A framework for resolving manual-automation job decision dilemma in Ferro-chrome mining

1.
Field of Research

Data
Science

 

2.
Provisional Title

A
framework for resolving manual-automation job decision dilemma in Ferro-chrome
mining

3.
Research Context

 

Background

In the mining industry, which can be hazardous due to earth
movements, workers are exposed to many injuries, including inhalation of dust
particles such as crystalline silica (Wilson et al., 2020). In South Africa,
which owes its economy primarily to mining, research has indicated that miners
have a higher propensity to suffer from respiratory diseases, injuries, HIV as
well as tuberculosis when compared to the general public (McCulloch &
Miller, 2023). Such research reaffirms that the mining industry is now faced with
a critical necessity to battle the security and environmental issues this
industry is plagued with (Bisschoff et al., 2022).

 

Dilemma

The
mining industry in South Africa is facing a major challenge. On one hand, it is
expected to provide employment opportunities to the country’s population, which
is suffering from high unemployment rates. This is especially important as the
mining sector has a responsibility to help reduce poverty, which is linked to
inequality in South Africa.

 

On
the other hand, mining companies have realized that relying on manual labor can
be expensive and increase the risk of employee injuries. As a result, industry
organizations are increasingly interested in technology-driven solutions.
Inspectors from the Department of Mineral Resources and Energy have also noted
this trend. The challenge now is to find ways to use technology to improve
decision-making processes while also enhancing employee safety and operational
efficiency.

 

Theory
Grounding the Study

Underpinning
the study is the data science paradigm, a transformative force that improves
someone’s decision-making process in complex surroundings. Data science, an
umbrella term that coats methodologies like machine learning and predictive
analytics, is fast becoming a powerful tool that can be used to distill actionable
insights from large datasets (Sajid, 2023). This, in turn, empowers
stakeholders to make well-informed decisions (Yedla et al., 2020). Integrating
data science methodologies with theories of sustainability and compliance with
safety standards is the focus of this exploratory research conducted to solve
the single-dimensional challenges facing all mining operations (Rehman et al.,
2022).

 

Constructions
Explained with Associations (link).

 

Literature
Review

An

 

Challenges
and Solutions

South
African ferrous open-pit mining corporations face daunting multi-level
challenges that go deep into the operational fabric of the industry (Atud,
2020).

 

4.
Goals of the Research

Assessment
of Data Science Applicability

 

Identification
of Decision-Making Challenges

Development
of Data-Driven Solutions

 

5.
Methods, Procedures, Techniques, and Ethical Consideration

 

 

 

 

Please
find below the revised version of the text you provided:

 

The
paper should cover the following points:

 

1.
Background: You can discuss the mining industry worldwide and then narrow it
down to the South African perspective.

 

2.
The Dilemma: Why is this proposal worth doing? How will it contribute to the
body of knowledge? Please make sure to use plenty of references to ensure that
the paper is valid and academically sound. Also, use examples to emphasize the
dilemma.

 

3.
The paper needs to demonstrate the importance of having a model that can be
used to make a decision and its impact.

1.     
My major contrast:
Informed decision making

2.     
The criteria:
job automation and manual labour

3.     
The indicators:
safety

                        Insurance
of employment

                        Efficiency  

                        Pricing

                        Cost

                        Production level or
quality

1.     
Methodology: is the how       

                        Explain
how the research is going to be conducted and the planning

                        What type of design, method
and population are to be used? How will the data be collected and going to be
analysed and validated.

I
will use quantitative methodology – comparative analysis. I am looking at
sampling about 60 expects from different mines.  This will include engineers, safety and mining
managers, HR, Social department, specialist and extra

Need
to make sure that the paper has a flow

The
goal must be clear

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