Initial data, 2) Design and planning and 3) Construction.
The implementation has not yet had time to extend
extensively to the latter part of the process chain, like 4)
Maintenance, 5) Production, 6) Termination of
operations and 7) Aftercare. The Initial data and Design
and planning process stages are strengths in the current
Finnish InfraBIM modelling guidelines. The identified
specificities of the mining and tunnelling sectors indicate
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that there are significant needs for change and
development towards the end of the process compared to
the current guidelines.”
“There are already some preliminary and very limited
guidelines for the mining and tunnelling sectors, but they
are not widespread. There are no actual uniform or
common model naming conventions. There are some
specifications for geological rock type and characteristics,
data produced and processed in the mine’s production
process and machine utilization, and rock support data.
The mining and tunnelling sectors are characterized by
longer time horizons and lower, not millimeter scales,
accuracy requirements compared to other BIM domains.”
“From a software perspective, national capabilities
for BIM-based information management work have
already been developed to reasonable level in other BIM
domains. The number of suitable software applications
remains very limited in the tunnelling sector, and in
particular in the mining sector.”
3.3 Expectations for the MIM
The workshop participants were asked what their
expectations are for MIM development. The following
types of responses were derived and compiled from the
participants’ responses.
“The potential of different BIM solutions is perceived
as significant. BIM is seen to be needed in many different
mining and tunnelling solutions, which enables savings
and brings added value to all parties. MIM is seen as an
opportunity for high-quality mining, where geological
data can be utilized by mining machines in different work
phases smoothly together with the material flow,
ensuring all interfaces and specifications along the way
to the concentrator. It is seen to as useful, especially when
looking for a new direction and taking advantage of new
opportunities.”
“Expectations for MIM development are emphasized
by the importance and relevance of cooperation in order
to achieve a better outcome through common
specifications and established standards. The general
need for additional knowledge and learning related to
MIM is great. The potential of various BIM solutions in
the mining and tunnelling sector is considered to be very
high.”
“Current modelling guidelines for the building
construction and InfraBIM sector can also be applied to
the mining and tunnelling sectors. However, due to the
peculiarities of mining and tunnelling, the need for
changes is estimated to be quite large. Creating new
modelling guidelines, and at the same time coordinating
old practices in the existing operations will be a challenge.
The mining and tunnelling sectors are also likely to need
two modelling guidelines, one for each sector separately.
However, it may be worth evaluating this in more detail
during the actual phase of creating the guidelines and also
possibly making use of modularity, for example. In the
mining sector itself, two separate guidelines may also be
required, considering UG and OC mining. The mining
and tunnelling sectors should develop modelling
guidelines that are as consistent as possible. Expertise
may already exist in other BIM domains and especially
in the construction and built infrastructure sectors, and
this know-how must be utilized.”
4 Next steps
Suggestions of the author of this paper for the next
steps MIM development are presented in the following
sections 4.1-4.2.
4.1 MIM development
The InfraBIM domain has already reached a high
level of BIM maturity in Finland. However, the
information classification in the mining sector is quite
specific, and therefore the current terminology in the
InfraBIM sector should be revised very closely if
necessary. The current GeoBIM references would also be
useful in defining, for example, solid modelling of ores
and other formation rocks, as they are not included in the
InfraBIM guidelines.
Further development of MIM’s modelling guidelines
may be based on the existing InfraBIM guidelines.
Where necessary, they should only be adapted to the
specific needs of the mining and tunnelling sectors. It is
also clear that GeoBIM guidelines must be included in
the overall picture of this future BIM domain.
The actual preparation of MIM guidelines should take
place in a separate development project. One good
possibility would be a co-innovation project involving
key experts and actors from different fields. Similarly,
development trends in international BIM domains must
be taken into account as part of the creation of new
guidelines and classifications.
It would also be important to start general
international standardization work and/or creation of a
White Paper on MIM development. Significant advances
in information modelling in mining are most likely to be
developed and implemented through a collaborative,
multi-party approach and coordinated by an industry-
centric steering group. Industrial cooperation is very
critical because the technical challenges are extensive
and outside any single entity to be solved.
4.2 MIM guidelines
In Finland, the buildingSmart Finland organization is
the controlling unit of all specifications related to BIM.
The InfraBIM sector has had very good modelling
guidelines since 2013.
The author of this paper made a rapid study and a
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preliminary proposal to assess the need to make possible
changes to the current outline of these guidelines if they
were applied and implemented in the mining and
tunnelling sectors. The proposal was presented and
discussed among the workshop participants. It was found
that, in fact, little change is needed to the current outline
in order to be better suited and to fill in the gaps in the
needs of the mining sector. A preliminary proposal for
modelling guidelines for the mining sector is presented
in Figure 5.
Figure 5. The main content of the MIM modelling
guidelines
The first three headings, which include 1) General
matters, 2) Initial data and 3) Design and planning, are
also very suitable for the mining sector. The fourth
heading in the InfraBIM guideline, Construction, should
be looked at in more detail. In the mining sector, it should
be opened up more widely 4) General preparatory
tunnelling, which would also cover all other tunnelling
work in the mine. Also, for the production phase of the
actual mine, 5) Excavation and production section, would
include all issues related to mining. Finally, 6) Mine
closure and afterwork section, would describe all the
necessary details of the post-production period. Similar
comparisons and suggestions were also made to all
subtitles of the InfraBIM guidelines to make them more
suitable for the mining sector. However, the results of the
these are not presented in this paper but are available
from the author.
5 Conclusion
Mines and tunnelling work sites need to work with
enormous amounts of data, coming from many different
sources like humans, machines, and surrounding
environment. Data can be located in many different
places at the same time. In the mining sector, 3D-
modelling, data management and mine automation are
still mainly handled separately. Both the mining and
tunnelling sectors lack a unified information modelling
methodology for converting physical mining
infrastructure into digital infrastructure for machine
control.
Various BIM domains have developed very rapidly in
recent years and clear benefits have been reported from
many industries. InfraBIM, GeoBIM and TIM domains
have been continuously developed internationally. The
mining sector does not yet have a common OpenBIM
derived approach.
Numerous questions were asked in the workshops
held in Finland, and the author has analyzed and
summarized the results obtained from the contribution of
the participants. Based on the results, it was concluded
that now is the right time to move forward with MIM in
the mining and tunnelling sector. The potential of various
BIM solutions was considered significant. BIM is seen to
be needed in many different mining and tunnelling
solutions, which enables savings and brings added value
to all parties. However, specific features have been
identified in the mining and tunnelling sectors which
indicate that the current guidelines need to be further
developed significantly.
A preliminary proposal for the main outline of the
MIM guidelines was presented and discussed. Further
development of MIM’s modelling guidelines could well
be based on the existing InfraBIM guidelines. There is
strong support for the idea of standardizing BIM in the
mining and tunnelling sectors. The need to start
researching and further developing the MIM concept in
future development projects was identified. It would also
be important to start general international standardization
work on MIM.
CRediT authorship contribution statement
Jyrki Salmi: Conceptualization, Methodology, Writing,
Review & Editing. Rauno Heikkilä: Conceptualization,
Methodology, Writing, Review & Editing.
Declaration of Competing Interest
The authors declare that they have no known competing
financial interests or personal relationships that could
have appeared to influence the work reported in this
paper.
Acknowledgments
The presented work has been supported by the Next
Generation Mining project, funded by Business Finland
and led by Sandvik and Nokia. The authors thank you
gratitude for your support.
References
[1] Barnewold L. and Lottermoser B.G. Identification
of digital technologies and digitalisation trends in
the mining industry. International Journal of Mining
Science and Technology, 30:747–757, 2020.
40th International Symposium on Automation and Robotics in Construction (ISARC 2023)
440

https://doi.org/10.1016/j.ijmst.2020.07.003
[2] Koch C., Vonthron A. and König M. A tunnel
information modelling framework to support
management, simulations, and visualisations in
mechanised tunnelling projects. Automation in
Construction, 83:78-90, 2017.
https://doi.org/10.1016/j.autcon.2017.07.006
[3] Huang M.Q., Ninic J and Zhang Q.B. BIM,
machine learning and computer vision techniques in
underground construction: current status and future
perspectives. Tunnelling and Underground Space
Technology, 108:103677, 2021.
https://doi.org/10.1016/j.tust.2020.103677
[4] Willmott A. Accenture mounts case for mining’s
digital shift. Mining Journal, Staff reporter inter -
view 2016. On-line: https://www.mining-
journal.com/leadership/news/1171901/accenture-
mounts-mining%E2%80%99-digital-shift.
Accessed: 13/01/2023.
[5] Slansky D. Sight Machine Enables Operational
Intelligence with the Digital Twin, ARC Advisory
group, ARC view, 2017. On-line:
https://www.arcweb.com/blog/sight-machine-
enables-operational-intelligence-digital-twin.
Accessed: 13/01/2023.
[6] Li W., Li S., Lin Z. and Li Q. Information modeling
of mine working based on BIM technology.
Tunnelling and Underground Space Technology,
115:103978, 2021.
https://doi.org/10.1016/j.tust.2021.103978
[7] Mitchell J. and Parken D. National Guidelines for
Digital Modelling, CRC Construction Innovation.
On-line: http://www.construction-
innovation.info/images/pdfs/BIM_Guidelines_Boo
k_191109_lores.pdf, 2009. Accessed: 13/01/2023.
[8] Eastman C.M., Jeong Y.-S., Sacks R. and Kaner I.
Exchange model and exchange object concepts for
implementation of national BIM standards. Journal
of Computing in Civil Engineering. 24 (1), 2010.
DOI: 10.1061/(ASCE)0887-3801(2010)24:1(25)
[9] Chen L., Shi P., Tang Q., Liu W. and Wu Q.
Development and application of a specification-
compliant highway tunnel facility management
system based on BIM, Tunnelling and Underground
Space Technology, Volume 97, 103262, 2020.
https://doi.org/10.1016/j.tust.2019.103262
[10] Hegemann F., Stascheit J. and Maidl U. As-built
documentation of segmental lining rings in the BIM
representation of tunnels, Tunnelling and
Underground Space Technology, 106:103582, 2020.
https://doi.org/10.1016/j.tust.2020.103582
[11] Borrmann A., König M., Koch M. and Beetz J.
Building Information Modeling: Technology
Foundations and Industry Practice. Springer, 2018.
https://doi.org/10.1007/978-3-319-92862-3
[12] Smith S. Building information modelling – moving
forward Crossrail, UK, forward. Proceedings of the
Institution of Civil Engineers – Management,
Procurement and Law, 167(3):109-159, 2014.
https://doi.org/10.1680/mpal.13.00024
[13] Daller J., Zibert M. Exinger C. and Lah M.
Implementation of BIM in the tunnel design –
Engineering consultant’s aspect. Geomechanics and
Tunnelling 9(6):674-683, 2016.
https://doi.org/10.1002/geot.201600054
[14] Fraser S. Beyond Mine Automation: The Rock
Factory and The Common Mine Model. First
International Conference on Minerals in the
Circular Economy, 2014. On-line:
https://publications.vtt.fi/pdf/technology/2014/T19
2.pdf . Accessed: 13/01/2023.
[15] Cunningham J., Fraser S.J., Gipps I.D., Widzyk-
Capehart E., Ralston J.C. and Duff E.F.
Development and future directions in mine-site
automation. AusIMM Bulletin, April 2012. On-line:
https://www.researchgate.net/publication/2603409
12_Development_and_future_directions_in_mine-
site_automation . Accessed: 13/01/2023.
[16] Gipps I., Cunningham J., Fraser S. and Widzyk-
Capehart E. Now to the Future – A Path Toward the
Future Mine. In proceedings of the Second
International Future Mining Conference, pp 157-
162, Melbourne, Australia, 2011.
http://hdl.handle.net/102.100.100/105341?index=1
[17] Wang L. and Zhang H. Discussion on Lifecycle
Management of Mine Construction Based-On
Mining Information Model. International
Conference on Internet Technology and
Applications, pp. 1-4, 2010. DOI:
10.1109/ITAPP.2010.5566392
[18] Wang J., Bi L., Wang L., Jia M-T., Mao D. A
Mining Technology Collaboration Platform Theory
and Its Product Development and Application to
Support China’s Digital Mine Construction.
Applied Sciences 9(24):5373, 2019.
https://doi.org/10.3390/app9245373
[19] Du X., Yi L, Lu X and Ji J. Overview of Digital
Mine, Information Technology Journal, 9(6):1241-
1245, 2010. DOI: 10.3923/itj.2010.1241.1245
[20] Fabozzi S., Biancardo S.A., Veropalumbo R. and
Bilotta E. I-BIM based approach for geotechnical
and numerical modelling of a conventional tunnel
excavation, Tunnelling and Underground Space
Technology, 108:103723, 2021.
https://doi.org/10.1016/j.tust.2020.103723
[21] Yleiset Inframallivaatimukset YIV. On-line:
https://drive.buildingsmart.fi/s/9mFGPHLx49KaM
24?dir=undefined&path=%2F2021&openfile=573
8. Accessed 13/01/2023.
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