Accurate costing of mining equipment
© 2018, Springer International Publishing AG. When performing equipment selection, we can best account for the operating cost by considering the number of hours that the equipment has been utilised. In a surface mine, equipment is often not utilised to full capacity and not accounting for this diffe...
| Main Authors: | , |
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| Format: | Book Chapter |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/67029 |
| _version_ | 1848761456187670528 |
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| author | Burt, C. Caccetta, Louis |
| author_facet | Burt, C. Caccetta, Louis |
| author_sort | Burt, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2018, Springer International Publishing AG. When performing equipment selection, we can best account for the operating cost by considering the number of hours that the equipment has been utilised. In a surface mine, equipment is often not utilised to full capacity and not accounting for this difference may lead to inferior solutions. Generally, the cost of operating equipment depends on the age of that equipment, while the decision to use a piece of equipment or not is based on the cost. This co-dependency of the age and utilisation of the equipment has so far provided a barrier to tractable equipment selection models. In the mining industry, it is a common practice to discretise both the age of the equipment and the current time into discrete blocks. However, since the running cost of a piece of equipment depends on its age, an undesirable side-effect of this discretisation is that the cost of operating a piece of equipment over a given time period must be determined by its age at the start of that period. It would be more accurate to account for changes in the age of the equipment as time passes within the period. In this chapter, we present a way in which we can capture the effect of these changes, using linear constraints and adjustments to the objective function. These constraints and adjustments are intended to be added to a mixed-integer linear program for equipment selection, which accounts for equipment utilisation, pre-existing equipment and heterogeneous fleets. However, with these additions this mixed-integer programming model increases in complexity and requires further work to achieve tractability in large-scale case studies. |
| first_indexed | 2025-11-14T10:31:57Z |
| format | Book Chapter |
| id | curtin-20.500.11937-67029 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:31:57Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-670292018-05-18T08:04:22Z Accurate costing of mining equipment Burt, C. Caccetta, Louis © 2018, Springer International Publishing AG. When performing equipment selection, we can best account for the operating cost by considering the number of hours that the equipment has been utilised. In a surface mine, equipment is often not utilised to full capacity and not accounting for this difference may lead to inferior solutions. Generally, the cost of operating equipment depends on the age of that equipment, while the decision to use a piece of equipment or not is based on the cost. This co-dependency of the age and utilisation of the equipment has so far provided a barrier to tractable equipment selection models. In the mining industry, it is a common practice to discretise both the age of the equipment and the current time into discrete blocks. However, since the running cost of a piece of equipment depends on its age, an undesirable side-effect of this discretisation is that the cost of operating a piece of equipment over a given time period must be determined by its age at the start of that period. It would be more accurate to account for changes in the age of the equipment as time passes within the period. In this chapter, we present a way in which we can capture the effect of these changes, using linear constraints and adjustments to the objective function. These constraints and adjustments are intended to be added to a mixed-integer linear program for equipment selection, which accounts for equipment utilisation, pre-existing equipment and heterogeneous fleets. However, with these additions this mixed-integer programming model increases in complexity and requires further work to achieve tractability in large-scale case studies. 2018 Book Chapter http://hdl.handle.net/20.500.11937/67029 10.1007/978-3-319-76255-5_9 restricted |
| spellingShingle | Burt, C. Caccetta, Louis Accurate costing of mining equipment |
| title | Accurate costing of mining equipment |
| title_full | Accurate costing of mining equipment |
| title_fullStr | Accurate costing of mining equipment |
| title_full_unstemmed | Accurate costing of mining equipment |
| title_short | Accurate costing of mining equipment |
| title_sort | accurate costing of mining equipment |
| url | http://hdl.handle.net/20.500.11937/67029 |