Digital Innovation: Augmented Reality in the Mining Sector

This article discusses the use of augmented reality in the mining sector, focusing on its benefits and implementation. It also explores two data analytics techniques that benefit the organization and the opportunities and challenges in analytics. Additionally, it highlights the importance of artificial intelligence in mineral exploration and the ethical issues associated with AI.

Digital Innovation
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Table of Contents
INTRODUCTION...........................................................................................................................3
Augmented Reality within the Mining sector..............................................................................3
Analytics..........................................................................................................................................6
Two data analytics techniques which benefit the organization...................................................6
Analytics opportunities and the challenges and implementation of the opportunities................8
Importance of the Artificial Intelligence......................................................................................9
The ethical issues within Artificial intelligence.........................................................................10
CONCLUSION .............................................................................................................................11
REFERENCES..............................................................................................................................12
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INTRODUCTION
Augmented Reality within the Mining sector
The development regarding technology requires to create an augmented reality system
that enable to see this kind of technology within many sectors such as marketing, navigation aid
and maintenance aid as well as gaming. Augmented reality is an emerging form of experience
that is related to the real world and is increased through computer-generated content that tied to
a location as well as activities. In other words, Augmented Reality enables the digital content to
overlay seamlessly to provide perceptions of the real world. the 2D and 3D objects as digital
assets, for example, audio as well as video files, information is incorporated into the user's
perceptions considering the real world. This article emphasizes the mining sector within Canada
as well as particularly within the province of Quebec is considered as the leading decision maker
to utilizes the new technologies within a sector. The evaluation put forward some various actions
for the improvement as well as development by using technology and technical point of view to
assist augmented reality within the mining sector (Mesu, Sanders and Riemsdijk,2015).
Motivators
During the current mining operations, there are three significant areas of activity, as each
of the three corners of a triangle guides the work of the people on the site. One of the corners
represents health as well as safety within the workplace. The second one includes constraints
that are associated with the environment and the third one is associated with productivity. As a
part of the continuous improvement that has an impact on an employee's health and safety of
RIO TINTO. Moreover, mining structure from various industries trends so that their product can
be modernized (Mesu, Sanders and Riemsdijk,2015).
The first position that includes the operator of the power shovel, whose job is to collect
minerals to load high capacity trucks. The next position involves position related to truck drivers.
The people work closely with each other during the entire cycle regarding products such as from
the position of truck to the loading zone through the arrival regarding the unloading zone. With
the outline of the whole production, the augmented reality of the Rio Tinto related to the pure
production mode finds the better working by utilising work stations — enabling enhancing in
increases the profitability of the operators. The aim of this study bring change through
augmented system to necessary changes as a part of the improvement within the productivity and
also the safety of the workers of the RIO TINTO.
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Augmented reality
Here the combining as well as virtual and offering 3D registration. Here the third point is
not necessary to compiled with augmented reality. Thus, to use a more anthropocentric approach
that consists of the defining augmented reality as not byways of the effect as it has same as the
user. Thus, the aim of the anthropocentric approach that consists of defining augmented reality
that can offer either a modelling of the real world that depends on the creation of an imaginary
world (Mesu, Sanders and Riemsdijk,2015).
Here primary augmented reality is made up of the sensory devices that are capable of
stimulating the sense of the user such as helmets, speakers and glasses as well as motorized
devices that capture movement of the user such as vision camera, and inertial navigator platform.
Efficiency and accuracy regarding drilling is introduced by visual guidance assistance. This
visual technology can be improved through orientation of the drill below and display real time
location. It also displays drill below surface. It also assists the mining on surface regarding the
poor conditions such as rain, sand, etc. It assists developing applications that enable miners to
see scenarios and objects.
Primary skills areas within the mining sector
The mining sector requires synergy among various skill areas as it describes the primary areas
that are required for work regarding the open-pit mine as the order of the primary skills that are
linked to the various number of the people belonging to each skill areas.
Heavy Machines operators (Mobile or fixed)
Tasks: This job consists of various driving as well as operating as both at the hands, and the
machines that are considered extremely heavy as well as large. Here the operators of these kinds
of machines at the starting point are used for handling the minerals (Odoardi and et al., 2019).
Operators on the mobile machines must guide machines from the loading to the unloading zone
as they must follow the onboard software to know where they are required or also take the load
such as
utilize Augmented reality
Here the operators can deal with significant problems such as lack of visibility as giant machines
have also weighed several hundred tonnes as the operators must deal within the significant spots
called the blind spots. As in many of the conditions, the drivers must be manoeuvre blind that is
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guided only through AR. Thus, the uses of augmented reality are to solve the problem that is
attractive (Odoardi, and et al., 2019).
Drillers as well as Dynamiters: The job is drilling the rocks by using portable machines or also
self-supporting frills. Drill holes within the project take place within remote areas as the on site
presence of an expert is also often rare and arrival on site regarding an expert cam sometimes
takes several days.
Uses of the augmented reality
The first use of the augmented reality took place within the field regarding manufacturing as well
as maintenance aid. Here the augmented reality reduces reliance on paper media or also on the
direct consultation of a tool during maintenance.
Mining techniques- The mining techniques are also used for drawing up the drilling plans for
dynamiters and drillers
Use of augmented reality
During the exterior works, the technician deals with all the constraints such as excavation deals
with the public works.
Improvements- This context-related that there are no specific improvements that are to be made.
Other than those there are well-known through community (Odoardi, and et al., 2019).
b)
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Analytics
Two data analytics techniques which benefit the organization
Predictive analytics
Predictive analytics is the art and science of creating predictive systems and models. Rio
Tinto is using predictive analytics because it is widening the data analytics and using neural
networking as well. It has a process which is starting with data collection and mining. In the first
step of the process the data is collected and cleaned. Data is collected form the multiple sources
and is cleaned as well (Bir, and et al., 2019). Mining is done through many methods. The
methods for mining are machine learning methods, which include pattern matching and data
visualization, as well. The predictive analytics techniques include decision tree techniques and
text analytics techniques. Rio Tinto is implementing the text analytics technique. In the text
analytic techniques, the data is stored and the database management system is designed. For
finding the texted data the topic is examined. One of the predictive analytic techniques is the
probabilistic latent semantic indexing techniques, which is calculating the probability of the data
and the frequency of the data as well. The collected data is examined by the scientist. Product
reviews and the feedback of the customers are helping the scientist to collect the data for the
products and the company (Bertsimas and Kallus 2019).
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It would create the worthiness of the marketing and the campaign, as well. It would also
forecast the weather and store the data effectively in big data analytics tools. Rio Tinto would
also manage the data, and the asset of the company would be managed effectively.
Prescriptive analytics
Prescriptive analytics is related to both descriptive and predictive analytics. Descriptive
analytics is providing insight, and predictive analytics is providing the model and help to forecast
the situation. In the prescriptive analytics the company would evaluate situation and then provide
solutions. Prescriptive analytics would support in decision making. The approach is analyzing
the potential decision and the factors which are influencing the decisions.
The prescriptive analytics is using the data of Rio Tinto for performing the work, and if
the data is not provided accurate it will fail the technique. The mathematical algorithms and the
data sets are used for the prescriptive analysis. Game theory and the decision analysis methods
are used in it. It is beneficial for Rio Tinto and its employees. The data would be stored, and Rio
Tinto would also get the best solution to the problems.
Analytics opportunities and the challenges and implementation of the opportunities.
Analytics opportunities
Storing the Data
Storing data through the Analysis can help Rio Tinto to make new strategies for the
company, and they can use this data for the growth of the company, and improving financial
stability. The company can compare its performance and take certain measures. Collected data
for raw material can show the available.
Forecasting the data
Forecasting the data can be helpful for the Rio Tinto to fulfill future needs, and they can
make advance strategies. Forecasting the data can help to know how much growth Rio Tinto can
achieve according to the data they have collected. They make new strategies to achieve future
goals of the Rio Tinto company (He and Chua 2017). Analytics is important part of the company
because it can be helpful for Rio Tinto to achieve future opportunities for the company.
The company would get the best solution
Rio Tinto will get the best solution and they can solve a problem that is occurring in the
workplace. They can also gain the growth opportunities from the Analysis. If Rio Tinto is facing
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any problem related to the resources, and they are not able to find the solution then they can use
Analysis of the company and find the proper solution for their problem.
Challenges for the opportunities
Rio Tinto is facing many challenges in fulfilling opportunities. The predictive and
prescriptive analytics are helping Rio Tinto to work. Storing the data and forecasting about the
situations benefit Rio Tinto. The analytics would also provide the best solutions for Rio Tinto,
but the solution would only be given when the problem is understood properly. Rio Tinto is
facing the problem of identifying the problems, so the company is taking the help of the scientist
for identifying the problems. Data storage needs the investment and the data storage tools need
the money for the storing and security of the data. Data collection of Rio Tinto and the scientist
who is working in the company are significant problems and especially the accurate data
(Gunasekaran, and et al., 2017).
The data is collected through the digital survey and the feedback and reviews of the
employees of Rio Tinto so the data collected is manually, and also the data need to be cleaned
whether it also accurate or not. Rio Tinto has to use the big data tools which are used for
cleaning the data. Some companies would not able to afford these tools. Due to the lack of
technical staff Rio Tinto is not able to perform the analytic. A well-trained employee is needed
for data analytics and for storing the data in the database. Due to the lack of technical employees
Rio Tinto would not act in a suitable way (Larose 2015).
Importance of Artificial Intelligence
Mineral exploration.
Machine learning and artificial intelligence can assist mining companies like Rio Tinto to
extract mineral as it is considered as a critical component in mining operation. Although this is
considered as a relatively new application of AI as well as new machine learning and many
mining companies are initiating this (Lam, Huang, and Chan, 2015).
Sorting minerals
Within the majority of mining operations it is required to eliminate waste from raw
material to find valuable minerals. Some firms have to start to use AI to sort the mined materials
(Odoardi and et al., 2019).
Digital Twinning
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As consider to be a part mining operations firm like Rio Tinto is also creating a new mine
by 2021. There are many innovations done by them and are analyzing as one of the initiatives
called digital twinning. NASA is first company to use it and nowadays it is also adopted by
various industrial sectors as virtual model. It is considered as the fed real-time data from the
scenarios that can quickly be tested, field, as well as operations and productions that can also
optimized (Kang, FRONTIS Corp, 2019).
The ethical issues within Artificial intelligence.
Rio Tinto's operations involves 1500 km of rail,16 mines and three ports as well as more
as it creates 2.4 terabytes of the data for every minute from all of its sensors and mobile
equipment that collect and transmit data within real-time to assist monitor equipment
(Raso,Werth. and Loos,2017).
One of the primary concerns that deals use of Artificial intelligence is loss of jobs. As per
the McKinsey report, by the year 2039, 800 million people can lose their jobs to the AI driven
robots. Some jobs will be overtaken by robots while it is considered that they are too tedious for
humans. But on contrary Artificial intelligence can create more jobs that can take the advantage
regarding the human ability that includes higher cognitive functions.
Environmental impacts- This resource the existing vegetation, destroys wildlife as well as
habitat and also destroys the soil profile.
Acid Mine Drainage- As a high concentration of the metals as well as acidic conditions
considers having an adverse effect regarding the water bodies that can able destroy aquatic plant,
fish, etc.
Labour issues- The workers can be exploited within the mining industry as there is no
compensation or Monetary safety for the employees that are working in that (Kang, FRONTIS
Corp, 2019).
Safety equipment- Some mining companies the workers are not provided with the protective
gear as well as safety equipment within the mines.
Leadership
It is necessary to follow a specific leadership style. They can apply participative
leadership it is a kind of managerial style that invites all the workers of the RIO TINTO to
involve in decision making process. The employees are able to share their views and opinions
with leader. It enables in working in effective way and taking correct decisions.
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As a leader, it is important to motivate employees. This is because it results in improving
their performance and completing goals and objectives in specified time. Moreover, it leads to
creative working and utilising resources in efficient way. Alongside, when staff is encouraged,
they support to others in accomplishing goals. It results in increasing their satisfaction and
retaining them for long term. hence, it leads to creating a positive work place culture and
enhancing overall business efficiency. The rewards are given to those who performed best.
Rewards can be monetary and non monetary (Mesu,Sanders and Riemsdijk,2015).
CONCLUSION
From the above report, it had been concluded that augmented reality plays a crucial role
within the mining sector as it helps the improving accuracy as well as efficiency. There are
multiple advantages of augmented reality in the industrial manufacturing industries. As these
kinds of industry include higher sophisticated machinery thus tasks can be performed with help
of AR that can perform various task which requires high supervision and includes higher
efficiency when there is a use of AR navigation. It also helps in the maintenance work through
virtual instruction. Furthermore, report focused on the participative leadership that provides a
better solution for the firm.
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REFERENCES
Books and journals
Baier, D., Rese, A. and Schreiber, S., 2016. Analyzing online reviews to measure augmented
reality acceptance at the point of sale: the case of IKEA. In Mobile Computing and Wireless
Networks: Concepts, Methodologies, Tools, and Applications(pp. 1714-1736). IGI Global.
Bertsimas, D. and Kallus, N., 2019. From predictive to prescriptive analytics. Management of
Science.
Bir and et al., 2019. Prescriptive analytics platform and polarity analysis engine. U.S. Patent
Application 10/235,336.
Gunasekaran and et al., 2017. Big data and predictive analytics for supply chain and
organizational performance. Journal of Business Research. 70. pp.308-317.
Kang, J.S., FRONTIS Corp, 2019. Server, method and wearable device for supporting the
maintenance of military apparatus based on augmented reality using correlation rule mining.
U.S. Patent Application 16/212,686.
Lam, C.K., Huang, X. and Chan, S.C., 2015. The threshold effect of participative leadership and
the role of leader information sharing. Academy of Management Journal.58(3).pp.836-855.
Mesu, J., Sanders, K. and Riemsdijk, M.V., 2015. Transformational leadership and
organizational commitment in manufacturing and service small to medium-sized
enterprises: The moderating effects of directive and participative leadership. Personnel
Review.44(6).pp.970-990.
Odoardi, C and et al., 2019. Affective Commitment, Participative Leadership, and Employee
Innovation: A Multilevel Investigation. Journal of Work and Organizational
Psychology.35(2).pp.103-113.
Raso, R., Werth, D. and Loos, P., 2017, January. Enriching Augmented Reality with Text Data
Mining: An Automated Content Management System to Develop Hybrid Media
Applications. In Proceedings of the 50th Hawaii International Conference on System
Sciences.
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