an inventory of r elevant ict capabilities at south … down under an inventory of r elevant ict...
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MINERALS DOWN UNDER
An Inventory of Relevant ICT Capabilities at South Australia’s Universities
A Report commissioned by CSIRO and undertaken by the Ian Wark Research Institute as part of the South Australian Roadmap for Information and Communications Technologies in Minerals and Energy
June 2013
South Australian Roadmap for Information and Communication Technologies in Minerals and Energy
An inventory of relevant ICT capabilities at South Australia’s universities
Project Number PG 081253
Prepared for Commonwealth Scientific and Industrial Research Organisation – Minerals Down Under National Research Flagship (MDU) Box 312 Clayton South Vic 3169
Attention Dr Stephen Giugni, Deputy Director, MDU
Prepared by Professor Bart Follink
With contributions from Professor Jonas Addai-Mensah
Professor Bill Skinner
Date of Issue: 18 June 2013
This research was supported by the Flagship Collaboration Fund, which was
established to support collaborative activities with the CSIRO National Research
Flagships Program. The fund provides support for CSIRO to access external
capability to assist in solving specific science problems, develop expertise for CSIRO
and its partners and to build collaborative partnerships. The project was undertaken
for the Minerals Down Under Flagship which is delivering science and technology
options for the discovery and efficient development of Australia’s mineral resource
endowment that will lead to $1 trillion in-situ value by 2030 and enable flow-on
benefits to the wider national economy.
Important Notice This report applies only to the subject of the project. This report is confidential and was prepared exclusively for the client named above. It is not intended for, nor does the University of South Australia accept any responsibility for its use by any third party. This report consists of one cover page and 23 pages of text and figures.
Ian Wark Research Institute
ARC Special Research Centre
Minerals and Materials Science –
Nanotechnology – Interfaces
Director
Professor Magnus Nydén
Deputy Director
Professor Hans Griesser
Mawson Lakes Campus
Mawson Lakes
Adelaide SA 5095
Australia
t +61 8 8302 3694
f +61 8 8302 3683
www.unisa.edu.au/iwri
Australian Research Council
Special Research Centre for
Particle and Material Interfaces
CRICOS Provider Number 00121B
CONTENTS
Executive Summary of findings 1
1. Introduction 3
2. Approach 3
3. General observations 4
4. Capability groupings – What have we got? 6
5. Present initiatives in Minerals and Energy space
– What are we doing with it? 12
6. Future opportunities for capabilities
– What else could we be doing in M&E space? A number of scenarios 13
7. Preliminary gap analysis
– What would we still need to develop to achieve opportunities? 18
8. What are the research opportunities? 18
9. What’s next? - Follow up actions 19
10. Conclusions 19
Appendices
1. Organisational units in the SA university system with relevant ICT capabilities 20
1
Executive Summary
During the course of this study, from late January until May 2013, over 20 university executives and leading
scientists at the three South Australian universities and a number of other important Information and
Communication Technology (ICT) capability holders (particularly in the defence domain) were interviewed.
In discussions with the university leadership at the Chancellor, Vice-Chancellor /Pro Vice-Chancellor levels,
strong support for the initiative was evident.
Our study identified a broad range of strong relevant ICT capabilities, which, with a few minor exceptions
are not presently employed in the mining and energy space.
These ICT capabilities generally fall within the following categories:
o Sensors, sensor networks
o Autonomous vehicles, robotics
o “Management Systems”
� Logistics
� Engineering / design
� Decision support systems
o “Big Data” (unstructured data, analysis of multiple large data sets, etc.)
o Augmented reality, image processing / analysis
The main minerals sector “domain knowledge” exists at University of Adelaide (Institute for Mineral and
Energy Resources) and University of South Australia (The WarkTM).
Three potential applications (a systems approach to mineral processing, smart heap leaching, and a fully
automated remote operation) are used to guide a preliminary gap analysis, leading to the following
observations and conclusions:
• The necessary ICT capabilities and applications knowledge are well represented in the State’s
university community
• ICT research and development relevant for the Minerals and Energy domain in South Australia is
represented by an estimated 250 academics and 250 postgraduate students
• Almost 300 staff and 150 students are working in the Minerals and Energy domain and closely
related fields
• Convincing ICT-based demonstrator projects and proven capability for the different ICT capability
holders to work together in the minerals and energy sectors are largely lacking in the state
• There exists a “credibility gap” rather than a capability gap in the ICT for Minerals and Energy space
in South Australia
A strong science and technology ICT capability base and minerals and energy domain knowledge exist in the
university community in South Australia, a perfect starting position to propel Adelaide to the status of a
vibrant ICT research services hub for the minerals and energy industries.
It was somewhat surprising to find that the strong ICT capability at the State’s universities are at present
barely applied to the mineral and energy sectors, of which good , extensive application knowledge exists at
UniSA and University of Adelaide.
2
Coordination of the relevant activities within the universities (ICT capabilities and domain knowledge) and
close, coordinated interaction with the ICT industry, in particular through the AIIA, are seen as essential
steps towards achieving the vision of establishing Adelaide as a vibrant global hub for ICT services to the
mineral and energy sectors.
3
1. Introduction
It has long been recognised that the Minerals and Energy sectors could benefit greatly from applying
Information and Communication Technologies (ICTs) to their businesses. Some of the major and more
innovative players in minerals and energy have started doing this with significant success. Further roll-out
of implementation of ICT would lead to increased productivity through efficiency of business processes,
such as logistics and supply chain management, process automation and control, increased safety – e.g. by
allowing the removal of operators from dangerous locations, and decrease in environmental impact,
through better controlled processing. Overall this can lead to significantly improved performance of the
sector.
The minerals and energy sector has not been a pioneer in applying ICT skills and resources in their
businesses. Many of the skills in ICT have been specifically developed for the “forerunners” in the
economy, such as the manufacturing, retail, health and banking sectors, and –importantly – the defence
sector. Over the last few years, however, some impressive examples of implementation of ICT in the sector
have been seen (e.g. Rio Tinto’s “Mine of the FutureTM” program).
As recognised by the South Australian State Government, there now exists an opportunity to direct ICT
capabilities to the minerals and energy sectors, thereby innovating the industry (in the State and at large)
and triggering the growth of dedicated small and medium size enterprises in the ICT industry sector.
The present report deals with a “stocktake” of Research and Development capabilities in the ICT space in
South Australia, predominantly at the State’s three universities: University of Adelaide, University of South
Australia and Flinders University.
2. Approach
The approach chosen was to build a broad understanding of the spectrum of ICT capabilities and their
current application domains by interviewing leading researchers at the three universities. In most cases,
initial interviews at the individual universities were at the highest levels of university hierarchy, at
Chancellor, Vice-Chancellor and Pro Vice-Chancellor (Research) levels. These high-level interviews ensured
organisational context and support of the exercise and helped identify the universities’ leading scientists
relevant for the present study, who were subsequently interviewed during the course of the exercise.
For the purpose of the present stocktake, an initial and orientational round of interviews, “ICT” was
interpreted quite broadly. It included researchers in the ICT space per-se (mathematical and computer
science based), but also extended to scientists in closely related areas of research, such as sensor
development and medical devices.
The first round of interviews also covered leading scientists from the minerals and energy research field
with a view to capturing their vision for ICT-driven innovations in the sector. These interviews were
conducted mainly at the University of Adelaide (Institute for Mineral and Energy Resources) and UniSA (The
WarkTM).
Generally, interviews were scheduled to last one hour. In a number of cases, interviews were followed by a
tour of the experimental facilities.
4
Interviews were conducted in a free-flow format. After a brief introduction of the South Australian
Roadmapping exercise and the role of the present sub-project, interviewees were asked to briefly
introduce their organisational units, their development or usage of ICT capabilities, the main application
areas of their research and their main customers. Specific emphasis was placed on the existence of
interactions with companies in the SME sector. Brief (verbatim) notes from all interviews can be found in
Appendix 2 (CSIRO report only).
This present study is part of a larger initiative aimed at developing a roadmap for ICT for Minerals and
Energy Resources undertaken by the Minerals Down Under National Research Flagship and Deloitte. This
project is carried out under the auspices of the Department for Manufacturing, Innovation, Trade,
Resources and Energy (DMITRE) of the South Australian Government working with its industry partner, the
Australian Information Industries Association (AIIA) and is aimed to establish Adelaide as a vibrant global
hub for ICT services to the mineral and energy sectors.
3. General observations
An important general observation is that, without any exception, all of those interviewed were strongly
interested in the roadmapping initiative and very cooperative and enthusiastic participants in the
interviews.
As a key outcome it was observed that only very few of the ICT groups worked on projects specifically
addressing the minerals and energy sectors. None of the ICT groups consulted had key initiatives underway
specifically for these sectors. Defence (followed at a distance by health and manufacturing) seemed to be
the present focus areas for ICT researchers in South Australia.
Extensive domain knowledge and application know-how exists in the State, predominantly at the Institute
for Mineral and Energy Resources (University of Adelaide) and The Wark (UniSA). Historically, there seems
to have been a significantly stronger emphasis on minerals than on energy.
In the institutes dealing with mining sector research (Institute for Mineral and Energy Resources and The
Wark) there exist a number of fairly advanced ideas about innovations that can be brought about in the
sector through the application of ICT capabilities. Examples presented include ore sorting, advanced heap
leaching, use of “Big Data” to unravel key factors driving the performance of process steps and entire
operations, etc.
At the overview level and to assist the initial analysis undertaken in this report, it is useful to categorise ICT
capabilities into a number of main groupings. Before doing so, to assist the non-ICT expert reader, a
glossary of some simplified basic definitions for the key capability categories (mainly sourced from
Wikipedia) as used in this report are given below.
Augmented reality is a live, direct or indirect, view of a physical, real-world environment whose elements
are augmented by computer-generated sensory input such as sound, video, graphics or GPS data.
Autonomous vehicles sense their surroundings with such techniques as radar, lidar, GPS, and computer
vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as
well as obstacles and relevant signage.
5
Types:
• Unmanned ground vehicle (UGV), such as the autonomous car
• Unmanned aerial vehicle (UAV), unmanned aircraft commonly known as a "drone"
o Unmanned combat air vehicle
• Unmanned surface vehicle (USV), for the operation on the surface of the water
• Autonomous underwater vehicle (AUV) or unmanned undersea vehicle (UUV), for the operation
underwater
• Unmanned spacecraft, both remote controlled ("unmanned space mission") and autonomous
("robotic spacecraft" or "space probe")
Sensors (also called detectors) are converters that measure a physical quantity and convert it into a signal
which can be read by an observer or by an (today mostly electronic) instrument.
A wireless sensor network consists of spatially distributed autonomous sensors to monitor physical,
chemical or environmental conditions, such as temperature, sound, pressure, composition etc. and to
cooperatively pass their data through the network to a main location. The more modern networks are bi-
directional, also enabling control of sensor activity.
Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand
database management tools or traditional data processing applications. The challenges include capture,
curation, storage, search, sharing, transfer, analysis, and visualization.
Artificial intelligence is technology and a branch of computer science that studies and develops intelligent
machines and software. Major AI researchers and textbooks define the field as "the study and design of
intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions
that maximize its chances of success.
(Management) Information systems is the study of complementary networks of hardware and software
that people and organizations use to collect, filter, process, create, and distribute data. The study bridges
business and computer science using the theoretical foundations of information and computation to study
various business models and related algorithmic processes within a computer science discipline.
Information Systems aim to support operations, management and decision making.
Image processing is any form of signal processing for which the input is an image, such as a photograph or
video frame; the output of image processing may be either an image or a set of characteristics or
parameters related to the image. Most image-processing techniques involve treating the image as a two-
dimensional signal and applying standard signal-processing techniques to it.
Telecommunications network is a collection of terminal nodes, links and any intermediate nodes which
are connected so as to enable telecommunication between the terminals. The transmission links connect
the nodes together. The nodes use circuit switching, message switching or packet switching to pass the
signal through the correct links and nodes to reach the correct destination terminal. Each terminal in the
network usually has a unique address so messages or connections can be routed to the correct recipients.
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The collection of addresses in the network is called the address space. Examples of telecommunications
networks are:
• computer networks
• the Internet
• the telephone network
• the global Telex network
• the aeronautical ACARS network
Robotics is the branch of technology that deals with the design, construction, operation, and application of
robots, as well as computer systems for their control, sensory feedback, and information processing. These
technologies deal with automated machines that can take the place of humans in dangerous environments
or manufacturing processes, or resemble humans in appearance, behaviour, and/or cognition. Many of
today's robots are inspired by nature contributing to the field of bio-inspired robotics.
Simulation science deals with the imitation of the operation of a process or system over time. Simulating a
process requires that a model be developed; this model represents the key characteristics or
behaviours/functions of the selected physical or abstract system or process. The model represents the
system itself, whereas the simulation represents the operation of the system over time. Most relevant for
the present study, simulation is used for technology for performance optimization, safety engineering,
testing, training, and education. Key issues in simulation include acquisition of valid source information
about the relevant selection of key characteristics and behaviours, the use of simplifying approximations
and assumptions within the simulation, and fidelity and validity of the simulation outcomes.
4. Capability groupings – What have we got
The following main groupings of ICT capabilities are represented at South Australia’s universities:
• Management systems (logistics, engineering, design),
• autonomous vehicles and robotics, augmented reality (including image processing and analysis),
sensors (and actuators) and sensor networks,
• “Big Data”, including data analysis, statistics and mathematics,
• (tele)communications
We found that the relevant capabilities at the three South Australian universities are generally
concentrated in a limited number of organisational units (see Table 4.1), which makes coordination of
input for the ICT Roadmap and discussions on potential scenarios and gap analyses relatively
straightforward to coordinate. Table 4.1 displays ICT capabilities relevant for Minerals and Energy at South
Australia’s three universities (for meaning of acronyms see Appendix 1)
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Table 4.1 Institutional homes of ICT capabilities relevant for Minerals and Energy capabilities at
South Australia’s universities Institute1 Key contact Relevant ICT Capability comments
U Adelaide IMER Prof Stephen
Grano
Minerals and Energy application
knowledge
IPAS Prof Tanya
Monro
Optical sensing
TRC Dr Bruce
Northcote
Networking/communications
Risk management
ACVT Prof Anton
van den
Hengel
Image processing
Image analysis
UniSA DASI Prof Anthony
Finn
Robotics
IT Systems engineering
School of
ITMS
Prof Andy
Koronios
Image processing
Modelling and scheduling
Artificial intelligence
Augmented reality
Three relevant
Centres (ACRC,
CIAM, PBRC)
ITR Prof Alex
Grant
Satellite and terrestrial communications
Vehicle-to-vehicle communication
Sensor network algorithms
Wark Prof Magnus
Nyden
Mineral Processing application
knowledge
Systems approach
Flinders CNST Prof David
Lewis
Nano devices
School of
CSEM
Prof John
Roddick
Autonomous vehicles
Data mining
Civil engineering for resources industry
MDRI Prof Karen
Reynolds
Remote sensing
Simulation science
Signal and image analysis
Medical Device
Partnering Program
for SME interaction
Collaborative
Research
Institutes
DSIC Dr Sanjay
Mazumdar
Application in
System of Systems
Systems modelling
Information superiority (data mining)
Entity recognition
Coordinating D2D
CRC bid
DET CRC Dr Richard
Hillis
Application of ICT to deep drilling and
exploration geology
Interviewed by
Susan Andrews,
DMITRE
eResearch
SA
Mary Hobson High-Performance computing
Cloud computing
Software development
Data management and sharing
Collaborative joint
venture University of
Adelaide, Flinders
University and UniSA
DSTO Dr Warren
Harch
Cyber
Surveillance and Space systems
Autonomous systems
Information systems
Operations analysis
Interviewed jointly
with Dr Don Bursill,
SA Chief Scientist
1 For the full name of the institutes/centres, see Appendix 1
8
A brief description of the most relevant groups follows below, organised by university, with an emphasis on
their capability sets, main application areas, and capacity (in terms of staff numbers and graduate
students). A more detailed verbatim reflection of the interviews can be found in Appendix 2 (CSIRO report
only).
4.1 University of Adelaide
4.1.1 Institute for Minerals and Energy Resources (IMER) - www.adelaide.edu.au/imer/
Director: Prof Stephen Grano. Three Centres: Centre for Energy Technology, South Australian Centre for
Geothermal Energy Research, Centre for Tectonics, Resources and Exploration. Three Research Programs:
Resource Engineering, Socio-Economic Impact of Mineral and Energy Resource Development,
Environmental Impact of Mineral and Energy Resource Development. Three related CRCs at UA: CRC for
Greenhouse Gas Technologies, Deep Exploration Technologies CRC, Energy Pipelines CRC.
About 220 staff, including 5 senior academics and 80 PhD/MSc students
4.1.2 Institute for Photonics & Advanced Sensing (IPAS) - www.adelaide.edu.au/ipas/
Director: Prof Tanya Monro. Five key market areas: Defence and national security, Environmental
monitoring, Preventative health, Food and wine, Mining.
About 190 staff, including ca. 90 postgraduate students
4.1.3 Teletraffic Research Centre (TRC) - www.trc.adelaide.edu.au/
Director: Dr Bruce Northcote. Problem domains: Optimal resource allocation, Assembly line scheduling,
Futures pricing – electrical markets, Water flow analysis, Real-time control systems.
About 14 academic staff and 4 postgraduate students.
4.1.4 Australian Centre for Visual Technologies (ACVT) - www.acvt.com.au/
Director: Prof Anton van den Hengel. Capabilities: Context based image retrieval, Large-scale intelligent
video surveillance, Robust model fitting, Structure from image sets.
50+ staff and 22 postgraduate students.
4.1.5 eResearch SA - www.adelaide.edu.au/research/researchers/services/eresearch/
Director: Mary Hobson. Capabilities High-Performance computing, Cloud computing, Software
development, Data management and sharing. Collaborative joint venture between University of Adelaide,
Flinders University and UniSA.
4.2 University of South Australia
4.2.1 Ian Wark Research Institute (The Wark) - www.unisa/research/ian-wark-research-institute/
9
Director: Prof Magnus Nyden. Three Research Sectors: Bio and polymer interfaces, Colloids and
nanostructures, Mineral Processing.
73 academic staff and 65 postgraduate students
4.2.2 Defence and Systems Institute (DASI) - www.unisa/research/defence-and-systems-institute/
Director: Prof Anthony Finn. Themes: Systems modelling, simulation and analysis, Systems technologies and
applications, Systems methodologies, tools and techniques, Systems engineering frameworks.
About 22 staff and 20 postgraduate students
www.unisa/research/defence-and-systems-institute/
4.2.3 Institute for Telecommunications Research (ITR) - www.itr.unisa.edu.au/
Director: Prof Alex Grant. Focus areas: Satellite communications, Flexible radios and networks, High-speed
data communications, Computational and theoretical neuroscience laboratory.
About 35 staff and 30 postgraduate students
4.2.4 School of Information Technologies and Mathematical Sciences (ITMS)
Head of School: Prof Andy Koronios
4.2.4.1 Advanced Computing Research Centre (ACRC)
Director: Prof Markus Stumptner
Around 28 staff and 68 postgraduate students
4.2.4.2 Centre for Industrial and Applied Mathematics
Director: Prof John Boland. Themes: Mathematical analysis, Modelling of systems and processes,
optimisation and optimal control, Signal and image processing, Scheduling and control for transportation
and water management.
Around 18 staff and 23 postgraduate students
4.2.4.3 Phenomics and Bioinformatics Research Centre (PBRC)
Director: Prof Stan Miklavcic. Research Themes: Biometrics and statistics, Image analysis, Mathematical
modelling, Computational biology and bioinformatics.
Ca. 15 staff and 6 postgraduate students
4.3 Flinders University
4.3.1 School of Computer Science, Engineering and Mathematics (SCSEM) -
www.flinders.edu.au/science_engineering/csem/
Head of School: Prof John Roddick. Capabilities: Autonomous vehicles, Data mining, Civil engineering for
resources industry.
10
60 staff and 80 postgraduate students (numbers may include CNST and MDRI)
4.3.2 Centre for NanoScale Science and Technology (CNSST) -
ww.flinders.edu.au/science_engineering/nanoscale/
Director: Prof David Lewis. Capabilities: Chemical characterisation of surfaces, Chemical analysis, Surface
topography and shape. Research areas: Energy, Health, Security, Water.
About 12 staff and 45 postgraduate students
4.3.3 Medical Device Research Institute (MDRI) -
www.flinders.edu.au/science_engineering/research/mdri/home.cfm
Director: Prof Karen Reynolds. Capabilities: Assistive technologies, Biomechanics & implants, Health
informatics, Medical devices & instrumentation, Medical signals & imaging Medical simulation and
modelling.
Ca. 46 academic staff, 29 postgraduate students
4.4 Defence Science and Technology Organisation( DSTO) - www.dsto.defence.gov.au/
Deputy Chief Defence Scientist: Dr Warren Harch. ICT-related Capabilities: Cyber, Surveillance and Space
Systems, Autonomous Systems.
About 200 scientific staff in ICT domain.
The spread across the university network of the broader ICT capability groups that will form the main
building blocks on the roadmap are given in Table 4.2.
Table 4.2 Main capability groupings across university institutes and schools2
ICT capability grouping Represented at Comments
Communications DSIC, ITR, DSTO
Management systems TRC, DASI, ITMS
Autonomous vehicles /
Robotics
DASI, DSTO, CSEM
Sensors and sensor networks MDRI, IPAS, CNST, ITR, DET CRC
Augmented reality MDRI, ITMS, ACVT Includes image analysis
Big Data (incl. maths&stats) ITMS, DSIC, D2D D2D – new CRC bid
From the discussion thus far, it can be concluded that the capabilities relevant for the ICT in Minerals and
Energy Roadmap are generally well represented in South Australia.
2 for meaning of acronyms see Appendix 1
11
The University of Adelaide and the University of South Australia represent the bulk of science development
in these areas, whereas Flinders University makes significant contributions in relevant niche areas.
From figures quoted, we conclude that ICT capabilities in South Australia are certainly of a critical mass:
jointly within the three universities some 450 academic staff and almost 400 postgraduate students (PhD,
MSC and honours) are involved in ICT-related research. Even though there is the risk of some double-
counting (such as in the School of Computer Science, Engineering and Mathematics and its institutes (CNST
and MDRI)) and inclusion of staff and students involved in areas not directly related to ICT (such as in IPAS)
or in the minerals and energy domain (such as at The Wark, UniSA), these numbers show that South
Australia has a very significant concentration of academic ICT capability and expertise. It may be a safe
statement to conclude that ICT research directly relevant to the Minerals and Energy domain in South
Australia is represented by an estimated 250 academics and 250 postgraduate students at the state’s three
universities. Another potentially very powerful source of Minerals and Energy-relevant ICT capability is the
DSTO site at Edinburgh, SA, with about 2400 staff, of which at least 200 work in the relevant ICT domain,
often on applications that would be translatable to Minerals and Energy, such as communication,
autonomous vehicles, robotics, etc.
On the side of minerals and energy application research, the situation is similarly impressive: between IMER
at the University of Adelaide and The Wark at UniSA, almost 300 staff and 150 students are working in the
Minerals and Energy and closely related application fields (such as in interfacial research at The Wark).
From our observations, it seems that only limited interactions occur between the minerals and energy
domain knowledge holders and the potentially relevant ICT research nodes at the universities. We found
evidence of emerging dialogue between IMER and ICT experts in IPAS and ACVT at the University of
Adelaide regarding application of ICT expertise in ore sorting and exploration type of applications. At UniSA,
discussions have been initiated between The Wark and the School of Information Technologies and
Mathematical Sciences to jointly investigate the potential of a systems approach to mineral processing (a
concept developed by Prof Nyden) akin to systems biology.
From our interviews, it is evident that a small number of individual organisational units and individual
researchers in the ICT research space at all universities do have (limited) interactions with companies in the
minerals and energy sectors. Those examples are briefly discussed in the next Section. The vast majority of
industry sector interactions are conducted through the “domain institutes” IMER and Wark, respectively.
These interactions are mostly exploration, mining and processing oriented, rather than ICT centric.
It was interesting to note that a number of cross-organisational initiatives, such as CRCs and inter-university
collaborations, with relevance to the ICT Roadmap are starting to emerge. Examples are the Deep
Exploration Technologies CRC (headquartered in Adelaide!) and the Defence Systems Innovation Centre.
The latter organisation is finalising a bid for a Data to Decisions CRC. This CRC, if successful, is also likely to
be headquartered in Adelaide. Another strong point is the prominent presence of DSTO in Adelaide,
representing a wide range of relevant strong ICT capabilities.
Given this favourable state of affairs, there now exists an excellent opportunity for a fruitful discussion
aimed at coordination around the ICT for minerals and energy opportunity as a key focus area for the South
Australian ICT and Minerals and Energy research communities.
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5. Present initiatives in Minerals and Energy space – What are we doing with it?
During the present research, only a very limited number of examples of ICT-centric initiatives specifically for
the Minerals and Energy sectors were identified.
At the Institute for Mineral and Energy Resources (UA), algorithms are being developed and optimised for
interpreting electrical geophysical and seismic data. These algorithms are required to process large
amounts of geophysical data in applications such as sensing while drilling, monitoring changes in
unconventional energy resource extraction and permeability pathways in heap and in-situ leaching. This
computational expertise is complemented by one of the largest electromagnetic geophysics pools in the
world, based around the NCRIS Auscope MT facility.
IMER’s ICT expertise is also applied in mining applications. In particular, geostatistics expertise for
predicting distributions of ore grades in mining, which has resulted in a commercial package ‘GeoStatsWin’.
Expertise in financial evaluation and risk assessment of mining projects has also produced the commercial
software package ‘MINVEST’.
In the petroleum domain, there is a significant degree of ICT expertise with a long track record of working
closely with industry including 3D reservoir modelling and visualisation using the state-of-the-art South
Australian Virtual Reality Centre (SAVRC), fine particle transport in porous media and mathematical
modelling of well stimulation, as are highly relevant for hydrofracking technology (for unconventional
energy production).
Understanding fractures for enhanced extraction of unconventional energy resources is another key area of
expertise. Inputs to this include geomechanical modelling for predicting stress and natural fractures using
geomechanical simulations and 3D seismic data as applied in the GeoFrac project. Expertise in stochastic
rock fracture modelling has led to development of the software package FracSim3D, which can also be
applied in mining and mineral processing industries.
The University of Adelaide’s Institute for Photonics and Advanced Sensing, is using their expertise in
developing new sensors in current projects with DET CRC on down-hole sensors and on other projects for
mine face scanning and radiation sensing.
Prof van den Hengel, at the Australian Centre for Visual Technologies at the University of Adelaide has
worked on virtual reality safety training programs for the minerals industry. There are also preliminary
(academic) discussions underway with IMER on ore sorting concepts for the minerals industry.
At UniSA’s The Wark, under the leadership of the institute’s new director, recent discussions have focussed
on the need for a “systems approach” to mineral processing, where statistical-analytical methods are
employed on huge numbers of data collected throughout the process flow (sensors, sensor networks!). This
helps answer the “What (influences the process outcome)? - question”. This then helps ask the correct
“How (does it do that)? – question”, guiding the fundamental research direction into individual process
steps and critical physico-chemical phenomena.
In the Advanced Computing Research Centre (ACRC) at UniSA, Prof Stumptner is working on semantic data
management methods that provide interoperability between industrial software systems, creating large
flexible information ecosystems. He is currently involved in the international Oil & Gas Interoperability
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Pilot with partners IBM, Worley-Parsons, Bentley, AVEVA, and Assetricity, which promises major cost
savings for oil & gas operators. Similar techniques can be applied in the minerals and chemical process
industry (where the German DEXPI consortium is already studying the potential impact of such
technologies). The ACRC is also working on projects in the space of Big Data Analytics. All these techniques
are crucial to the "systems approach to mineral processing" described above.
Minerals and Energy relevant work is being done at eResearch SA, the South Australian provider of high-
performance computing, data management and storage, research collaboration, and visualisation services
for researchers in SA. It is a collaborative joint venture between the University of Adelaide, Flinders
University, and the University of South Australia. eResearch SA's mission is to support the development,
implementation and use of eResearch methodologies and activities, and to provide access to eResearch
facilities and practical support for researchers in South Australia. Based at the University of Adelaide's
Thebarton campus, eResearch SA provides facilities, services and expertise in (i) High-Performance
Computing to perform complex data processing and analysis jobs, (ii) Cloud Computing to publish research
data, share knowledge and rapidly deploy and access software applications, web services and scalable
computing resources, (iii) Software Development, and (iv) Data Management and Sharing managing more
than 400 terabytes of data storage.
As is clear from this chapter, there is only limited evidence of applications of the generally strong ICT
capabilities in academia in the State to problems in the mineral and energy sectors. This leads to what one
of the interviewees aptly called a “credibility gap”. There is presently not enough visible evidence in the
state that demonstrates that ICT and minerals and energy research can successfully work together for the
(quantifiable) benefit of these sectors. Future opportunities should ideally be positioned such that they
generate factual evidence that would demonstrate significant advantages for the industry of adopting ICT,
thus providing this badly needed credibility.
6. Future opportunities for capabilities – What else could we be doing in M&E space? Three
scenarios
For the purpose of a preliminary analysis of the current capability portfolio in the state, it seems useful to
map the portfolio against a number of medium-term (say, 5 – 10 years) scenarios.
In general it can be concluded that a much stronger and strategically guided interaction between the
“domain side” and the ICT capability holders in SA could lead to drastically increased ICT-based activity for
the minerals and energy sector. This would seem to be the case at the individual university level (stronger
interactions between IMER and the ICT focussed institutes at University of Adelaide, and between The
Wark and ICT capability holders at UniSA), but particularly so at an all-of-state level.
There is a clear role to play for each of the universities. Preferably through the existing domain centres,
they could position themselves as minerals and energy industry interfaces into the wealth of relevant
science and technology capability in the state. This would undoubtedly lead to a strongly increased
research effort specifically for the sector, which would in turn inspire the development and growth of small
and medium size ICT enterprises servicing the minerals and energy sectors.
By way of example, and for the purpose of a first, superficial analysis, three potential scenarios are
developed here. For a more appropriate, more detailed and fuller analysis, the scenarios developed by the
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Scenario Team within the scope of the overall South Australian Roadmap for Minerals and Energy project
will need to be used once available.
The three scenarios developed here are more or less randomly picked from the minerals space and
somewhat influenced by the present author’s experience and research interests. Many others are possible.
6.1 A systems (“omics”) approach to mineral processing
At The Wark, Prof Magnus Nyden is investigating the concept of Systems Mineral Processing (SMP), a
concept strongly anchored in ICT and mathematical statistics and inspired by recent decennial advances
made in Systems Biology. Pivotal to the SMP vision are (i) dramatically improved existing systems and
technologies and (ii) novel and innovative, game-changing mineral resources’ prospecting, procurement
and processing technologies. The vision reflects a paradigm shift where our minerals resources are
explored and mined in a more efficacious manner and processed in more sustainable and energy efficient
ways with minimum ecological footprint and high social acceptability. The SMP approach will lead to hugely
beneficial scientific and technological outcomes and significant economic competitiveness for Australia,
especially through IP ownership and licensing.
The approach is inter-disciplinary and highly ICT-dependent, focusing on resolution and integration of the
complex interactions between various facets of mineral resource mining, geo-metallurgy and related
mineral plant unit operations, including waste tailings management. As a holistic approach, SMP involves
the integration of relevant mineral ore characteristics, individual physical and chemical processes and unit
operations, their inter-dependency and the plant performance for prediction, optimisation and
maximisation of product yield and recovery. At CRC ORE and at the University of Adelaide, research is
underway to integrate geo-mechanical and fragmentation attributes of the ore into the resource model to
predict down-stream processing. There are correlations between the attributes with chemical composition,
allowing proxy measures to be used. As a cross-disciplinary sector, traditional expertise and skills of
practitioners/researchers from both industry and academia, such as geologists, mining engineers,
metallurgists, chemical/process engineers, chemists, electrical/electronic instrumentation engineers,
quality control engineers and environmental engineers, etc., feature in the equation. A key highlight of SMP
is the central roles of mathematical statistics and ICT envisaged in providing significantly improved sensing,
data gathering, treatment, correlation and deployment nexus and capabilities for enhanced process
modelling, monitoring and control, and optimum plant performance.
The SMP approach and strategy is based on data ‘mining’ and processing at three different hierarchical
levels. These will involve collection of ‘big representative data’ comprising both simple and advanced
physical and chemical data at three inter-connected, but different, levels of complexities, preferably on-line
and/or in real time. The execution process strongly relies on ICT capability in e.g. sensors and sensor
networks, telecommunications and mathematical statistics.
Level 1: This level of data may typically represent the most basic type of primary process variables and
diagnostic parameters obtained by sensor networks in the field and/or units (e.g., ore blasting
characteristics, run-of-mine ore crushed and ground size, mineralogy type, grade, and values liberation
data, process temperature, pH, ionic strength, viscosities, acid concentrations, and air bubble size and its
distribution). Extensive, in situ and ex situ, diagnostic characterisation and tools are required at this level.
Many of the primary variables may be judiciously adjusted to optimise parameters and performance
following the output from the process control unit.
Level 2: Parameters at level 2 are more complex physical and chemical parameters, indicative of the
mineral particle surface/interfacial behaviour (e.g., contact angle, wettability, surface expression of
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values/non-values). These will have profound impact on performance of unit operations (e.g., flotation,
smelting, pressure and atmospheric leaching of values). The level 2 parameters are largely determined by
the 1st level parameters / primary variables and their interactions. They mostly will require both in situ and
ex situ characterisation techniques
Level 3: These parameters are largely defined by both level 1 and 2 parameters, and as such are the most
complex. They may require state-of-the-art characterisation and quantification and modelling techniques in
order to obtain the relevant data to be fed into the process control unit. Due to the fundamental nature of
mineral resources, level 3 parameters are anticipated to convey information about molecular interactions
at mineral particle surfaces and interfaces.
Feed parameters: These parameter sets are determined by the nature of the ore and are generally input
parameters for the processing. They are for instance ore grade, surface characteristics, such as morphology
and surface chemistry. Particle size and particle size distribution following comminution are part of these
essential input parameters. Feed characteristics are also of the Big Data type and should preferably be
measured on-line and in real time.
SMP is envisaged to lead to the following outcomes:
1. Current technologies optimised for significantly improved plant operations and performance. These
include flotation, in-situ and heap leaching technologies.
2. Novel, innovative game changing technologies.
It is clear that the future success of SMP requires a strong, strategic collaboration between process
scientists and ICT experts from across a broad expertise domain (sensors, sensor networks, actuators,
communications, decision tools, computer engineers, mats and stats, etc.), both from within academia and
participating mineral companies.
6.2 Automated, “smart”, heap leaching operations
With Australia’s mineral resources becoming increasingly “complex” (lower in grade and with a more
distributed and intricate mineralogy), grinding to full liberation is becoming a difficult and extremely energy
intense process that cannot always be economically afforded, heap leaching operations are increasingly
becoming the process option of choice.
Such leaching operations are presently rather low-tech and unsophisticated. This has significant economic
advantages, both in capital and operating costs. However, heap leach operations are plagued by
performance uncertainty due, mainly, to a lack of detailed understanding of the complex interplay between
mineralogy, chemistry and geotechnical issues. Performance of a heap can be compromised by blockages
from fine particle build up (often resulting in waterlogging), non-uniformity of acid flow and permeation
through the heap (e.g. channelling) and collapse. Optimisation of the heap feed material is possible for
some operations (e.g. optimal crush, agglomeration, etc.), but hard to control for others. Valuable metal
extraction can be highly variable and extremely slow in many cases. Typical heaps can be run for up to, and
longer than, 12 months to achieve the required value metal recovery. Application of ICT has the potential of
fundamentally changing that situation, by turning leaching into a smart, high-tech, and tightly controlled
processing route for Australia’s minerals – both for building an understanding of heap leach mechanisms,
and maximising performance in real time.
How this might work is as follows. An ore heap is designed such that it is equipped with spatially distributed
multi-parameter sensors that measure, in real-time, parameters that are known to influence leaching
behaviour, such as temperature, pH, metal ion concentration, oxygen and CO2 levels, hydrostatic pressure,
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etc. The spatial and temporal Big Data thus collected by this sensor network are analysed in real time and
compared with sophisticated computer models of the heap operation, running in parallel, i.e. in, or close
to, real time. This generates sufficient information to provide a 3-dimensional monitoring capability of a
real heap, and to identify the location of problem “voxels” (of cubic metre dimensions) in the heap. This
“sensor net” approach identifies, at the very least, catastrophic heap failure very early in its operation. This
allows re-building of the failed heap, saving time and cost. If the failure is localised, the volume of material
responsible is either recycled and/or analysed as a mechanistic aid. The key components here are the
“sensor net” and the understanding and translation of the data produced, in the context of the chemistry
and geotechnical engineering. A “systems biology” approach to the sensor data, as described in 6.1, based
on a multivariate statistical treatment, is a vital ICT tool to enable real time process diagnostics. The use of
such sensors in trial heaps would certainly go a long way to building sufficient understanding of what makes
a good heap.
A first level target would be the development of robust, integrated multi-parameter sensor technology.
Many of the individual sensors are available or in development within South Australia, as is the Big Data
handling capability, solution/surface chemistry understanding and geotechnical expertise and modelling.
Initially, such sensors might be incorporated within physical “nets” lain across a heap at different depths
within it. One could imagine, eventually, that clusters of wirelessly-readable integrated sensors might be
randomly distributed as the heap is constructed. This would certainly be a long-term major challenge, but
success in fabricating such sensor probes would have spin-off applications in many industrial areas.
Levering off this approach would be the ability to react to changes and problems in an active heap leach.
Spotting a physical blockage or an excursion in solution chemistry is one advance - dealing with it adds a
second powerful level to the possibilities. A cleverly engineered system of transport lines and valves allows
for the (semi-continuous) spatial adjustment of process parameters, keeping the overall operation within
its optimal process window. Stimuli may simply involve the injection of air, complexant or additional acid.
Knowing the accurate location of a “problem voxel” in a heap also allows direct corrective action through
the injection of gases/liquids, e.g. via a manually operated “lance” apparatus.
A concept like this critically builds on a range of ICT capabilities – sensors and sensor networks, computer
modelling, communication strategies, decision systems, Big Data analysis, with a strong emphasis on
measurement and control.
A sensor-data analysis/model-diagnosis-process control-sensor cyclic approach, with built in statistical
analysis, may be extended to a range of other systems within the mining and mineral processing chain, e.g.
underground ore-sorting strategies (see also scenario 6.3), grinding/mineralogy relationships and flotation
processing.
6.3 Fully-automated, “No-people”3 operations
Adequate staffing of mining and energy and mineral processing facilities are a long-standing and critical
issue for the sectors. Reasons for this include the unattractiveness of working in remote locations and the
serious shortages of well-trained and qualified staff.
Additional reasons to strive for minimal personnel numbers close to the action at minerals and energy
production sites stem from the intrinsically dangerous nature of many of the tasks combined with a
generally hot and humid working environment. Health hazards like dust, chemical exposure and
3 Terminology borrowed from Dr Paul Heithersay, DMITRE
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operational health and safety risks are significant in any minerals and energy operation. The increased long-
term costs associated with increasingly-deeper underground operations are often a “showstopper” for
deposit development – particularly during periods of metal price volatility.
This leads to the notion that a fully automated, remotely controlled operation would be the ideal for the
future, although there will always need to be limited numbers of people somewhere on site, but not
exposed to dangerous activities. To achieve this ideal, it is obvious that ICT will need to make critical
contributions: remote control rooms, reliable and safe proprietary communication networks, sensors and
sensor networks, decision tools, robotics and autonomous vehicles all have critical roles to play.
In essence, a no-people scenario could look as follows. Remote control and augmented reality establish the
virtual control room of the no-people operation. Given reliable and safe customised communication
channels, this control room is located close to the major residential centres where people like to live. The
control room is continuously provided with real-time data from a range of chemical and physical sensors
and cameras distributed throughout the operation, sent across the customised communication network.
Decision support systems, virtual reality representations and big data analysis systems and software assist
remote operators to respond adequately to those signals. Through specific remotely controlled actuators
and robotic devices, the control is highly automated and virtually in real time.
At a more detailed level, a scenario based on automated, remotely controlled mineral operation could take
many forms. It could apply to open-pit as well as to under-ground mining, it could be limited to the down-
stream ore processing, or it could include the entire production chain from mining to final mineral
concentrate on a given site.
As an example, this scenario has the potential of generating significant innovations in a mining and mineral
processing operation and will assist in integrating the two (in remote locations).
At the level of the underground mining operation, in resource modelling and mine planning, during the
mining operation, sensors and on-line measuring devices provide data directly from the drill hole. These
data assist in the continuous upgrading and refinement of the resource model and mine plan. A vision for
DET CRC is to reduce drilling costs to allow extensive drilling for rapid resource definition using low cost,
low weight and highly automated drill rigs with extensive down-hole sensors and mini-chemical and
mineralogical laboratories on the rig. These drill rigs may become highly automated and controlled
remotely both for unconventional energy resource extraction (natural gas) and for drill and blast operations
of large open cut mines. For unconventional gas, chemical and mineralogical information from the drill rig
can be telemetered to a control site where decisions are made on continued drilling, fracking conditions
and completions. For large scale open cut mines, chemical and mineralogical information can be used to
update the resource model continuously and to control the distribution of explosives in blasting cycles also
delivered by the same robotic and flexible drill rigs.
The accurate ore body information leads to an optimised blasting process and allows for accurate
predictions of the composition of the resulting run of mine (ROM). In combination with fast ore sorting
technology, based on on-belt sensing and vast actuator concepts, the ROM is continuously separated into a
product and a gangue stream. In the most ideal situation, finer-tuning on selective ore processing could be
made rapidly, with appropriate underground ore monitoring, such that only ore of sufficient value is
brought to the surface. Gangue and ore of lower grade, though still of economic value, could be stockpiled
underground for later processing and/or blended with high-value material as required. Underground sensor
technology for ore-sorting at the work face (value-adding to block-caving strategies) would play a major
role in this scenario.
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Processing steps are optimised on the basis of detailed temporally-resolved compositional information
from the ore sorting and down-hole sensors on the drill rig, leading to a full understanding of the process
feed at any point in time. This information is further complemented by on-line sensors continuously
checking the feed. All sensor information is combined into the resource model which is updated
continuously.
Given the fact that accurate and real-time information is available on the feed, individual unit processes in
the overall processing flowsheet are dynamically run under conditions optimally tailored to the actual
characteristics of the feed entering the unit process. This optimises throughput, minimises energy
consumption and wastage.
The processing settings are optimised through a combination of actual physical input parameters (e.g. using
the SMP methodology described in scenario 6.1) and extensive performance predictions derived from a
computer model simulating the unit process at or near real-time.
This scenario enables high throughput, high efficiency mineral and energy operations with a minimum of
manpower in (multiple) remote locations and for deep, presently uneconomic deposits.
7. Preliminary gap analysis
For the scenarios developed above, at a macroscopic level all the ICT capabilities required seem to be well
represented in South Australia. At a more detailed level, there seems to be a need for more detailed
application know-how – a more detailed link between the specific requirements of the processes employed
in the minerals and energy sector and ICT approaches.
The capability gap doesn’t seem to lie so much in the lack of individual ICT skills as well as in a proven
capability to combine the relevant individual capabilities into convincing application demonstrators
specifically for the minerals and energy sector.
It will be useful to, as a next step, analyse the scenarios developed in the DMITRE master study in the
context of the capability set identified within the present work. Working through such specific examples
may well identify concrete critical ICT capability gaps. It is, however, encouraging to see that the three
disparate scenarios chosen in the present report do not seem to raise any red flags regarding lacking critical
capability, essentially confirming the strong capability base present at South Australia’s universities.
8. What are the research opportunities?
Major opportunities for the research community are envisaged in large collaborative demonstrator projects
with the involvement of service providers, equipment manufacturers, etc., to establish large-scale
demonstrator projects in a number of relevant areas, such as, for instance, “smart” heap leach operations
and no-people autonomous mining and processing plant.
Such projects can be built on capabilities presently existing in the State and would guide further (sub)
capability refinement and development and – importantly –would be a convincing means to close the
“credibility gap”. They would also form an excellent platform for the different capabilities to demonstrate
working together in the minerals and energy space (where they at present only rarely operate), thereby
developing the specific minerals and energy context that the Roadmap is seeking to inspire.
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These significant demonstrator projects are certain to attract significant attention, nationally and globally.
They would be there for South Australia to benefit from and for the world to see.
The findings of this preliminary capability stocktake would seem to warrant a specific collaborative research
program (CRC or similar) into ICT in Minerals and Energy, with South Australia in the driving seat.
9. What’s next? - Follow up actions
From the preliminary work performed during the present sub-project of the South Australian Roadmap for
ICT in Minerals and Energy project, a number of follow up actions present themselves in order to maintain
the momentum built during this stocktake and to initiate a broader dialogue among the capability holders
in the State and between the capability holders and the domain knowledge centres.
• A workshop, or a series of workshops, in which the interview participants work through the
scenarios developed in the present study and / or, if available, some selected scenarios developed
as part of the broader DMITRE study.
• Broad discussions at the university and State levels to scope out a possible structure for a future ICT
in Minerals and Energy CRC or alternative collaborative research initiative.
• A workshop with selected participants to flesh out potential scenarios and concomitant gap
analyses, specifically relating to the energy sector (e.g. coal seam gas), as this sector has remained
under-illuminated in this present study.
It is felt that the above points require actioning within the scope of the overall CSIRO roadmapping project
in order to keep the collective creative energy in the research community focused.
10. Conclusions
From the present study it is concluded that South Australia is well-endowed with both capabilities and
domain knowledge required to establish a strong science and technology base in ICT for Minerals and
Energy.
The majority of ICT capabilities are based at the University of Adelaide and the University of South
Australia. Flinders University has a range of interesting relevant niche capabilities.
Application of ICT capabilities presently mainly focuses on defence and, to a lesser extent, manufacturing
applications. In order to develop strong mineral and energy applications from the State’s ICT capability
base, a dialogue is required between capability and domain knowledge.
A rigorous coupling between the capability and the application/domain expertise is generally lacking, both
at an individual university and – particularly – at an all-of-State level.
Such a coupling is required to come up with convincing demonstrators in the energy and minerals space.
Those are the “runs on the board” that South Australia’s academia needs to increase its credibility.
As one of the interviewees remarked: “South Australia doesn’t have a capability gap, but a credibility gap
when it comes to ICT in minerals and energy.”
Convincing industry demonstrators will help generate that credibility.
Appendix 1
Organisational units in the SA university system with relevant ICT capabilities
Acronym
For institute / unit
Full name Home organisation
IMER Institute for Minerals and
Energy Resources
UA
IPAS Institute for Photonics &
Advanced Sensing
UA
TRC Teletraffic Research Centre UA
ACVT Australian Centre for Visual
Technologies
UA
DASI Defence Systems Institute UniSA
ITMS School of Information
Technologies and
Mathematical Sciences
UniSA
ACRC Advanced Computing Research
Centre
UniSA
CIAM Centre for Industrial and
Applied Mathematics
UniSA
PBRC Phenomics and Bioinformatics
Research Centre
UniSA
ITR Institute for
Telecommunications Research
UniSA
The Wark Ian Wark Research Institute UniSA
CNST Centre for NanoScale Science
and Technology
Flinders
CSEM School of Computer Science,
Engineering and Mathematics
Flinders
MDRI Medical Device Research
Institute
Flinders
DSIC Defence Systems Innovation
Centre
Inter-university
DET CRC Deep Exploration Technologies
Cooperative Research Centre
Multiple partners
DSTO Defence Science and
Technology Organisation