3
(such as production capacity, mining method, depth, etc.)
can be selected. Considering the unique nature of each
mining project based on different raw materials and depos-
its, it must be concluded that these cost models can only
provide supporting information regarding mining costs for
pre-scoping or scoping studies. A comparison conducted
for a mine extracting a sample deposit shows that within
the costs calculated using the cost models, discrepancies of
up to USD 86/t in OPEX and USD 71 million in CAPEX
can occur. [8 pp. 10–12]
For the more advanced planning stages, cost lists or
catalogs, such as the “Baugeräteliste” [17] in Germany or
Costmine [18] in the USA, as well as experience values,
guideline prices, or quotes from service providers or manu-
facturers, are used.
The overall assessment reveals that no standardized or
efficient approach for mining planning with variant com-
parisons is generally available. The acquisition of current,
reliable cost data largely depends on the experience of the
planner and the company, which can disadvantage small to
medium-sized mining enterprises right from the planning
phase. [8 pp. 24–25]
Requirements for a New Planning Tool
After evaluating the existing planning methods and tools,
the need for the development of an innovative planning
tool was demonstrated [8 pp. 26–31]. The following gen-
eral requirements were defined for this tool [8 pp. 32–40]:
• Integration of all technical, organizational, eco-
nomic, and environmental calculations and their
interdependencies within a single tool
• Flexible parameterization of input variables
• Database-like recording of costs
• Integration and transparent representation of all
calculations for main, auxiliary, and secondary pro-
cesses, aligned with the general technological chain
and specifically tailored to the individual mining
project
• Capability for conducting and documenting variant
comparisons
• Optimization options based on defined ecological,
time-based, or economic targets
• Usability of such a tool with standard office hardware
and software, suitable for users with average IT skills
and basic mining knowledge
Building on this, the basic structure for creating an
automated calculation tool for the planning of under-
ground mines was developed, and the technical implemen-
tation and validation were carried out using a real project
for a planned hard rock mine in Germany (from 2020 to
2024). Subsequently, the accuracy of the data generated by
the calculation tool was verified against most recent real
life data from another operating underground mine in
Germany (in 2024).
For the development of the tool, specific require-
ments for the following aspects were defined in detail [8
pp. 32–40]:
• Purpose of use,
• Limitations,
• User group and usability,
• Calculation, and
• Documentation.
It is important to emphasize that the tool is intended
for use in all stages of mining planning starting from the
pre-feasibility study. The level of detail in the planning
Table 1. Examples of cost models for underground mining
Editor/ Name
Country (currency),
Year Description
Thomas W. Camm
(USGS) [9, 10]
USA (USD), 1989,
updated 2019
Model (formulas, partly with tables for factors): developed for mineral deposits
in the desert regions of the US Southwest based on data from 3–4 mines
only for each mining method
T. A. O´Hara &S. C.
Suboleski [11 p. 405 ff.]
USA (USD), 1988 Model (tables with formulas for various factors): Standard reference in the US
mining industry, based on data from real mines
MAFMINE [12, 13] Brasil (USD), 2016–
2021
Free software (online tool): based on O’Hara and Suboleski, calculates not only
costs but also technical and organisational parameters
V. Rudenno [14] Wolrdwide (USD),
2011
Model (formulas without factors): based on 350 mines in 60 countries,
linear regression of mining costs, only input of annual production, no
differentiation of mining methods
Sherpa Cost Estimating
Software (Costmine) [15
p. 50 ff., 16]
USA (USD), 2000, is
continuously updated
Software for a fee (available: table): Consideration of different mining
methods, accesses and daily productions
(such as production capacity, mining method, depth, etc.)
can be selected. Considering the unique nature of each
mining project based on different raw materials and depos-
its, it must be concluded that these cost models can only
provide supporting information regarding mining costs for
pre-scoping or scoping studies. A comparison conducted
for a mine extracting a sample deposit shows that within
the costs calculated using the cost models, discrepancies of
up to USD 86/t in OPEX and USD 71 million in CAPEX
can occur. [8 pp. 10–12]
For the more advanced planning stages, cost lists or
catalogs, such as the “Baugeräteliste” [17] in Germany or
Costmine [18] in the USA, as well as experience values,
guideline prices, or quotes from service providers or manu-
facturers, are used.
The overall assessment reveals that no standardized or
efficient approach for mining planning with variant com-
parisons is generally available. The acquisition of current,
reliable cost data largely depends on the experience of the
planner and the company, which can disadvantage small to
medium-sized mining enterprises right from the planning
phase. [8 pp. 24–25]
Requirements for a New Planning Tool
After evaluating the existing planning methods and tools,
the need for the development of an innovative planning
tool was demonstrated [8 pp. 26–31]. The following gen-
eral requirements were defined for this tool [8 pp. 32–40]:
• Integration of all technical, organizational, eco-
nomic, and environmental calculations and their
interdependencies within a single tool
• Flexible parameterization of input variables
• Database-like recording of costs
• Integration and transparent representation of all
calculations for main, auxiliary, and secondary pro-
cesses, aligned with the general technological chain
and specifically tailored to the individual mining
project
• Capability for conducting and documenting variant
comparisons
• Optimization options based on defined ecological,
time-based, or economic targets
• Usability of such a tool with standard office hardware
and software, suitable for users with average IT skills
and basic mining knowledge
Building on this, the basic structure for creating an
automated calculation tool for the planning of under-
ground mines was developed, and the technical implemen-
tation and validation were carried out using a real project
for a planned hard rock mine in Germany (from 2020 to
2024). Subsequently, the accuracy of the data generated by
the calculation tool was verified against most recent real
life data from another operating underground mine in
Germany (in 2024).
For the development of the tool, specific require-
ments for the following aspects were defined in detail [8
pp. 32–40]:
• Purpose of use,
• Limitations,
• User group and usability,
• Calculation, and
• Documentation.
It is important to emphasize that the tool is intended
for use in all stages of mining planning starting from the
pre-feasibility study. The level of detail in the planning
Table 1. Examples of cost models for underground mining
Editor/ Name
Country (currency),
Year Description
Thomas W. Camm
(USGS) [9, 10]
USA (USD), 1989,
updated 2019
Model (formulas, partly with tables for factors): developed for mineral deposits
in the desert regions of the US Southwest based on data from 3–4 mines
only for each mining method
T. A. O´Hara &S. C.
Suboleski [11 p. 405 ff.]
USA (USD), 1988 Model (tables with formulas for various factors): Standard reference in the US
mining industry, based on data from real mines
MAFMINE [12, 13] Brasil (USD), 2016–
2021
Free software (online tool): based on O’Hara and Suboleski, calculates not only
costs but also technical and organisational parameters
V. Rudenno [14] Wolrdwide (USD),
2011
Model (formulas without factors): based on 350 mines in 60 countries,
linear regression of mining costs, only input of annual production, no
differentiation of mining methods
Sherpa Cost Estimating
Software (Costmine) [15
p. 50 ff., 16]
USA (USD), 2000, is
continuously updated
Software for a fee (available: table): Consideration of different mining
methods, accesses and daily productions