Gurmeet Shekhar, A. Gustafson, K. Jonsson, J. Martinsson, H. Schunnesson
{"title":"Malmberget矿分段崩落开采最优放煤控制策略的开发","authors":"Gurmeet Shekhar, A. Gustafson, K. Jonsson, J. Martinsson, H. Schunnesson","doi":"10.1080/25726668.2020.1775432","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper addresses the identification of the optimal draw control strategy for a sublevel caving (SLC) operation at Malmberget mine in Sweden. Two mathematical models, a probability model and an economic model, were created using five datasets: bucket weights, bucket grades, extraction ratio, mine economics parameters and production constraints. The probability model was used to generate a set of simulated bucket weights and corresponding bucket grades which acts as a ‘virtual mine’ environment. The economic model assesses the economic impact of loading at the draw point. Two approaches to draw control were tested using the ‘virtual mine’ created by the probability model. Based on the results of the simulation tests, an optimal draw control strategy is suggested for a field test at the mine. The new draw control strategy optimises further the loading operation at Malmberget mine. The paper shows a roadmap for optimising draw control strategy for SLC operations.","PeriodicalId":44166,"journal":{"name":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of an optimal draw control strategy for a sublevel caving operation at Malmberget mine\",\"authors\":\"Gurmeet Shekhar, A. Gustafson, K. Jonsson, J. Martinsson, H. Schunnesson\",\"doi\":\"10.1080/25726668.2020.1775432\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT This paper addresses the identification of the optimal draw control strategy for a sublevel caving (SLC) operation at Malmberget mine in Sweden. Two mathematical models, a probability model and an economic model, were created using five datasets: bucket weights, bucket grades, extraction ratio, mine economics parameters and production constraints. The probability model was used to generate a set of simulated bucket weights and corresponding bucket grades which acts as a ‘virtual mine’ environment. The economic model assesses the economic impact of loading at the draw point. Two approaches to draw control were tested using the ‘virtual mine’ created by the probability model. Based on the results of the simulation tests, an optimal draw control strategy is suggested for a field test at the mine. The new draw control strategy optimises further the loading operation at Malmberget mine. The paper shows a roadmap for optimising draw control strategy for SLC operations.\",\"PeriodicalId\":44166,\"journal\":{\"name\":\"Mining Technology-Transactions of the Institutions of Mining and Metallurgy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2020-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mining Technology-Transactions of the Institutions of Mining and Metallurgy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/25726668.2020.1775432\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MINING & MINERAL PROCESSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/25726668.2020.1775432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MINING & MINERAL PROCESSING","Score":null,"Total":0}
Development of an optimal draw control strategy for a sublevel caving operation at Malmberget mine
ABSTRACT This paper addresses the identification of the optimal draw control strategy for a sublevel caving (SLC) operation at Malmberget mine in Sweden. Two mathematical models, a probability model and an economic model, were created using five datasets: bucket weights, bucket grades, extraction ratio, mine economics parameters and production constraints. The probability model was used to generate a set of simulated bucket weights and corresponding bucket grades which acts as a ‘virtual mine’ environment. The economic model assesses the economic impact of loading at the draw point. Two approaches to draw control were tested using the ‘virtual mine’ created by the probability model. Based on the results of the simulation tests, an optimal draw control strategy is suggested for a field test at the mine. The new draw control strategy optimises further the loading operation at Malmberget mine. The paper shows a roadmap for optimising draw control strategy for SLC operations.