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It can be seen that significant improvement has been made with
respect to two of the failure codes over the period of the study.
Unplanned failures to the shovel lubrication system were chronic in
1997 and 1998, and not classified in 1999. Similarly, the total downtime
due to failures of controls in the operator cabin has decre a s e d .
H o w e v e r, unplanned failures to the swing system (comprising the two
swing motors, spur gears and main ring gear) are obviously an area
of concern, increasing from acute in 1997 to chronic and acute in 1999.
Likewise, unplanned stoppages due to motor over- t e m p e r a t u re alarm s
( a l a rms) also increased in both frequency and duration (data was not
available for the 1999 period to confirm this tendency).
Jack-knife trend plots provide a very useful visual means of
analysing and controlling maintenance perf o rmance. It is easy to see
the “wins and losses” of the maintenance department. Another
potential application of jack-knife trend diagrams is to the pre p a r a t i o n
of maintenance budgets. A log scatterplot of the repair costs incurre d
during the most recent time period could assist a maintenance
manager to fix perf o rmance targets for forthcoming periods. It is
postulated that windows-based software could be developed to help
automate this pro c e d u re. Using a mouse, the points re p re s e n t i n g
failure codes in the log scatterplot could be selected and dragged to
d e s i red target positions. The software could then automatically
calculate the resulting cost and downtime reductions, as well as
display the corresponding operating budget for the maintenance
department.
8. Conclusions
The use of logarithmic (log) scatterplots overcomes many of the
s h o rtcomings of Pareto analysis for generating lists of equipment
downtime priorities. Log scatterplots preserve the ranking scheme of
P a reto histograms, but provide additional information content
re g a rding failure frequencies and mean time to re s t o re service. A
methodology is provided for calculating thresholds for classifying
f a i l u res according to acute or chronic characteristics. The graphs
readily permit the identification of problems affecting system re l i a b i l i t y,
Downtime Priorities, Jack-knife Diagrams, Business Cycle
a v a i l a b i l i t y, and maintainability. Jack-knife limits can be established
for determining failure priorities. The orientation of the jack-knife limit
depends on the relative importance of repair costs to the economic
consequences of downtime, which in turn is affected by changes in
the business cycle.
Log scatterplots are not necessarily intended to replace traditional
P a reto analysis techniques. The two techniques can be beneficially
used in parallel. In addition, elements of the methodology outline in
the paper, such as the classification of acute and chronic failures, can
be usefully adapted for use in conventional Pareto analysis.
Since their inception in 1999, log scatterplots and jack-knife
diagrams have been profitably employed by a number of mining
companies and mining equipment suppliers. In Chile, a larg e
maintenance service provider now regularly used jack-knife diagrams
to monitor equipment downtime for controlling maintenance and re p a i r
(MARC) contracts.
9. Acknowledgements
The author would like to thank Komatsu Chile and Modular Mining
Systems Chile for supporting the development of the log scatterplot
m e t h o d o l o g y. The paper has also benefited from the thesis work of
Cristian Aranguiz and Carlos Turina, final year students of the Mining
Centre of the Catholic University of Chile.
10. References
Knights, P.F. (1999) “Analysing Breakdowns” Mining Magazine, Vol.
181 No. 3, pp.165-171, September.
Knights, P.F. (2001) “Rethinking Pareto Analysis: Maintenance
Applications of Logarithmic Scatterplots”, Journal of Quality in
Maintenance Engineering, Vol 7, No.4, pp252-263.
Moore, R. (2002) “Making Common Sense Common Practice:
Models for Manufacturing Excellence”, Butterworth Heinemann.
Moubray, J. (1997) “Reliability-Centered Maintenance”, 2nd Ed.,
Industrial Press Inc., New York.
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