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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Main Authors: Sorin Mihai Radu, Witold Chmielarz, Andrei Andras
Format: Article
Language:English
Published: Editura Sitech 2016-10-01
Series:Annals of the University of Craiova for Journalism, Communication and Management
Subjects:
Online Access:http://www.aucjc.ro/wp-content/uploads/2016/10/aucjcm-vol-2-2016-56-64.pdf
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spelling 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
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