Mine fleet cost evaluation : Dijkstra’s optimized path.
The transport distance in a mining operation strongly influences a mine op- eration revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engi- neer’s practical knowledge, which does not consider any mec...
| Autores: | , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Institución: | Universidade Federal de Ouro Preto (UFOP) |
| Repositorio: | Repositório Institucional da UFOP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufop.br:123456789/15444 |
| Acceso en línea: | http://www.repositorio.ufop.br/jspui/handle/123456789/15444 https://doi.org/10.1590/0370-44672018720124 |
| Access Level: | acceso abierto |
| Palabra clave: | Fleet costs Transport time Transport distance |
| Sumario: | The transport distance in a mining operation strongly influences a mine op- eration revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engi- neer’s practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for cal- culating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Di- jkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to in- crease for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning. |
|---|