PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ
Coal is one of the mining commodities needed by many industries that are used for fuel, coal is a resource that cannot be renewed so that in mining it requires mining planning with pit optimization principles to know the most optimal design produced. The purpose of this research is to design the...
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id-itb.:619572021-09-28T21:01:56ZPIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ Adjie Pramudya, Danung Indonesia Final Project Pit optimization, Pit shell, Ultimate pit limit, Coal, Scheduling INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/61957 Coal is one of the mining commodities needed by many industries that are used for fuel, coal is a resource that cannot be renewed so that in mining it requires mining planning with pit optimization principles to know the most optimal design produced. The purpose of this research is to design the most profitable option PT XYZ pit mining design using the principle of mine optimization. In addition, the purpose of this study is to find out the ideal production target of PT XYZ and the influence of PT XYZ coal mining direction. The pit design optimization in this study used Geovia Minex software based on the Lerchs- Grossmann Algorithm method. The first step in optimizing is to include the economic and technical parameters needed by Geovia Minex to perform pit optimization. In-pit optimization generated Pit Shell output which will be a reference for pit design and coal Scheduling PT XYZ. From Pit Shell Optimization and pit design will be compared to the difference in waste, coal, and stripping ratio. Scheduling in this study used Spry software that uses basic strips and blocks to do Scheduling. The first step in Scheduling is to import data output from Geovia Minex that has been processed before. After the next data import is to set the block that wants to be prioritized mining as well as the type and number of tools to be used. The last output is an animation of the progress of the mine in the time frame of each year. From the results of the study, there is a difference between the amount of coal from Pit Shell optimization results and pit design. The amount of Pit Shell coal is 139,114,318 tons while from the pit design is 113,004,538 tons there is a difference of 26,109,780 tons. Scenario 2A produces the most profitable option with a production target of 8,800,000 tons per year using 1 unit of PC 1250, 3 units of PC 750 and 3 units of PC 400 more profit compared to scenario 1A with a production target of 5,300,000 tons per year using 1 unit of PC 750 and 5 units of PC 400 because the 2A scenario has a larger NPV. There is a significant influence on the direction of mining in the distribution of stripping ratio every year where the southnorth direction has a large SR in the first year when compared to the north-south. text |
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Coal is one of the mining commodities needed by many industries that are used for fuel, coal
is a resource that cannot be renewed so that in mining it requires mining planning with pit
optimization principles to know the most optimal design produced. The purpose of this
research is to design the most profitable option PT XYZ pit mining design using the principle
of mine optimization. In addition, the purpose of this study is to find out the ideal production
target of PT XYZ and the influence of PT XYZ coal mining direction.
The pit design optimization in this study used Geovia Minex software based on the Lerchs-
Grossmann Algorithm method. The first step in optimizing is to include the economic and
technical parameters needed by Geovia Minex to perform pit optimization. In-pit
optimization generated Pit Shell output which will be a reference for pit design and coal
Scheduling PT XYZ. From Pit Shell Optimization and pit design will be compared to the
difference in waste, coal, and stripping ratio.
Scheduling in this study used Spry software that uses basic strips and blocks to do
Scheduling. The first step in Scheduling is to import data output from Geovia Minex that has
been processed before. After the next data import is to set the block that wants to be
prioritized mining as well as the type and number of tools to be used. The last output is an
animation of the progress of the mine in the time frame of each year.
From the results of the study, there is a difference between the amount of coal from Pit Shell
optimization results and pit design. The amount of Pit Shell coal is 139,114,318 tons while
from the pit design is 113,004,538 tons there is a difference of 26,109,780 tons. Scenario 2A
produces the most profitable option with a production target of 8,800,000 tons per year
using 1 unit of PC 1250, 3 units of PC 750 and 3 units of PC 400 more profit compared to
scenario 1A with a production target of 5,300,000 tons per year using 1 unit of PC 750 and
5 units of PC 400 because the 2A scenario has a larger NPV. There is a significant influence
on the direction of mining in the distribution of stripping ratio every year where the southnorth
direction has a large SR in the first year when compared to the north-south. |
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Final Project |
author |
Adjie Pramudya, Danung |
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Adjie Pramudya, Danung PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
author_facet |
Adjie Pramudya, Danung |
author_sort |
Adjie Pramudya, Danung |
title |
PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
title_short |
PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
title_full |
PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
title_fullStr |
PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
title_full_unstemmed |
PIT OPTIMIZATION AND SCHEDULING COAL MINES PT XYZ |
title_sort |
pit optimization and scheduling coal mines pt xyz |
url |
https://digilib.itb.ac.id/gdl/view/61957 |
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1822931808675692544 |