Casestudie Breakdown prediction Contell PILOT - Transumo

store this kind of data but only offer basic visualization possibilities and sometimes
basic statistical summarizations. Moreover, systems like that currently only allow data
analysis by hand.
This leads to a high amount of stored historical data with currently very few use. The
main idea is now to test statistical and data mining methods on applicability to
improve the current situation of rare information. Especially reliable answers on the
given criteria from the beginning of chapter 2 would offer great decision support, as
pictured in Figure 2-10.
Figure 2-10: Estimated Answers of Statistics and Data Mining
One hundred percent reliable answers to the questions on the right would allow a
perfect classification of cooling devices as OK or malfunctioning. But even if the
answers could only be given with a lower reliability, a possible knowledge gain could
at least support the decision of the current technical condition and put it on a larger
basis than just the current temperature.
Beside these four criteria, section 2.1 identified another two important requirements.
Since the stored samples are normally high valued and easy to destroy, a monitoring
approach has to be able to identify failures as soon as they are recognizable.
Because an early detection leads to additional time to save stored samples to other
fridges. Moreover, it must be possible to avoid an error of second kind in any case.
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