Shift production time 22... 6... cee cee ee ence eens 360 min

Coal density 22... cece cence tenes 0.042 st/cu ft
Continuous miner tram rate! 2. ee eee 0.015 min/ft
Roof bolter tram rate 2... ete eeeae 0.010 min/ft
Switch-in time per haul cycle? ....... 0.15 min
Switch-out time per haul cycle* 0.15 min
Miner in-place constants»... 0.26... cece cee eee ee eens 4.0 min
Bolter in-place constant

Length of belt to be advanced . 1.2... eee ec eens 125 ft
Miner load rate 2... eee eee eens 0.20 min/st
Shuttle car (S/C) payload ........2..00004 72 st
S/C tram rate from miner to change point..........0..0-00-0-00- 0.0030 min/ft
S/C tram rate from change point to dump 0.0028 min/ft
S/C tram rate from dump to change point 0.0027 min/ft
S/C tram rate from change point to mine 0.0026 min/ft

S/C discharge time .. 2... cece eee
Roof bolter cycle time
Mining height 22... 0... e tenes

An 8 x 8 test matrix was constructed, with payload varied from base case conditions
(7.20 st) to 35% under base case (4.68 st) and discharge time varied from base case
conditions (0.56 min) to 35% over base case (0.756 min), both in 5% increments. The
objective was to test the effects of the changes in these operating characteristics on such
measures as production rate, time to load the cut sequence, load time percentage, percentage
of time waiting for a shuttle car, and st per shuttle car mile. To remove variability within
sets of runs, all tram rates, payloads, and load rates were treated as constants, and no
breakdowns were permitted.

Representative Test Results

Figure 2 shows the interrelationships among discharge time increase, payload

1CONSIM requires input of tram rates in units of min/ft.

2Time required for an empty shuttle car to provide clearance for a loaded car by
tramming into an entry at the change out point.

>Time required by the shuttle car to return to the haulage road after switch-in.

‘Time required for any function other than production (¢.g., gas check, hang brattice,
check sprays, prepare miner to load).


LEGEND
Length of continuous miner = 32 ft
Length of shuttle car = 28 ft
Starting distance = 50 ft

A
8
c
10)

oO oO
=
B---S LSU SIRS TALS ots sepnaiaiadaieietaie 7
2 Pot ray ! 1
124 Sy
1g LX
° lee 81 !
of oR Ge E |
ss A AY < !
eo tt st miotelalete rt ! x]
SB IRIBIS Sr Bi wBint nig = £
8 --pts4—4 23 - a ae = oS
= fis ig g S
rel red ae
Les Ls ° @ 3
ral ' | ay 2 ® E
10 181 iw = = oS
°C, ret 1 2 = eo
& --5-- et | a w S
B tee form \ Le -—_—
Bt LS SESS Ss pan a al eirtuieaiaieietatata °
=z lm ret
He be
18! iS
m1 'y
18 \
“ ret t=
2,18! 1
SB ISIVIS SQ wiabete:
§ ---CE SQ PU LE LBS TOS
=x INT rot ry
LN Ls] i
1g! 1S 3
HO rey
|
- bed {
2.4 48h fe |
£7 SOE Trica rs Pater needs ube
ao iS; @int Ti elo
B--SALSLSLS TEL SS Slo
x

Discharge change out distance = 30 ft

77 Cut numbers


in tram rate of 0.0007 min/ft in each of the four haul segments (0.0023 from 0.003, 0.0021
from 0.0028, 0.002 from 0.0027, 0.0019 from 0.0026 (see previous input data), amounting
to increases above base case of 23.3%, 25%, 25.9%, and 26.9%, respectively) results in
only a maximum 0.136% increase in simulated production rate, or 0.036 st/min. In one
shift (assuming 360 min of production time), this totals about 13 deferred tons. These
13 st/shift are significant, as it represents the existing paradigm of "working faster."
However, it is not the only solution set. Another solution might imply that the cost
consequences of accidents and downtime as a result of overspeed on haul roads, at least in
this example, could exceed the economic benefit of increasing tram speed over base case
conditions. In this case, a simulated tram rate increase of approximately 25% over base
case velocities resulted in a simulated production increase equivalent to less than two
additional shuttle car loads per shift. An alternative interpretation of the CONSIM results
suggests that reducing the variability in mining system downtime (c.g., cable damage,
canopy and undercarriage damage) could more than offset the deferred 13 tons of
production (all of which were obtained in the simulation by simply "running faster").

In 1991, 331 accidents involving shuttle car operation in U. S. underground coal mines
were reported to MSHA. Of this number, 297 (89.7%) were classified in the "powered
haulage" category. In an analysis of 267 of these 297 shuttle car accidents®, "operating at
a speed too great for existing conditions" was the inferable primary causal factor in 161

(60.3%). These 161 accidents resulted in a total of 8416 days lost and a reported total cost

‘Data were omitted for 30 reported accidents for which no narrative was available. The
balance was sorted by two researchers, with consensus reached regarding the role that
excessive speed had on accident causation.


decrement, and simulated production rate. As one would expect, production decreases with
a decrease in effective payload. At the base case conditions, for example, the simulated
production is 2.61 st/min; at a 35% payload reduction, the simulated production is 2.30
st/min, This represents an 11.9% production decrement. Interestingly, simulated produc-
tion actually increases slightly (and nonsignificantly) with a 5% reduction in payload from
base case conditions (7.20 to 6.84 st) before predictably decreasing as payload is
incrementally reduced between runs. This occurs because of the complex interactions
among load time, payload, and tram rates at these near-optimum payloads, which are best
analyzed by mathematical simulation.’ A further potential complication is the variability in
clean-up car payload in each of the 77 cuts of the sequence between successive sets of runs.

Figure 2 also shows that a 35% increase in discharge time over the base case
conditions results in only a 0.55% production decrement (compared to an 11.9% decrement
for a simulated 35% payload reduction, as discussed above). These results suggest that
maintaining a good payload is much more important than minimizing dump time, a premise
that is driving a recent research emphasis into possible production gains through chemical
treatment of shuttle car payloads during continuous mining operation (Leonard, et al, 1994).
This example shows how production analyses can be used to rank candidate subtasks for
performance improvement attempts and to help carry out cost-benefit analyses.

Figure 3 shows the effect of tram rate increase on simulated production rate. For each
of the eight simulation runs, velocity on each of the four shuttle car haul components was
increased in increments of 0.0001 min/ft, which, for example, amounts to an increase of

11.5 ft/min (0.131 mph) between tram rates of 0.003 min/ft and 0.0029 min/ft. An increase

5For payloads above about 7 st, there were no further significant production gains, even
if it can be assumed that discharge time can be held constant (Wiehagen, et al, p. 32).

6


the congruency between production and operator training by providing a unique cost

linkage between performance engineering and human behavior.

Acknowledgement
Work was performed under appointment in the Oak Ridge Institute for Science and
Education Faculty Research Participation program at the U. S. Bureau of Mines, Pittsburgh

Research Center, Pittsburgh, PA.

References

Bird, F. E., 1980, Mine Safety and Loss Control: A Management Guide, Institute Press,
Loganville, GA, pp. 17-18.

Leonard, J. W., Pradakar, A., and Groppo, J. G., 1994, “Are Big Gains in Coal Loading
Productivity Possible?: A Look at Some of the Fundamentals," Mining Engineering, Vol.
46, No. 1, Jan., pp. 65-69.

Topuz, E., Nasuf, E., and Ramachandran, D., 1989, CONSIM User’s Manual, 2nd rev.,
Virginia Tech, Blacksburg, VA, 81 pp.

Wiehagen, W. J., Lineberry, G. T., Lacefield, W. E., Brnich, M. J., and Rethi, L. L., 1994,
"The Work Crew Performance Model: A Method for Evaluating Training and Performance
in the Mining Industry," Information Circular 9394, U.S. Bureau of Mines, 32 pp.

Conversions
1 ft = 0.3048 m
1 cu ft = 0.02832 cu m
1 mph = 0.447 m/s
1 st = 0.9072 tonne
List of Figure Captions
Figure 1. Hypothetical, idealized section layout, showing cut sequencing and some

system variables (After Topuz, Nasuf, and Ramachandran, p. 32).

Figure 2. Simulation results; interrelationships among payload decrement, discharge
time increase, and production rate.

Figure 3. Simulation results; effect of tram speed increase on production rate; 7.20 st
payload, 0.56 min discharge time.

9


THE COST RELATIONSHIP BETWEEN PERFORMANCE
ENGINEERING AND HUMAN BEHAVIOR

G. T. Lineberry
W. J. Wiehagen

A Paradigm Shift

As market economists, mine managers are interested in "staying in business" and even
"prospering." Bottom-line results are the “order of the day." Concern for bottom-line
results invokes questions such as: How much was produced? At what cost? And, was
anyone injured? While these questions will always carry everyday emphasis at the mine,
they are fundamentally lacking in that they often appear, especially to lower levels of
management and to the production worker, as preeminent concerns.

Driven by market economics, many organizations have decentralized, outsourced,
downsized, restructured, and formed new coalitions. Investments in new technology and
concentration on productivity have been part and parcel with these changes, contributing to
improvements in both safety and efficiency. A reason for (and, perhaps a result of) these
improvements has been the development of a highly experienced and flexible work force.

These changes in mining present an interesting opportunity to modify a few paradigms
about work life in general, and perhaps a few paradigms about how we invest in the miner,
in particular. Studying these issues now might offer some interesting opportunities for the
future, as the foundations for the next generation of mine workers are laid. With the
average “experienced" U.S. miner five to fifteen years from retirement, perhaps a key
determinant of future success in the world market might be how well we make the
transition from today’s work force to the work force of tomorrow. We can ill afford to
wait a few more years to tap into the special knowledge residing within a veteran mining
work force. The WCPM (Work Crew Performance Model, see pp. _) is one approach to

defining, capturing, and transferring this expertise.


H/UIW OL “ASVAYONI SV WEL
9 g v g é] | O_.
T T T T ! T a7?
“Ajeanoodsar “ogcge pur “%OL'E “LSE
“~HECEE JO SoweI teI] oSed aseq dAoge 4¢ ‘?’
sasealoul 0} JUaTeAInbe st yuaudes
[ney Youd ut y/uTW 1QQ0'0 JO aseorUt
yel wed] [eUSWAIOUL UY :330N
472%
43°32
-e——_o——_4° ¢
o———_e-—""* —————o
! | 1 j 1 ! Lz

ulus ‘31VY NOILONdOYd


od “3SV3YNONIT SWIL S9YXVHOSIC
Se Og Se 02 St Ol

Sa S29 Slm Go

OfV O2X% Od O@

49d juswasoap pdolkog
43m

2%

3LvY¥ NOILONGOYd

‘

uli /4s


of $ 1.25 M. Applying the 1:10:30:600 accident ratio’ (Bird, 1980), coupled with the
potential for equipment damage, accelerated equipment degradation, and compromise of
structural integrity (knocked out roadway timbers, broken bolts, reduced pillar size due to
rib rubbing or glancing blows), it is likely that the cost consequences of operating at unsafe
speeds far exceed this reported total. Attention to these many sources of negative cost
consequences offers the potential for providing a much larger basis for more effective

control of total incident losses than the problematic dependent measure of injury data alone.

Summary

Use of a face production simulator, such as CONSIM, in conjunction with an
empirically-based method for successively improving work crew performance, such as the
WCPM, can help identify and rank cycle elements for implementation of intervention
strategies. This, in turn, can help human resource developers better target groups of tasks
and subtasks as candidates for improved training or coaching, for job/equipment/condition
modification, or for changes in management practices/policies. The net result is the
acquisition of an ability to offer more specific guidelines for human resource development
at the mine site-- guidelines that are based on empirical evidence and meaningful analysis
of performance metrics. Even pure "market economists," tempted always to seek
technology and human operators that "run faster at “less cost," might now consider
investments that empower workers to "run smarter."

Moreover, use of CONSIM has shown, by example, how common operating parameters
(e.g., payload, tram rate) can be used as cost-conscious indicators of performance variability

and therefore targeted for performance improvement. This field trial of the WCPM affirms

Major injuries (death, disability, lost time, or medical treatment): minor injuries (first-
aid): property damage accidents: incidents with no apparent injury or property damage.

8


observable data and probability distributions for these data can be linked to operator
proficiency. Unfortunately, in real life, the cost consequences resulting from production
decrements caused by deviations from optimum operation frequently are subtle, of
unpredictable magnitude, and can be confounded by other variables (e.g., breakdown
characteristics and empirical distributions of individual cycle time elements and operation
tates). This case study, however, permitted investigation into the effects that operator-

influenced parameters alone can have on production.

Test Design

The major events in CONSIM include cutting and loading, hauling, roof bolting, and
equipment breakdowns. Input data are relatively simple and include essentially:
© the dimensions of the section (e.g., number of headings; number of cuts in the
sequence; dimensions of pillars, headings, and breakthroughs; cut depth; change out
distance)
© the operational characteristics of the face equipment (e.g., length; tram rates of miner
and bolter; breakdown data; empirical distributions for shuttle car payload, load rate,
tram rate, and discharge rate; in-place constants).
Several of these operating parameters can be viewed as being linked to proficiency. For
example, an exemplary shuttle car operator consistently will achieve near-optimum payload,
will interact with the miner operator to maintain a high load rate, and will minimize
discharge time. CONSIM permits rapid investigation into the effects of changes in these
and other operating parameters on production.
Figure 1 shows the hypothetical, idealized section layout used for the analyses.

Pertinent input data for the base case not conveyed in Figure 1 are as follows:


work site. It implies learning from veteran mining personnel that have gone well "beyond
the book." This approach to learning and to integrating training with everyday work life
can help answer such questions as: What constitutes desirable performance as a shuttle car
operator, a miner operator, or a dozer operator? What characterizes exemplary performance
within the context of the work system, the technology, and the work crew? How can
investments in the worker be linked to measurable results within the organization? This
paper explores these questions and makes recommendations for enhancing the cost linkages

between investments in people and the mine’s monthly cost sheets.

Use of CONSIM

The use of CONSIM, a discrete, event-oriented simulation program for analyzing face
operations in continuous mining systems (Topuz, et al, 1989), offers a unique and
interesting engineering test of the WCPM. The rigor of CONSIM, a standard
computational tool in the mining industry, enables study of a complex problem that mine
managers relate to on a daily basis: the problem of maximizing the return on investment--
both on technology and people. _In a traditional sense, CONSIM gives insight into the
effect of changes in work place geometry, section layout, and equipment operating
characteristics, on estimates of production. The authors have modified the use of CONSIM
(but not the mechanics) to a more robust and richer application through integration of
operator variability into the work system (Wiehagen, et al, 1994).

The test reported here summarizes an investigation into the impacts of variability of
shuttle car operator performance on estimates of production. This variability was expressed
in terms of measurable operating parameters inherent in the duty cycle of a continuous
mining development section. This study recognized that production can be impacted by

variability in such parameters as payload, load time, dump time, and tram rate, and that


The WCPM suggests a paradigm shift, moving from a focus on products (quantity) to
a focus on the process (quality). It also involves a slight change in the process--a different
way to think and work. Of great importance, it entails: a belief and a commitment to
people within the organization; a commitment to collect simple, but interesting, data;
exploration for insightful ways to plot and integrate that data; and finally the search for
creative methods to reinvest that knowledge back into the organization, that is, back into the
work force.

As a way of thinking, the WCPM subordinates information about how much is
produced daily or how many were injured over a year’s time to concern and detail for how
the individual's and the work crew’s performance contribute toward meeting organizational
goals. Drawing upon the expertise within members of that work crew to address and solve
operational problems is one approach for meeting organizational goals. This everday focus
on how we work is hypothesized by the WCPM to make the difference between a good
section supervisor and the average one; an exemplar continuous miner operator and the run-
of-the-mill one; 4 mining crew that produces consistently high quantities, but, inadvertently,
degrades the production of other units. The WCPM permits objective and reliable
performance data to be collected. This data then can be used: to define variability within
tasks of work crew members; to relate observed variability to a cost consequence; and to
more meaningfully analyze performance through the integration of traditional analytical
tools, such as the production simulator, CONSIM, with a recommended behavioral

approach, the WCPM.

Basis for Engineering Test
Most equipment selections and purchases involve a field trial, a test of the system.
Technology is routinely bench tested at the manufacturer’s facility, government agencies,
and the mine site. The WCPM suggests a similar, but more practical, method for testing

the performance of a work system--a test for how technology is used (by people) at the