May - Library
May - Library
May - Library
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T h i rd l y, Pareto analysis of equipment downtime may miss<br />
identifying: (i) individual events having high associated downtime or<br />
(ii) frequently occurring failures that consume relatively little downtime<br />
yet cause frequent operational disturbances. An example of the form e r<br />
is the failure of the transmission in a mechanical mining truck. An<br />
example of the latter are repairs to the truck’s driving lights. Failures<br />
that frequently re-occur often have significant hidden costs. For<br />
example, if the truck has to re t u rn to the truck shop to have a light<br />
replaced, the time lost travelling to and from the shop may dramatically<br />
increase the opportunity costs associated with lost production.<br />
Fourthly, when there is a lot of data to analyse we commonly use<br />
data stratification or hierarchical decomposition techniques. A Pare t o<br />
histogram is pre p a red for downtime data grouped by major equipment<br />
14.0%<br />
12.0%<br />
10.0%<br />
8.0%<br />
6.0%<br />
4.0%<br />
2.0%<br />
0.0%<br />
Downtime Priorities, Jack-knife Diagrams, Business Cycle<br />
or functional failure type. More detailed Pareto graphs are prepared<br />
for the downtime associated with those components or functional<br />
f a i l u res judged to be the most significant contributors of downtime.<br />
T h e re are two potential problems with the use of stratified Pare t o<br />
analyses: (i) because hierarchical Pareto graphs are only pre p a re d<br />
for the significant contributors of system downtime, failure s<br />
associated with less significant components or functional failures will<br />
not be explored. It is possible that we may miss identifying a<br />
component, or failure mode that offers significant potential for<br />
reliability improvement. (ii) The same failure mode may appear in<br />
several of the lower level Pareto histograms. We may fail to identify<br />
or underestimate the relative importance of these common cause<br />
failure modes.<br />
1 2 11 3 10 7 12 8 5 15 6 9 4 17 14 16 13<br />
Failure Code<br />
Figure 1: Pareto hisogram of unplanned shovel electrical downtime<br />
Code Description Quantity Duration % Time % Cum.<br />
(min)<br />
1 Electrical inspections 30 1015 13.0 13.0<br />
2 Damaged feeder cable 15 785 10.1 23.1<br />
11 Motor over temperature 36 745 9.6 32.6<br />
3 Change of substation or shovel move 27 690 8.8 41.5<br />
10 Overload relay 23 685 8.8 50.3<br />
7 Auxiliary motors 13 600 7.7 58.0<br />
12 Earth faults 7 575 7.4 65.3<br />
8 Main motors 12 555 7.1 72.5<br />
5 Power cuts to substations 21 395 5.1 77.5<br />
15 Air compressor 8 355 4.6 82.1<br />
6 Rope limit protection 10 277 3.6 85.6<br />
9 Lighting system 26 240 3.1 88.7<br />
4 Coupling repairs or checks 15 225 2.9 91.6<br />
17 Over current faults 6 220 2.8 94.4<br />
14 Control system 7 165 2.1 96.5<br />
16 Operator controls 5 155 2.0 98.5<br />
13 Miscellaneous 9 115 1.5 100<br />
TOTAL 270 7797 100<br />
Table 1: Unplanned shovel electrical downtime.<br />
100.0%<br />
90.0%<br />
80.0%<br />
70.0%<br />
60.0%<br />
50.0%<br />
40.0%<br />
30.0%<br />
20.0%<br />
10.0%<br />
0.0%<br />
16