Mining Technological System's Performance Analysis
The mining production systems, both for underground and open pit extraction consist mainly in a string of equipment starting with the winning equipment (shearer loader, in case of underground longwall mining or bucket wheel excavator in case of open pit mining), hauling equipment (armored face conve...
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Online Access: | http://www.aucjc.ro/wp-content/uploads/2016/10/aucjcm-vol-2-2016-56-64.pdf |
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doaj-1f3b43af9e0a4b11b20eddade3d900332020-11-24T21:56:35ZengEditura SitechAnnals of the University of Craiova for Journalism, Communication and Management2501-35132016-10-01215664Mining Technological System's Performance AnalysisSorin Mihai Radu0Witold Chmielarz1Andrei Andras2University of Petrosani, RomaniaUniversity of Warsaw, PolandUniversity of Petrosani, RomaniaThe mining production systems, both for underground and open pit extraction consist mainly in a string of equipment starting with the winning equipment (shearer loader, in case of underground longwall mining or bucket wheel excavator in case of open pit mining), hauling equipment (armored face conveyor in longwall mining or the on-board belt conveyor in case of excavators), main conveying equipment (belt conveyor in both cases), transfer devices, stock pile or bunker feeding equipment. This system of mainly serially connected elements is characterized by the throughput (overall amount of bulk coal respectively overburden rock produced), which is dependent on the functioning state of each involved equipment, and is strongly affected also by the process inherent variability due to the randomness of the involved processes (e.g. the cutting properties of the rock). In order to model and simulate such production systems, some probabilistic methods are applied arising from the artificial intelligence approach, involving unit operations and equipment, as the overall system as a whole, namely the Monte Carlo simulation, neural networks, fuzzy systems, and the Load Strength Interference methods. The results obtained are convergent and offer the opportunity for further developments of their application in the study of mining production systems.http://www.aucjc.ro/wp-content/uploads/2016/10/aucjcm-vol-2-2016-56-64.pdfmining technology system analysis performance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sorin Mihai Radu Witold Chmielarz Andrei Andras |
spellingShingle |
Sorin Mihai Radu Witold Chmielarz Andrei Andras Mining Technological System's Performance Analysis Annals of the University of Craiova for Journalism, Communication and Management mining technology system analysis performance |
author_facet |
Sorin Mihai Radu Witold Chmielarz Andrei Andras |
author_sort |
Sorin Mihai Radu |
title |
Mining Technological System's Performance Analysis |
title_short |
Mining Technological System's Performance Analysis |
title_full |
Mining Technological System's Performance Analysis |
title_fullStr |
Mining Technological System's Performance Analysis |
title_full_unstemmed |
Mining Technological System's Performance Analysis |
title_sort |
mining technological system's performance analysis |
publisher |
Editura Sitech |
series |
Annals of the University of Craiova for Journalism, Communication and Management |
issn |
2501-3513 |
publishDate |
2016-10-01 |
description |
The mining production systems, both for underground and open pit extraction consist mainly in a string of equipment starting with the winning equipment (shearer loader, in case of underground longwall mining or bucket wheel excavator in case of open pit mining), hauling equipment (armored face conveyor in longwall mining or the on-board belt conveyor in case of excavators), main conveying equipment (belt conveyor in both cases), transfer devices, stock pile or bunker feeding equipment. This system of mainly serially connected elements is characterized by the throughput (overall amount of bulk coal respectively overburden rock produced), which is dependent on the functioning state of each involved equipment, and is strongly affected also by the process inherent variability due to the randomness of the involved processes (e.g. the cutting properties of the rock). In order to model and simulate such production systems, some probabilistic methods are applied arising from the artificial intelligence approach, involving unit operations and equipment, as the overall system as a whole, namely the Monte Carlo simulation, neural networks, fuzzy systems, and the Load Strength Interference methods. The results obtained are convergent and offer the opportunity for further developments of their application in the study of mining production systems. |
topic |
mining technology system analysis performance |
url |
http://www.aucjc.ro/wp-content/uploads/2016/10/aucjcm-vol-2-2016-56-64.pdf |
work_keys_str_mv |
AT sorinmihairadu miningtechnologicalsystemsperformanceanalysis AT witoldchmielarz miningtechnologicalsystemsperformanceanalysis AT andreiandras miningtechnologicalsystemsperformanceanalysis |
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