Trong Vu, T. Bao, C. Drebenstedt, H. Pham, Hoai-Quoc-Trung Nguyen, Duc Nguyen
{"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":null,"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":"113 1","pages":"146 - 158"},"PeriodicalIF":1.8000,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mining Technology-Transactions of the Institutions of Mining and Metallurgy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/25726668.2021.1894398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MINING & MINERAL PROCESSING","Score":null,"Total":0}
引用次数: 2
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.