XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 1425
per tonne, which is $1.85 per tonne less than the base case.
However, due to the higher plant yield, the less stringent
6,300 kcal contract would allow the breakeven realization
to drop by $7.15 per tonne. Therefore, the lowest possible
quality contract specification should be targeted by the sales
force for this particular coal since the difference between
$7.15 and $1.85 would generate an additional $5.30 per
tonne margin (assuming the price adjustments were purely
on a CV basis).
Similar benefits are seen for most coking coals, as
shown in Table 2. In this case, selling coking coal at the base
price of $250/tonne for 7% ash coal would require a $9.25/
tonne price increase to sell the coal at 6.85% ash, due to
major plant yield loss in producing the lower ash product.
Conversely, producing a 7.25% ash product for this coal
would allow the sales price to be dropped by $14.05/tonne
to break even. Huge opportunities can be missed if the
yield/quality exercises are not fully understood and applied.
Invariably, as long as the contractual coking character-
istics (swelling, fluidity, etc.) are maintained while produc-
ing a higher ash, the higher yield product generates more
revenue. As discussed later, this relationship will apply until
the added incremental ash causes greater revenue loss than
the tonnage gains from the yield increase.
EFFICIENCY MONITORING AND
MISPLACEMENT REDUCTION
The old adage that “…it is impossible to manage what is not
monitored…” is certainly true for CPPs. As such, plants
need to be designed for easier sampling on all circuits so
that routine monitoring of processing efficiency can occur.
The economic benefits resulting from such sampling pro-
tocols typically exceed the sampling and analytical costs by
a factor of 10–100 (Bethell 2015). Facilities that have not
been thoroughly sampled for extended periods of time are
highly inefficient as a result of deteriorating separation per-
formance created by the lack of operational data needed
to detect and correct operational issues. Unfortunately, dif-
ficult financial times often bring major costcutting at plant
sites, which frequently involves eliminating and/or reduc-
ing sampling programs. These cutbacks typically result in
minor cost savings while millions of dollars are lost in unre-
alized clean coal recovery due to inadequate monitoring
and unrecognized inefficient operations.
Opportunities for improvement from sampling often
include the identification of operational problems with
primary cleaning equipment such as dense medium sepa-
rators, fine concentrators and froth flotation cells. Table 3
summarizes data from a sampling program conducted
around a fine coal spiral circuit. The results show only a
small mass (0.74%) of high-ash (66.67%) rock present in
the clean coal and a low partition coefficient of 1.81%. In
contrast, a large mass (17.74%) of low-ash (7.42%) coal
was found to be present in the spiral refuse. Consequently,
the partition coefficient (PC) was only 91.2% for the Float
1.6 RD class. Without this type of information, the opera-
tors would be unaware of the poor level of performance
and no corrective measures would have been undertaken. It
was discovered that flow rates to the spirals were inadequate
and the cutter settings varied. Once these issues were fixed
performance improved radically (refer to Table 4), 1.6 float
recovery increased significantly from 91.2% to 98.97%.
Table 1. Quality volume price matrix for alternative energy coal applications
Parameter Unit (ar) Base Case
Alternatives
Option 1 Option 2 Option 3 Option 4
Shipped Quality CV (kcal/kg) 6,600 6,700 6,750 6,400 6,300
Available Clean Coal tonnes 350,000 340,000 333,000 390,000 411,000
Breakeven Realization $/tonne $49.58 $51.02 $52.48 $44.64 $42.43
Delta vs. Base Case $/tonne — $1.44 $2.90 -$4.94 -$7.15
Market Value $/tonne $49.58 $50.00 $50.37 $48.48 $47.73
Delta vs. Base Case $/tonne — $0.42 $0.79 -$1.10 -$1.85
Table 2. Price Matrix for Alternative Metallurgical Applications
Case
MET Shipped
Ash, %db
MET,
1,000 tonne
Base Product Realization
MET-LS,
$/Tonne
Breakeven
Realization
Base 7.00 420 $250.00 $250.00
Alt 1 6.85 405 $259.25
Alt 2 7.25 445 $235.95
per tonne, which is $1.85 per tonne less than the base case.
However, due to the higher plant yield, the less stringent
6,300 kcal contract would allow the breakeven realization
to drop by $7.15 per tonne. Therefore, the lowest possible
quality contract specification should be targeted by the sales
force for this particular coal since the difference between
$7.15 and $1.85 would generate an additional $5.30 per
tonne margin (assuming the price adjustments were purely
on a CV basis).
Similar benefits are seen for most coking coals, as
shown in Table 2. In this case, selling coking coal at the base
price of $250/tonne for 7% ash coal would require a $9.25/
tonne price increase to sell the coal at 6.85% ash, due to
major plant yield loss in producing the lower ash product.
Conversely, producing a 7.25% ash product for this coal
would allow the sales price to be dropped by $14.05/tonne
to break even. Huge opportunities can be missed if the
yield/quality exercises are not fully understood and applied.
Invariably, as long as the contractual coking character-
istics (swelling, fluidity, etc.) are maintained while produc-
ing a higher ash, the higher yield product generates more
revenue. As discussed later, this relationship will apply until
the added incremental ash causes greater revenue loss than
the tonnage gains from the yield increase.
EFFICIENCY MONITORING AND
MISPLACEMENT REDUCTION
The old adage that “…it is impossible to manage what is not
monitored…” is certainly true for CPPs. As such, plants
need to be designed for easier sampling on all circuits so
that routine monitoring of processing efficiency can occur.
The economic benefits resulting from such sampling pro-
tocols typically exceed the sampling and analytical costs by
a factor of 10–100 (Bethell 2015). Facilities that have not
been thoroughly sampled for extended periods of time are
highly inefficient as a result of deteriorating separation per-
formance created by the lack of operational data needed
to detect and correct operational issues. Unfortunately, dif-
ficult financial times often bring major costcutting at plant
sites, which frequently involves eliminating and/or reduc-
ing sampling programs. These cutbacks typically result in
minor cost savings while millions of dollars are lost in unre-
alized clean coal recovery due to inadequate monitoring
and unrecognized inefficient operations.
Opportunities for improvement from sampling often
include the identification of operational problems with
primary cleaning equipment such as dense medium sepa-
rators, fine concentrators and froth flotation cells. Table 3
summarizes data from a sampling program conducted
around a fine coal spiral circuit. The results show only a
small mass (0.74%) of high-ash (66.67%) rock present in
the clean coal and a low partition coefficient of 1.81%. In
contrast, a large mass (17.74%) of low-ash (7.42%) coal
was found to be present in the spiral refuse. Consequently,
the partition coefficient (PC) was only 91.2% for the Float
1.6 RD class. Without this type of information, the opera-
tors would be unaware of the poor level of performance
and no corrective measures would have been undertaken. It
was discovered that flow rates to the spirals were inadequate
and the cutter settings varied. Once these issues were fixed
performance improved radically (refer to Table 4), 1.6 float
recovery increased significantly from 91.2% to 98.97%.
Table 1. Quality volume price matrix for alternative energy coal applications
Parameter Unit (ar) Base Case
Alternatives
Option 1 Option 2 Option 3 Option 4
Shipped Quality CV (kcal/kg) 6,600 6,700 6,750 6,400 6,300
Available Clean Coal tonnes 350,000 340,000 333,000 390,000 411,000
Breakeven Realization $/tonne $49.58 $51.02 $52.48 $44.64 $42.43
Delta vs. Base Case $/tonne — $1.44 $2.90 -$4.94 -$7.15
Market Value $/tonne $49.58 $50.00 $50.37 $48.48 $47.73
Delta vs. Base Case $/tonne — $0.42 $0.79 -$1.10 -$1.85
Table 2. Price Matrix for Alternative Metallurgical Applications
Case
MET Shipped
Ash, %db
MET,
1,000 tonne
Base Product Realization
MET-LS,
$/Tonne
Breakeven
Realization
Base 7.00 420 $250.00 $250.00
Alt 1 6.85 405 $259.25
Alt 2 7.25 445 $235.95