Casestudie Breakdown prediction Contell PILOT - Transumo

that are not caused by user interaction. This improvement would extend the currently
limited possibility to recognize general changes on the short-run. 73
In addition to that, the suggested analysis of door openings might offer the possibility
to optimize the usage of cooling devices. Although this was not part of the
requirements analysis, a relief of frequently opened devices could lead to a better
cooling behavior and less alarms. Also the suggested graphical distribution cannot
improve factors of the requirement analysis. But it could indicate the cooling device’s
accuracy and behavior at a glance. This additional knowledge might support
decisions in case of uncertainty of the cooling device’s general condition.
Section 5.10.2 presented a promising way to discover a trend by the use of
regression. Such a trend would notify a change in general behavior on the long-run.
Hence, a combination of basic statistics and regression could lead to a limited ability
to predict upcoming failures. In fact, a definite prediction is not possible due to the
very low probability and the lack of information. 74 But a detected change may hint a
person in charge to have a closer look at that corresponding cooling device.
These estimated improvements can even be extended by using not only statistical
analysis, but also data mining. The suggested classification from section 5.10.3
establishes additional system states besides “OK” and “Malfunctioning”. These states
could allow a more accurate description of the current system state because an
alarm is rated. Based on these ratings, a person in charge could react to a
temperature exceeding in a better way. Moreover, external influences are partly
recognized because the classification of alarms also depends on the occurrence of
door openings in advance of a temperature exceeding.
Hence, a combination of statistical analysis and data mining is promising to
significantly improve the current monitoring situation. The estimated improvements
are summarized again in Table 5-1. Blue dashed arrows represent estimated
improvements by the use of statistical analysis and magenta dashed arrows
represent estimated improvements by the use of data mining.
73 See section 6.3 for details
74 See sections 2.4.1, 5.4.2 and 5.9.3 for details
84