Pub Date : 2021-10-02DOI: 10.1080/25726668.2021.1957539
S. Islam, David J. Williams, Chenming Zhang
ABSTRACT Proper understanding and analysis of the consolidation behaviour and parameters of tailings from a slurry-like to a soil-like state are vital for the design, management, and assessment of a tailings storage facility (TSF). Fine-grained coal tailings slurry can undergo relatively rapid and substantial settlement from a slurried state and can experience relatively slow and limited self-weight consolidation, remaining slurry-like and under-consolidated, rather than soil-like. A large purpose-built slurry consolidometer having a newly developed consolidometer cell, instrumented with load cells and pore water pressure transducers, is well-suited to test tailings from a slurry-like to a soil-like state and enables the constant rate of loading (CRL) to simulate the build-up of tailings. CRL is more representative of the rate of rise of tailings in a TSF than incremental step loading. By conducting consolidation tests on fine-grained coal tailings from a slurry-state under a loading rate of 0.12 kPa/min up to applied stress of 320 kPa, this research investigated the effect of initial specimen height (ISH) and initial solids concentration (ISC) on consolidation parameters and hydraulic conductivity. Using ISH and ISC as independent inputs, a statistical model has been proposed to estimate the consolidation settlement at the end of the slurry consolidation test.
{"title":"Effect of initial specimen height and solids concentration on the consolidation parameters of fine-grained coal tailings","authors":"S. Islam, David J. Williams, Chenming Zhang","doi":"10.1080/25726668.2021.1957539","DOIUrl":"https://doi.org/10.1080/25726668.2021.1957539","url":null,"abstract":"ABSTRACT Proper understanding and analysis of the consolidation behaviour and parameters of tailings from a slurry-like to a soil-like state are vital for the design, management, and assessment of a tailings storage facility (TSF). Fine-grained coal tailings slurry can undergo relatively rapid and substantial settlement from a slurried state and can experience relatively slow and limited self-weight consolidation, remaining slurry-like and under-consolidated, rather than soil-like. A large purpose-built slurry consolidometer having a newly developed consolidometer cell, instrumented with load cells and pore water pressure transducers, is well-suited to test tailings from a slurry-like to a soil-like state and enables the constant rate of loading (CRL) to simulate the build-up of tailings. CRL is more representative of the rate of rise of tailings in a TSF than incremental step loading. By conducting consolidation tests on fine-grained coal tailings from a slurry-state under a loading rate of 0.12 kPa/min up to applied stress of 320 kPa, this research investigated the effect of initial specimen height (ISH) and initial solids concentration (ISC) on consolidation parameters and hydraulic conductivity. Using ISH and ISC as independent inputs, a statistical model has been proposed to estimate the consolidation settlement at the end of the slurry consolidation test.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89552832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/25726668.2021.1886544
L. Dorador, E. Eberhardt, D. Elmo
ABSTRACT Broken ore density (BOD) is an important parameter in planning a block cave mine. However, its assessment is complicated by the heterogeneous nature of its distribution within a draw column, varying from a denser central plug-flow zone and decreasing outwards towards outer perimeter shear bands. The BOD further decreases immediately above the drawpoint due to the development of a loosening zone that develops in response to mucking. This makes determining BOD a challenging task, hindered by the inability to measure it in situ. To address this, several key factors influencing BOD are investigated including the influence of primary and secondary fragmentation, air gap thickness, draw rate and column height. Data is used to link primary and secondary fragmentation to broken ore size distributions. From these, a conceptual framework and empirical procedures are presented for evaluating BOD within draw columns during block caving for feasibility and early stage mine planning and design.
{"title":"Procedure for estimating broken ore density distribution within a draw column during block caving","authors":"L. Dorador, E. Eberhardt, D. Elmo","doi":"10.1080/25726668.2021.1886544","DOIUrl":"https://doi.org/10.1080/25726668.2021.1886544","url":null,"abstract":"ABSTRACT Broken ore density (BOD) is an important parameter in planning a block cave mine. However, its assessment is complicated by the heterogeneous nature of its distribution within a draw column, varying from a denser central plug-flow zone and decreasing outwards towards outer perimeter shear bands. The BOD further decreases immediately above the drawpoint due to the development of a loosening zone that develops in response to mucking. This makes determining BOD a challenging task, hindered by the inability to measure it in situ. To address this, several key factors influencing BOD are investigated including the influence of primary and secondary fragmentation, air gap thickness, draw rate and column height. Data is used to link primary and secondary fragmentation to broken ore size distributions. From these, a conceptual framework and empirical procedures are presented for evaluating BOD within draw columns during block caving for feasibility and early stage mine planning and design.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89702341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-30DOI: 10.1080/25726668.2021.1944458
Trong Vu, T. Bao, Q. Hoang, Carsten Drebenstetd, Pham Van Hoa, Hoang Hung Thang
ABSTRACT Blast fragmentation size distribution is one of the most critical factors in evaluating the blasting results and affecting the downstream mining and processing operations in open-pit mines. Image-based methods are widely applied to address the problem but require heavy user interaction and experience. This study deployed a deep learning model Mask R-CNN to develop an automatic measurement method of blast fragmentation. The model was trained using images captured from real blasting sites in Nui Phao open-pit mine in Vietnam. The trained model reported high average precision scores (Intersection over Union, IoU = 0.5) 92% and 83% for bounding box and segmentation masks, respectively. The results lay a solid technical basis for the automated measurement of blast fragmentation in open-pit mines.
摘要露天矿爆破破片粒度分布是评价爆破效果和影响下游开采加工作业的关键因素之一。基于图像的方法被广泛应用于解决问题，但需要大量的用户交互和经验。本研究采用深度学习模型Mask R-CNN，开发了一种爆炸破片自动测量方法。该模型使用从越南Nui phhao露天矿真实爆破现场捕获的图像进行训练。训练后的模型对边界框和分割掩码的平均精度得分(Intersection over Union, IoU = 0.5)分别为92%和83%。研究结果为露天矿爆破破片的自动化测量奠定了坚实的技术基础。
{"title":"Measuring blast fragmentation at Nui Phao open-pit mine, Vietnam using the Mask R-CNN deep learning model","authors":"Trong Vu, T. Bao, Q. Hoang, Carsten Drebenstetd, Pham Van Hoa, Hoang Hung Thang","doi":"10.1080/25726668.2021.1944458","DOIUrl":"https://doi.org/10.1080/25726668.2021.1944458","url":null,"abstract":"ABSTRACT Blast fragmentation size distribution is one of the most critical factors in evaluating the blasting results and affecting the downstream mining and processing operations in open-pit mines. Image-based methods are widely applied to address the problem but require heavy user interaction and experience. This study deployed a deep learning model Mask R-CNN to develop an automatic measurement method of blast fragmentation. The model was trained using images captured from real blasting sites in Nui Phao open-pit mine in Vietnam. The trained model reported high average precision scores (Intersection over Union, IoU = 0.5) 92% and 83% for bounding box and segmentation masks, respectively. The results lay a solid technical basis for the automated measurement of blast fragmentation in open-pit mines.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79693066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-11DOI: 10.1080/25726668.2021.1937455
R. C. Barbosa, Carlos E. P. Ortiz, A. Curi
ABSTRACT Complex load and haul cycles in mining are composed of individual steps, whose times could be better described by a statistical distribution than by the average value. In order to evaluate how loading times and dumping times behave, this paper tested a large dataset of loading and dumping times measured at an open pit limestone mine in Brazil against the distributions most commonly used to model these variables, Log-normal and Normal; as well as Gamma, Logistic, Weibull and Exponential distributions. None of the tested distributions provided statistically significant adherence to the data, but it was possible to identify that for most equipment, Logistic and Normal distributions would produce less error on stochastic modelling then the other tested distributions.
{"title":"Non-deterministic load and dump behaviour in mining haul trucks: a case of study","authors":"R. C. Barbosa, Carlos E. P. Ortiz, A. Curi","doi":"10.1080/25726668.2021.1937455","DOIUrl":"https://doi.org/10.1080/25726668.2021.1937455","url":null,"abstract":"ABSTRACT Complex load and haul cycles in mining are composed of individual steps, whose times could be better described by a statistical distribution than by the average value. In order to evaluate how loading times and dumping times behave, this paper tested a large dataset of loading and dumping times measured at an open pit limestone mine in Brazil against the distributions most commonly used to model these variables, Log-normal and Normal; as well as Gamma, Logistic, Weibull and Exponential distributions. None of the tested distributions provided statistically significant adherence to the data, but it was possible to identify that for most equipment, Logistic and Normal distributions would produce less error on stochastic modelling then the other tested distributions.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78762161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-04DOI: 10.1080/25726668.2021.1935098
Douglas Alexandre Gonçalves Alegre, Rodrigo De Lemos Peroni, Eduardo da Rosa Aquino, Felipe Dille
ABSTRACT Haul roads play a significant role in mining, with rolling resistance being one of the main aspects that can affect road quality and consequently the performance of mining trucks. The aim of this study is to estimate the rolling resistance of haul road segments considering longitudinal grade crossed with dispatch system data using back-calculation from Rimpull curves and estimated performance equations developed by Cooper. The use of this method demonstrated that it could assist in quickly identifying issues on mine haul roads and assess road quality locally through rolling resistance estimated maps, which will help to improve maintenance routines and truck performance.
{"title":"A method to assess haul roads rolling resistance using dispatch system data","authors":"Douglas Alexandre Gonçalves Alegre, Rodrigo De Lemos Peroni, Eduardo da Rosa Aquino, Felipe Dille","doi":"10.1080/25726668.2021.1935098","DOIUrl":"https://doi.org/10.1080/25726668.2021.1935098","url":null,"abstract":"ABSTRACT Haul roads play a significant role in mining, with rolling resistance being one of the main aspects that can affect road quality and consequently the performance of mining trucks. The aim of this study is to estimate the rolling resistance of haul road segments considering longitudinal grade crossed with dispatch system data using back-calculation from Rimpull curves and estimated performance equations developed by Cooper. The use of this method demonstrated that it could assist in quickly identifying issues on mine haul roads and assess road quality locally through rolling resistance estimated maps, which will help to improve maintenance routines and truck performance.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87094031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-21DOI: 10.1080/25726668.2021.1927587
T. Komba
ABSTRACT As metal mineral resources get depleted over time, there is a need to recover metals from ores of lower grades and waste. Mining wastes are largely characterized using physical and mineralogical heterogeneity properties. There is variation in the geochemical properties with different grain sizes, thus, different metal recovery potential. The research evaluated mine waste characterization and identified opportunities for optimizing project economics using fragmentation analysis. This study linked petrographic, compositional and quantitative mineralogical analyses with fragmentation data resulting from conventional mechanical communition of mined-out waste rock. The results improve the understanding of what grain sizes are optimal for metal recovery from the waste rock and established that environmental threats can be mitigated by removing fines from waste. The economic metals including Ni and Cu sulphides are predominantly held in pentlandite and chalcopyrite within the rocks. Maximum liberation and metal recovery are in the finer grains.
{"title":"Evaluation of mine waste characterization to identify opportunities for optimizing project economics using fragmentation analysis","authors":"T. Komba","doi":"10.1080/25726668.2021.1927587","DOIUrl":"https://doi.org/10.1080/25726668.2021.1927587","url":null,"abstract":"ABSTRACT As metal mineral resources get depleted over time, there is a need to recover metals from ores of lower grades and waste. Mining wastes are largely characterized using physical and mineralogical heterogeneity properties. There is variation in the geochemical properties with different grain sizes, thus, different metal recovery potential. The research evaluated mine waste characterization and identified opportunities for optimizing project economics using fragmentation analysis. This study linked petrographic, compositional and quantitative mineralogical analyses with fragmentation data resulting from conventional mechanical communition of mined-out waste rock. The results improve the understanding of what grain sizes are optimal for metal recovery from the waste rock and established that environmental threats can be mitigated by removing fines from waste. The economic metals including Ni and Cu sulphides are predominantly held in pentlandite and chalcopyrite within the rocks. Maximum liberation and metal recovery are in the finer grains.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75946958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-03DOI: 10.1080/25726668.2021.1919374
M. Mohtasham, Hossein Mirzaei-Nasirabad, H. Askari-Nasab, B. Alizadeh
ABSTRACT The present study aims to propose new strategies based on mixed-integer non-linear programming (MINLP) models for the equipment sizing (ES) problem to verify the overall efficiency of the fleet. The developed models estimate the optimal size of trucks concerning the match factor value with two different strategies. The first strategy deals with each loader type, and the second one is applied simultaneously with all types of loaders. The proposed approaches are compared to a simulation strategy to assess the models. Implementing models with a copper mine case study provides a more efficient haul fleet size than the decisions offered by the simulation method. Moreover, the presented strategies provide an effective way to improve equipment performance where the current mine strategy does not adapt well. A key contribution of this research is the development, implementation, and verification of new optimization and simulation methods to address the ES problem in open-pit mines.
{"title":"Truck fleet size selection in open-pit mines based on the match factor using a MINLP model","authors":"M. Mohtasham, Hossein Mirzaei-Nasirabad, H. Askari-Nasab, B. Alizadeh","doi":"10.1080/25726668.2021.1919374","DOIUrl":"https://doi.org/10.1080/25726668.2021.1919374","url":null,"abstract":"ABSTRACT The present study aims to propose new strategies based on mixed-integer non-linear programming (MINLP) models for the equipment sizing (ES) problem to verify the overall efficiency of the fleet. The developed models estimate the optimal size of trucks concerning the match factor value with two different strategies. The first strategy deals with each loader type, and the second one is applied simultaneously with all types of loaders. The proposed approaches are compared to a simulation strategy to assess the models. Implementing models with a copper mine case study provides a more efficient haul fleet size than the decisions offered by the simulation method. Moreover, the presented strategies provide an effective way to improve equipment performance where the current mine strategy does not adapt well. A key contribution of this research is the development, implementation, and verification of new optimization and simulation methods to address the ES problem in open-pit mines.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90191245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-03DOI: 10.1080/25726668.2021.1916170
M. Mohtasham, Hossein Mirzaei-Nasirabad, B. Alizadeh
ABSTRACT The truck allocation problem is an important section of the transportation system in open-pit mines. Most available models for the truck scheduling problem do not directly address the stochastic nature of truck-shovel systems by using multi-objective optimization techniques. This paper presents a chance-constrained goal programming (CCGP) model based on four important goals to estimate the impacts of the uncertainty on the efficiency of truck-shovel systems. The proposed model has been implemented using 11 schedule scenarios and different confidence levels (CLs) for loader’s production to determine the best allocation of trucks in an open-pit copper mine. The results display that the model can handle the quality and quantity of material required to achieve the objectives of the short-term production schedule of the mine in all CLs, even in the highest risk level. This model has a remarkable ability to meet the required objectives in terms of uncertainty in mining operations.
{"title":"Optimization of truck-shovel allocation in open-pit mines under uncertainty: a chance-constrained goal programming approach","authors":"M. Mohtasham, Hossein Mirzaei-Nasirabad, B. Alizadeh","doi":"10.1080/25726668.2021.1916170","DOIUrl":"https://doi.org/10.1080/25726668.2021.1916170","url":null,"abstract":"ABSTRACT The truck allocation problem is an important section of the transportation system in open-pit mines. Most available models for the truck scheduling problem do not directly address the stochastic nature of truck-shovel systems by using multi-objective optimization techniques. This paper presents a chance-constrained goal programming (CCGP) model based on four important goals to estimate the impacts of the uncertainty on the efficiency of truck-shovel systems. The proposed model has been implemented using 11 schedule scenarios and different confidence levels (CLs) for loader’s production to determine the best allocation of trucks in an open-pit copper mine. The results display that the model can handle the quality and quantity of material required to achieve the objectives of the short-term production schedule of the mine in all CLs, even in the highest risk level. This model has a remarkable ability to meet the required objectives in terms of uncertainty in mining operations.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75299317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-22DOI: 10.1080/25726668.2021.1901026
Luke Clarkson, David J. Williams
ABSTRACT New literature, mining regulators, insurance firms, and mining practitioners are calling for increased diligence in the form of real-time monitoring: but what can the industry offer in response? This research establishes a centralisation of instrumentation systems suitable for tailings dams, discussing the specifications, advantages, and disadvantages of each. This paper describes an understanding of dataloggers and sensor nodes, sensor networks, and online monitoring systems critical to the transmission and reception of sensor data across vast and remote site areas. Collaboration with suppliers discovered systems which enable reliable, efficient, and real-time transmission of instrumentation data, ready for interpretation. This paper aims to translate traditionally electrical and systems engineering terminology into a reference base suitable for the broad range of tailings dam practitioners. This reference base is anticipated to help facilitate informed discussions and encourage deployment of appropriate instrumentation systems that are suitable to the practitioner’s short- and long-term intent.
{"title":"Catalogue of example instrumentation and monitoring systems for tailings dams in Australia","authors":"Luke Clarkson, David J. Williams","doi":"10.1080/25726668.2021.1901026","DOIUrl":"https://doi.org/10.1080/25726668.2021.1901026","url":null,"abstract":"ABSTRACT New literature, mining regulators, insurance firms, and mining practitioners are calling for increased diligence in the form of real-time monitoring: but what can the industry offer in response? This research establishes a centralisation of instrumentation systems suitable for tailings dams, discussing the specifications, advantages, and disadvantages of each. This paper describes an understanding of dataloggers and sensor nodes, sensor networks, and online monitoring systems critical to the transmission and reception of sensor data across vast and remote site areas. Collaboration with suppliers discovered systems which enable reliable, efficient, and real-time transmission of instrumentation data, ready for interpretation. This paper aims to translate traditionally electrical and systems engineering terminology into a reference base suitable for the broad range of tailings dam practitioners. This reference base is anticipated to help facilitate informed discussions and encourage deployment of appropriate instrumentation systems that are suitable to the practitioner’s short- and long-term intent.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/25726668.2021.1901026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72527330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-03DOI: 10.1080/25726668.2021.1894398
Trong Vu, T. Bao, C. Drebenstedt, H. Pham, Hoai-Quoc-Trung Nguyen, Duc Nguyen
ABSTRACT The success of a cement production project depends on the supply of raw materials. Long-term quarry production scheduling (LTQPS) based on resource models is essential to maintain a consistent supply to cement plants. Geological uncertainty is inherent due to sparse exploration data in resource models and significant risk factors for not achieving production targets. This research proposes a stochastic framework for LTQPS that considers the impact of geological uncertainty on raw material supply. A clustering algorithm uses multiple simulated deposit models to aggregate blocks into mining cuts. A new stochastic mixed-integer programming model is formulated with two objectives: to minimise the cost for developing the raw mix and the risk of not meeting production targets. The proposed framework is implemented successfully in a limestone deposit in Southern Vietnam, resulting in an increase of 5 million tons (Mt) and a 30% reduction in unit cost over the deterministic mixed-integer programming model.
{"title":"Optimisation of long-term quarry production scheduling under geological uncertainty to supply raw materials to a cement plant","authors":"Trong Vu, T. Bao, C. Drebenstedt, H. Pham, Hoai-Quoc-Trung Nguyen, Duc Nguyen","doi":"10.1080/25726668.2021.1894398","DOIUrl":"https://doi.org/10.1080/25726668.2021.1894398","url":null,"abstract":"ABSTRACT The success of a cement production project depends on the supply of raw materials. Long-term quarry production scheduling (LTQPS) based on resource models is essential to maintain a consistent supply to cement plants. Geological uncertainty is inherent due to sparse exploration data in resource models and significant risk factors for not achieving production targets. This research proposes a stochastic framework for LTQPS that considers the impact of geological uncertainty on raw material supply. A clustering algorithm uses multiple simulated deposit models to aggregate blocks into mining cuts. A new stochastic mixed-integer programming model is formulated with two objectives: to minimise the cost for developing the raw mix and the risk of not meeting production targets. The proposed framework is implemented successfully in a limestone deposit in Southern Vietnam, resulting in an increase of 5 million tons (Mt) and a 30% reduction in unit cost over the deterministic mixed-integer programming model.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77603963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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