10
Dust Concentration Analysis
A closer examination of the concentration data reveals a
clear relationship between the measured dust levels and the
actual degree of pick wear, as represented by the pick tip
radius. Figure 17 presents the quantitative concentration
data for all rock types, plotted and compared against the
corresponding pick tip radii data. Across all rock samples,
this figure demonstrates consistent, positive linear trends,
indicating that as the pick wear increases, the dust concen-
tration also rises.
INFERENCE
Analysis of particle size distribution at multiple testing
parameters reveals strong relationships between cutting
parameters and fragmentation properties. Larger fragments
have a different distribution depending on penetration
depth, with 100–200mm concentrations (53 particles) at
0.5-inch penetration as opposed to 200–300mm concen-
trations (22 particles) at 0.2-inch penetration. Larger Fines
correlate in an opposite way to penetration depth (456.01g
at 0.2-inch and 269.6g at 0.5-inch) but directly to bit wear
(369.24g at new bits vs 627.73g at worn bits). Data from
laser diffraction also describes the evolution of the finer par-
ticles, with distinctive distributions from new bits (highest
at 249.9m, 0.4%) to worn bits (increased fines at 2.313m,
8.89%). This wear curve has a major impact on dust produc-
tion, especially in coal, where the concentration increases
from 300 to 800 mg/m3 with an increase in bit radius from
0.028 (new) to 0.201 inches (used), and specific energy
demands double from 1.879 to 3.757 hp-hr/yd3.
CONCLUSIONS
Understanding the distribution of particle size at different
scales offers key insights into the relationship between cut-
ting parameters and mining efficiency. Its work shows that
bit wear dramatically affects fragmentation properties at
all scales, from larger chips to very small dust grains. The
incremental wear from new (0.028 inches radius) to worn
(0.201 inches radius) conditions result in a 70% increase in
larger fines production (369.24g to 627.73g), while pen-
etration depth correlates invertely with larger fines produc-
tion (456.01g at 0.2-inch to 269.6g at 0.5-inch). This is
shown by laser diffraction data showing the evolution of
fine particle concentrations from new bits (highest 249.9m)
to worn bits (fines increase to 2.313m) and, for coal min-
ing dust, a dramatic three-fold rise between 300 and 800
mg/m3. These adjustments are matched by a doubling of
specific energy use from 1.879 to 3.757 hp-hr/yd3, indicat-
ing its considerable impact on performance. The practical
implications of these results for mining operations are rel-
evant, and they suggest that optimal cutting performance
and dust management rely on carefully monitoring pen-
etration depth and bit wear. The results show that at higher
depth, picks require more energy but results in a smaller
amount of fines generation, while performance degrades in
all respects. It is this deep understanding that helps optimize
New Bit Worn-out Moderately Worn-Out
Size(um) %Chan %Pass Size(um) %Chan %Pass Size(um) %Chan %Pass
2,000.0 -100.0 2000 0 100 2000 0 100
1,674.0 -100.0 1674 0 100 1674 0 100
1,408.0 -100.0 1408 0 100 1408 0 100
1,184.0 -100.0 1184 0 100 1184 0 100
995.6 -100.0 995.6 0 100 995.6 0 100
837.2 -100.0 837.2 0 100 837.2 0 100
704.0 -100.0 704 0 100 704 0 100
592.0 -100.0 592 0 100 592 0 100
497.8 -100.0 497.8 0 100 497.8 0 100
418.6 -100.0 418.6 0 100 418.6 0 100
352.0 -100.0 352 0 100 352 0 100
296.0 -100.0 296 0 100 296 0 100
248.9 0.4 100.0 248.9 0 100 248.9 0 100
209.3 -99.6 209.3 0 100 209.3 0 100
176.0 0.3 99.6 176 0 100 176 0 100
148.0 0.4 99.4 148 0.12 100 148 0 100
124.5 0.1 99.0 124.5 0.42 99.88 124.5 0 100
104.7 0.5 98.9 104.7 0.58 99.46 104.7 0 100
88.0 0.6 98.4 88 0.93 98.88 88 0.01 100
74.0 0.6 97.8 74 1.5 97.95 74 0.02 99.99
62.2 0.5 97.1 62.23 2.35 96.45 62.23 0.03 99.97
52.3 1.6 96.6 52.33 4.05 94.1 52.33 0.04 99.94
44.0 3.6 95.0 44 6.33 90.05 44 0.06 99.9
37.0 6.8 91.4 37 8.9 83.72 37 0.11 99.84
31.1 10.4 84.6 31.11 10.88 74.82 31.11 0.19 99.73
26.2 12.3 74.2 26.16 11.3 63.94 26.16 0.31 99.54
22.0 12.1 61.9 22 10.63 52.64 22 0.48 99.23
18.5 11.0 49.8 18.5 9.27 42.01 18.5 0.74 98.75
15.6 9.8 38.8 15.56 7.88 32.74 15.56 1.15 98.01
13.1 8.6 29.0 13.08 6.6 24.86 13.08 1.8 96.86
11.0 7.3 20.4 11 5.4 18.26 11 2.74 95.06
9.3 5.6 13.2 9.25 4.24 12.86 9.25 3.98 92.32
7.8 3.8 7.6 7.78 3.15 8.62 7.78 5.47 88.34
6.5 2.2 3.8 6.54 2.16 5.47 6.54 7 82.87
5.5 1.1 1.6 5.5 1.38 3.31 5.5 8.55 75.87
4.6 0.5 0.5 4.63 0.92 1.93 4.63 10.62 67.32
3.89 0.61 1.01 3.89 12.88 56.7
3.27 15.72 43.82
2.75 19.21 28.1
2.313 8.89 8.89
Figure 16. Particle size distribution of small fines vs bit
condition in laser diffraction
0
100
200
300
400
500
600
700
800
900
New Mod Worn
Wear Condition
Concrete Limestone Coal Sandstone
Figure 17. Dust concentration vs bit condition
)3m/gm(noitartnecnoC
Dust Concentration Analysis
A closer examination of the concentration data reveals a
clear relationship between the measured dust levels and the
actual degree of pick wear, as represented by the pick tip
radius. Figure 17 presents the quantitative concentration
data for all rock types, plotted and compared against the
corresponding pick tip radii data. Across all rock samples,
this figure demonstrates consistent, positive linear trends,
indicating that as the pick wear increases, the dust concen-
tration also rises.
INFERENCE
Analysis of particle size distribution at multiple testing
parameters reveals strong relationships between cutting
parameters and fragmentation properties. Larger fragments
have a different distribution depending on penetration
depth, with 100–200mm concentrations (53 particles) at
0.5-inch penetration as opposed to 200–300mm concen-
trations (22 particles) at 0.2-inch penetration. Larger Fines
correlate in an opposite way to penetration depth (456.01g
at 0.2-inch and 269.6g at 0.5-inch) but directly to bit wear
(369.24g at new bits vs 627.73g at worn bits). Data from
laser diffraction also describes the evolution of the finer par-
ticles, with distinctive distributions from new bits (highest
at 249.9m, 0.4%) to worn bits (increased fines at 2.313m,
8.89%). This wear curve has a major impact on dust produc-
tion, especially in coal, where the concentration increases
from 300 to 800 mg/m3 with an increase in bit radius from
0.028 (new) to 0.201 inches (used), and specific energy
demands double from 1.879 to 3.757 hp-hr/yd3.
CONCLUSIONS
Understanding the distribution of particle size at different
scales offers key insights into the relationship between cut-
ting parameters and mining efficiency. Its work shows that
bit wear dramatically affects fragmentation properties at
all scales, from larger chips to very small dust grains. The
incremental wear from new (0.028 inches radius) to worn
(0.201 inches radius) conditions result in a 70% increase in
larger fines production (369.24g to 627.73g), while pen-
etration depth correlates invertely with larger fines produc-
tion (456.01g at 0.2-inch to 269.6g at 0.5-inch). This is
shown by laser diffraction data showing the evolution of
fine particle concentrations from new bits (highest 249.9m)
to worn bits (fines increase to 2.313m) and, for coal min-
ing dust, a dramatic three-fold rise between 300 and 800
mg/m3. These adjustments are matched by a doubling of
specific energy use from 1.879 to 3.757 hp-hr/yd3, indicat-
ing its considerable impact on performance. The practical
implications of these results for mining operations are rel-
evant, and they suggest that optimal cutting performance
and dust management rely on carefully monitoring pen-
etration depth and bit wear. The results show that at higher
depth, picks require more energy but results in a smaller
amount of fines generation, while performance degrades in
all respects. It is this deep understanding that helps optimize
New Bit Worn-out Moderately Worn-Out
Size(um) %Chan %Pass Size(um) %Chan %Pass Size(um) %Chan %Pass
2,000.0 -100.0 2000 0 100 2000 0 100
1,674.0 -100.0 1674 0 100 1674 0 100
1,408.0 -100.0 1408 0 100 1408 0 100
1,184.0 -100.0 1184 0 100 1184 0 100
995.6 -100.0 995.6 0 100 995.6 0 100
837.2 -100.0 837.2 0 100 837.2 0 100
704.0 -100.0 704 0 100 704 0 100
592.0 -100.0 592 0 100 592 0 100
497.8 -100.0 497.8 0 100 497.8 0 100
418.6 -100.0 418.6 0 100 418.6 0 100
352.0 -100.0 352 0 100 352 0 100
296.0 -100.0 296 0 100 296 0 100
248.9 0.4 100.0 248.9 0 100 248.9 0 100
209.3 -99.6 209.3 0 100 209.3 0 100
176.0 0.3 99.6 176 0 100 176 0 100
148.0 0.4 99.4 148 0.12 100 148 0 100
124.5 0.1 99.0 124.5 0.42 99.88 124.5 0 100
104.7 0.5 98.9 104.7 0.58 99.46 104.7 0 100
88.0 0.6 98.4 88 0.93 98.88 88 0.01 100
74.0 0.6 97.8 74 1.5 97.95 74 0.02 99.99
62.2 0.5 97.1 62.23 2.35 96.45 62.23 0.03 99.97
52.3 1.6 96.6 52.33 4.05 94.1 52.33 0.04 99.94
44.0 3.6 95.0 44 6.33 90.05 44 0.06 99.9
37.0 6.8 91.4 37 8.9 83.72 37 0.11 99.84
31.1 10.4 84.6 31.11 10.88 74.82 31.11 0.19 99.73
26.2 12.3 74.2 26.16 11.3 63.94 26.16 0.31 99.54
22.0 12.1 61.9 22 10.63 52.64 22 0.48 99.23
18.5 11.0 49.8 18.5 9.27 42.01 18.5 0.74 98.75
15.6 9.8 38.8 15.56 7.88 32.74 15.56 1.15 98.01
13.1 8.6 29.0 13.08 6.6 24.86 13.08 1.8 96.86
11.0 7.3 20.4 11 5.4 18.26 11 2.74 95.06
9.3 5.6 13.2 9.25 4.24 12.86 9.25 3.98 92.32
7.8 3.8 7.6 7.78 3.15 8.62 7.78 5.47 88.34
6.5 2.2 3.8 6.54 2.16 5.47 6.54 7 82.87
5.5 1.1 1.6 5.5 1.38 3.31 5.5 8.55 75.87
4.6 0.5 0.5 4.63 0.92 1.93 4.63 10.62 67.32
3.89 0.61 1.01 3.89 12.88 56.7
3.27 15.72 43.82
2.75 19.21 28.1
2.313 8.89 8.89
Figure 16. Particle size distribution of small fines vs bit
condition in laser diffraction
0
100
200
300
400
500
600
700
800
900
New Mod Worn
Wear Condition
Concrete Limestone Coal Sandstone
Figure 17. Dust concentration vs bit condition
)3m/gm(noitartnecnoC