LHD operations in sublevel caving mines: a productivity perspective

Mining is a high-risk industry, so efficiency and safety are key priorities. As mines continue to go deeper and exploit low-grade deposits, bulk mining methods, such as sublevel caving (SLC), have become increasingly important. SLC is suitable for massive steeply dipping ore bodies and is known for...

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Bibliographic Details
Main Author: Tariq, Muhammad
Format: Master Thesis
Language:English
Published: Luleå tekniska universitet, Geoteknologi 2024
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-105420
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author Tariq, Muhammad
author_facet Tariq, Muhammad
author_sort Tariq, Muhammad
collection Luleå University of Technology Publications (DiVA)
description Mining is a high-risk industry, so efficiency and safety are key priorities. As mines continue to go deeper and exploit low-grade deposits, bulk mining methods, such as sublevel caving (SLC), have become increasingly important. SLC is suitable for massive steeply dipping ore bodies and is known for its high degree of mechanisation, productivity, and low operational cost. Moreover, technological developments and mechanisation have allowed these methods to be applied at greater depths. In modern mechanised mines Load haul dump (LHD) machines are central to achieving the desired productivity. Therefore, automation of LHDs and their increasing use in mines make it crucial to understand the performance of these machines in actual mining environments. The aim of this research was to understand the differences in the productivity of semiautonomous and manual LHDs and identify how external factors impact the performance of these machines in SLC operations. The research also investigated how LHD operator training could improve the loading efficiency. Performance data for semi-autonomous and manual LHDs were collected from LKAB’s Kiirunavaara mine’s central database, GIRON. These data were used to compare cycle times and payloads of semi-autonomous and manual LHDs. The data were filtered and sorted so that only data where both machine types were operating in the same area (crosscut, ring, and ore pass) were used. To understand the impact of external factors, data on the occurrence of boulders were collected from LKAB’s Malmberget mine by recording videos of LHD buckets, while the data on operator training were obtained by performing baseline mapping and conducting a questionnaire study with the LHD operators at LKAB’s Kiirunavaara mine. The results of the comparative analysis of manual and semi-autonomous LHDs showed the mean payload was 0.34 tonnes higher for manual LHD machines. However, the differences were not consistent across different areas of the mine. Similarly, when comparing the cycle times, in 57% of the ...
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spelling ftluleatu:oai:DiVA.org:ltu-105420 2025-01-16T23:02:36+00:00 LHD operations in sublevel caving mines: a productivity perspective Tariq, Muhammad 2024 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-105420 eng eng Luleå tekniska universitet, Geoteknologi Luleå Licentiate thesis / Luleå University of Technology, 1402-1757 info:eu-repo/semantics/openAccess info:eu-repo/semantics/embargoedAccess Underground Mining Load Haul Dump machine (LHD) Automation Training Stochastic Simulation Other Civil Engineering Annan samhällsbyggnadsteknik Licentiate thesis, comprehensive summary info:eu-repo/semantics/masterThesis text 2024 ftluleatu 2024-12-18T12:24:47Z Mining is a high-risk industry, so efficiency and safety are key priorities. As mines continue to go deeper and exploit low-grade deposits, bulk mining methods, such as sublevel caving (SLC), have become increasingly important. SLC is suitable for massive steeply dipping ore bodies and is known for its high degree of mechanisation, productivity, and low operational cost. Moreover, technological developments and mechanisation have allowed these methods to be applied at greater depths. In modern mechanised mines Load haul dump (LHD) machines are central to achieving the desired productivity. Therefore, automation of LHDs and their increasing use in mines make it crucial to understand the performance of these machines in actual mining environments. The aim of this research was to understand the differences in the productivity of semiautonomous and manual LHDs and identify how external factors impact the performance of these machines in SLC operations. The research also investigated how LHD operator training could improve the loading efficiency. Performance data for semi-autonomous and manual LHDs were collected from LKAB’s Kiirunavaara mine’s central database, GIRON. These data were used to compare cycle times and payloads of semi-autonomous and manual LHDs. The data were filtered and sorted so that only data where both machine types were operating in the same area (crosscut, ring, and ore pass) were used. To understand the impact of external factors, data on the occurrence of boulders were collected from LKAB’s Malmberget mine by recording videos of LHD buckets, while the data on operator training were obtained by performing baseline mapping and conducting a questionnaire study with the LHD operators at LKAB’s Kiirunavaara mine. The results of the comparative analysis of manual and semi-autonomous LHDs showed the mean payload was 0.34 tonnes higher for manual LHD machines. However, the differences were not consistent across different areas of the mine. Similarly, when comparing the cycle times, in 57% of the ... Master Thesis Malmberget giron Luleå University of Technology Publications (DiVA)
spellingShingle Underground Mining
Load Haul Dump machine (LHD)
Automation
Training
Stochastic Simulation
Other Civil Engineering
Annan samhällsbyggnadsteknik
Tariq, Muhammad
LHD operations in sublevel caving mines: a productivity perspective
title LHD operations in sublevel caving mines: a productivity perspective
title_full LHD operations in sublevel caving mines: a productivity perspective
title_fullStr LHD operations in sublevel caving mines: a productivity perspective
title_full_unstemmed LHD operations in sublevel caving mines: a productivity perspective
title_short LHD operations in sublevel caving mines: a productivity perspective
title_sort lhd operations in sublevel caving mines: a productivity perspective
topic Underground Mining
Load Haul Dump machine (LHD)
Automation
Training
Stochastic Simulation
Other Civil Engineering
Annan samhällsbyggnadsteknik
topic_facet Underground Mining
Load Haul Dump machine (LHD)
Automation
Training
Stochastic Simulation
Other Civil Engineering
Annan samhällsbyggnadsteknik
url http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-105420