Abstract
Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant proportion of the overall operational cost. Currently available costing methods and models do not take into account all key constraints and as a result, maintenance cost cannot be minimised. A new mixed integer programming (MIP) model is developed to minimise the maintenance cost for a heterogeneous truck fleet over a multi-year period while considering a new truck-purchase option. The proposed model is applied to truck maintenance cost data from a gold mine in Western Australia. Results indicate 21?64% and 14?76% cost savings over 10 years in comparison to the spread sheet based and original MIP models, respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 30-35 |
| Number of pages | 6 |
| Journal | Transactions of the Institution of Mining and Metallurgy, Section A: Mining Technology |
| Volume | 123 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
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Keywords
- Cost minimisation
- Mine optimisation
- Mine truck scheduling
- Mixed integer programming
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology
- Geology
Cite this
Optimisation of a mixed truck fleet schedule through a mathematical model considering a new truck-purchase option. / Fu, Zhao; Topal, Erkan; Erten, Oktay.
In: Transactions of the Institution of Mining and Metallurgy, Section A: Mining Technology, Vol. 123, No. 1, 2014, p. 30-35.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Optimisation of a mixed truck fleet schedule through a mathematical model considering a new truck-purchase option
AU - Fu, Zhao
AU - Topal, Erkan
AU - Erten, Oktay
PY - 2014
Y1 - 2014
N2 - Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant proportion of the overall operational cost. Currently available costing methods and models do not take into account all key constraints and as a result, maintenance cost cannot be minimised. A new mixed integer programming (MIP) model is developed to minimise the maintenance cost for a heterogeneous truck fleet over a multi-year period while considering a new truck-purchase option. The proposed model is applied to truck maintenance cost data from a gold mine in Western Australia. Results indicate 21?64% and 14?76% cost savings over 10 years in comparison to the spread sheet based and original MIP models, respectively.
AB - Mining is a capital-intensive industry that requires hundreds of million-dollar investment in major equipment. In regards to surface mining operations, mine trucks are the most common pieces of equipment that are used for material haulage. Their maintenance cost, however, constitutes a significant proportion of the overall operational cost. Currently available costing methods and models do not take into account all key constraints and as a result, maintenance cost cannot be minimised. A new mixed integer programming (MIP) model is developed to minimise the maintenance cost for a heterogeneous truck fleet over a multi-year period while considering a new truck-purchase option. The proposed model is applied to truck maintenance cost data from a gold mine in Western Australia. Results indicate 21?64% and 14?76% cost savings over 10 years in comparison to the spread sheet based and original MIP models, respectively.
KW - Cost minimisation
KW - Mine optimisation
KW - Mine truck scheduling
KW - Mixed integer programming
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UR - http://www.scopus.com/inward/citedby.url?scp=84901457550&partnerID=8YFLogxK
U2 - 10.1179/1743286314Y0000000055
DO - 10.1179/1743286314Y0000000055
M3 - Article
VL - 123
SP - 30
EP - 35
JO - Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology
JF - Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology
SN - 1474-9009
IS - 1
ER -