XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1117
INTRODUCTION
The mining industry in the world are facing several forcing
factors that deal with ore falling grades, rising energy costs,
large ore type variations, increase in water consumption
and its decreasing availability, remote operations, stringer
safety and environmental regulations, and increasing skilled
operator labor costs. As we mine lower grade ores the
required energy shut exponentially and the water resources
to enables the perform the required grinding and flota-
tion are also increased as shown in Figure 1 (Fuerstenau,
2001). At the time that this conference was held in Brazil,
it was tremendous opportunity to wake up and we started
process data and advanced data analytics with on-line real-
time models to reduce waste, improve equipment uptime
and maximize the production while conserving water and
energy. The results of the operational excellence strategies
under the digital era are summarized by Bascur, 2020.
aA key strategy to deal with the necessity of providing
the right amount of metals to the world is to use the lat-
est technologies to analyze the large amount of historical
operations data accumulated by the mining operations.
The world is experiencing one of the greatest and fastest
change in human history caused by these new cyber tech-
nologies which are transforming the economy, society and
the way we live. The digital disruption produced in indus-
try by automatization of processes, artificial intelligence,
Big Data, and machine learning present an opportunity for
great technological improvements. Big Data is a discipline
of the field of information and communication technolo-
gies, which shows, by collecting and ordering data sets too
large or complex to be treated by traditional data, how to
present their visualization, representation and predictions
and apply them to software analysis from the observed pat-
terns. This discipline is based on three elements, large data
volume, data treatment speed and variety of data formats.
The existence of Big Data allows machine learning, the
autonomous learning of a machine that does not need to
be programmed. This is what we call Industry Revolution
4.0 (Schwab 2016).
Currently the major roadblock for the digital transfor-
mation is the cultural change required to adapt to new ways
for business process workflows. These roadblocks are:
• Too many data silos and legacy systems
• Too many versions of the truth
• Cultural adaption and new skills
• Lack of management involvement and having the
right information
• Resistance to redesign the new business work pro-
cesses in the digital age
• Not empowering people to use computers to analyze
data
The future of mining lies in the implementation of
the Industrial Revolution 4.0 to mining. These new tech-
nologies, called Mining 4.0, should permit the integrated
Figure 1. Key mineral processing factors, increase in water and energy resources in operating copper ores with less than 0.5%
grade operations. (Source: Fuerstenau, 2001)
INTRODUCTION
The mining industry in the world are facing several forcing
factors that deal with ore falling grades, rising energy costs,
large ore type variations, increase in water consumption
and its decreasing availability, remote operations, stringer
safety and environmental regulations, and increasing skilled
operator labor costs. As we mine lower grade ores the
required energy shut exponentially and the water resources
to enables the perform the required grinding and flota-
tion are also increased as shown in Figure 1 (Fuerstenau,
2001). At the time that this conference was held in Brazil,
it was tremendous opportunity to wake up and we started
process data and advanced data analytics with on-line real-
time models to reduce waste, improve equipment uptime
and maximize the production while conserving water and
energy. The results of the operational excellence strategies
under the digital era are summarized by Bascur, 2020.
aA key strategy to deal with the necessity of providing
the right amount of metals to the world is to use the lat-
est technologies to analyze the large amount of historical
operations data accumulated by the mining operations.
The world is experiencing one of the greatest and fastest
change in human history caused by these new cyber tech-
nologies which are transforming the economy, society and
the way we live. The digital disruption produced in indus-
try by automatization of processes, artificial intelligence,
Big Data, and machine learning present an opportunity for
great technological improvements. Big Data is a discipline
of the field of information and communication technolo-
gies, which shows, by collecting and ordering data sets too
large or complex to be treated by traditional data, how to
present their visualization, representation and predictions
and apply them to software analysis from the observed pat-
terns. This discipline is based on three elements, large data
volume, data treatment speed and variety of data formats.
The existence of Big Data allows machine learning, the
autonomous learning of a machine that does not need to
be programmed. This is what we call Industry Revolution
4.0 (Schwab 2016).
Currently the major roadblock for the digital transfor-
mation is the cultural change required to adapt to new ways
for business process workflows. These roadblocks are:
• Too many data silos and legacy systems
• Too many versions of the truth
• Cultural adaption and new skills
• Lack of management involvement and having the
right information
• Resistance to redesign the new business work pro-
cesses in the digital age
• Not empowering people to use computers to analyze
data
The future of mining lies in the implementation of
the Industrial Revolution 4.0 to mining. These new tech-
nologies, called Mining 4.0, should permit the integrated
Figure 1. Key mineral processing factors, increase in water and energy resources in operating copper ores with less than 0.5%
grade operations. (Source: Fuerstenau, 2001)