11
Realized NPV Sensitivity to Ore Control Selectivity
For continuous improvement opportunity testing, a
key analysis is to evaluate how ore control selectivity can
impact value. To test this question, the mining sequence
was fixed by the base plan (built with the IK model) and
the processing sequence was optimized using the different
block models. The results isolate the dramatic impact that
mining selectivity can have on value realized from a mine
plan (Table 4 bottom section)—5% lower NPV with the
IKD model’s selectivity and 17% lower NPV with the OK
model’s level of selectivity. Figure 15 shows how the lower
selectivity model impacts mill grade and discounted cash
flows over time.
CONCLUSION
Because an operation only has a finite budget and limited
change management bandwidth, continuous improvement
projects should be prioritized based on expected value and
change complexity. The MILP production scheduling tool
can be useful in evaluating the value expected from con-
tinuous improvement projects which improve mining and
processing constraints. The tool accounts for how improve-
ments will interact over time with the mining sequence,
grade-tonnage distributions, cutoff grades and mine/mill
constraints. The tool was also used to compute the value
resulting from cost per ton improvement projects, mine
planning changes, and mine selectivity changes.
For the copper mine example presented, cost per ton
improvements showed more benefit than tonnage capac-
ity increases. Mine planning levers and mine selectivity
levers showed similar or larger potential value impacts than
cost or capacity improvement levers. Mine planning and
mine selectivity improvements should also be considered
within an operation’s portfolio of continuous improvement
projects.
14a) Histograms of alternate copper grade models
14b) Grade above cutoff for alternate grade models
Figure 14. Selectivity impacts to grade distributions
Table 4. Value Creation vs Geostatistics
Geostatistics Levers NPV
Model impact to planned NPV
OK model plan &selectivity 3,396 (684) -16.8%
-1 6 .8 %IKD (-5%) model plan &selectivity 3,869 (210) -5.2%
-5 .2 %Model impact to realized NPV (constant selectivity)
OK model plan w/ IK selectivity 4,047 (32) -0.8%
-0.8 %IKD (-5%) model plan w/ IK selectivity 4,076 (3) -0.1%
-0.1 %Selectivity impact to realized NPV (constant mine plan)
Base Plan (IK) w/ OK selectivity 3,371 (709) -17.4%
-1 7 .4 %Base Plan (IK) w/ IKD (-5%) selectivity 3,868 (212) -5.2%
-5 .2 %
Diff vs Base Case
15a) Yearly mill grade comparison
15b) Discounted cash flow comparison
Figure 15. Selectivity impacts on mill grade and cash flow
mine sequence held constant (plan based on IK model) and
process sequence varied by block model
Realized NPV Sensitivity to Ore Control Selectivity
For continuous improvement opportunity testing, a
key analysis is to evaluate how ore control selectivity can
impact value. To test this question, the mining sequence
was fixed by the base plan (built with the IK model) and
the processing sequence was optimized using the different
block models. The results isolate the dramatic impact that
mining selectivity can have on value realized from a mine
plan (Table 4 bottom section)—5% lower NPV with the
IKD model’s selectivity and 17% lower NPV with the OK
model’s level of selectivity. Figure 15 shows how the lower
selectivity model impacts mill grade and discounted cash
flows over time.
CONCLUSION
Because an operation only has a finite budget and limited
change management bandwidth, continuous improvement
projects should be prioritized based on expected value and
change complexity. The MILP production scheduling tool
can be useful in evaluating the value expected from con-
tinuous improvement projects which improve mining and
processing constraints. The tool accounts for how improve-
ments will interact over time with the mining sequence,
grade-tonnage distributions, cutoff grades and mine/mill
constraints. The tool was also used to compute the value
resulting from cost per ton improvement projects, mine
planning changes, and mine selectivity changes.
For the copper mine example presented, cost per ton
improvements showed more benefit than tonnage capac-
ity increases. Mine planning levers and mine selectivity
levers showed similar or larger potential value impacts than
cost or capacity improvement levers. Mine planning and
mine selectivity improvements should also be considered
within an operation’s portfolio of continuous improvement
projects.
14a) Histograms of alternate copper grade models
14b) Grade above cutoff for alternate grade models
Figure 14. Selectivity impacts to grade distributions
Table 4. Value Creation vs Geostatistics
Geostatistics Levers NPV
Model impact to planned NPV
OK model plan &selectivity 3,396 (684) -16.8%
-1 6 .8 %IKD (-5%) model plan &selectivity 3,869 (210) -5.2%
-5 .2 %Model impact to realized NPV (constant selectivity)
OK model plan w/ IK selectivity 4,047 (32) -0.8%
-0.8 %IKD (-5%) model plan w/ IK selectivity 4,076 (3) -0.1%
-0.1 %Selectivity impact to realized NPV (constant mine plan)
Base Plan (IK) w/ OK selectivity 3,371 (709) -17.4%
-1 7 .4 %Base Plan (IK) w/ IKD (-5%) selectivity 3,868 (212) -5.2%
-5 .2 %
Diff vs Base Case
15a) Yearly mill grade comparison
15b) Discounted cash flow comparison
Figure 15. Selectivity impacts on mill grade and cash flow
mine sequence held constant (plan based on IK model) and
process sequence varied by block model