{"title":"Use of Simulation Techniques in Determining the Fleet Requirements of an Open Pit Mine","authors":"R. Suglo, S. Al-Hassan","doi":"10.4314/GM.V9I1.42606","DOIUrl":null,"url":null,"abstract":"When the final feasibility report on a new mine indicates that it is feasible under the prevailing technological and economic conditions to develop the project into an open pit mine, mine managers are often faced with the problem of determining the capacities, fleet sizes and how to match the materials handling equipment to ensure maximum production and profitability of the mine. One option is to use the results from other operating mines in similar geographic, geological and economic environments. Of late, most mine managements are increasingly depending on the results of computer simulations of their operations to determine the capacities, fleet sizes, for equipment matching. This paper uses the Visual SLAM with AweSim simulation software to determine the optimum fleet sizes of Kantaayele\nGoldfields Ltd., a gold mine in Ghana, which will enable the mine to meet its waste stripping and ore production targets. The use of simulation techniques as a tool in the modeling, formulation and testing of several models in the ore and waste mining operations of the mine are demonstrated. The results obtained from the simulation runs show that the mine cannot achieve its targets in ore mining and waste stripping with its initial fleets operating over 7.5-hour shifts per day. Using waiting times and queue lengths at the shovel and crusher locations as the determinants, the optimum fleet size for ore mining was found to be Option E with six 80-tonne trucks operating over 1350 minutes. For the waste stripping operations, the optimum fleet size was determined to be fourteen 80-tonne trucks. Ghana Mining Journal Vol. 9 2007: pp. 25-32","PeriodicalId":12530,"journal":{"name":"Ghana Mining Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ghana Mining Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/GM.V9I1.42606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
When the final feasibility report on a new mine indicates that it is feasible under the prevailing technological and economic conditions to develop the project into an open pit mine, mine managers are often faced with the problem of determining the capacities, fleet sizes and how to match the materials handling equipment to ensure maximum production and profitability of the mine. One option is to use the results from other operating mines in similar geographic, geological and economic environments. Of late, most mine managements are increasingly depending on the results of computer simulations of their operations to determine the capacities, fleet sizes, for equipment matching. This paper uses the Visual SLAM with AweSim simulation software to determine the optimum fleet sizes of Kantaayele
Goldfields Ltd., a gold mine in Ghana, which will enable the mine to meet its waste stripping and ore production targets. The use of simulation techniques as a tool in the modeling, formulation and testing of several models in the ore and waste mining operations of the mine are demonstrated. The results obtained from the simulation runs show that the mine cannot achieve its targets in ore mining and waste stripping with its initial fleets operating over 7.5-hour shifts per day. Using waiting times and queue lengths at the shovel and crusher locations as the determinants, the optimum fleet size for ore mining was found to be Option E with six 80-tonne trucks operating over 1350 minutes. For the waste stripping operations, the optimum fleet size was determined to be fourteen 80-tonne trucks. Ghana Mining Journal Vol. 9 2007: pp. 25-32