Casestudie Breakdown prediction Contell PILOT - Transumo
Casestudie Breakdown prediction Contell PILOT - Transumo
Casestudie Breakdown prediction Contell PILOT - Transumo
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5 Possible and Promising Ways of Data Analysis<br />
The first four chapters already introduced the existing methodological problems of<br />
sensor based temperature monitoring systems and the current state of research. The<br />
second chapter pointed out the existing problems of the temperature monitoring task<br />
and limitations of the current approach of just setting critical temperature limits. The<br />
biggest problem was the existing lack of information. 41 This disabled an analyst to<br />
identify real causes of temperature deviations. Moreover, a very low probability of<br />
real malfunctions leads to many false alarms. 42<br />
The introduction of currently available temperature monitoring products in the third<br />
chapter pointed out that no solution seems to be available that bases on an other<br />
approach. Only some workarounds like time dependent limit settings are offered to<br />
solve the existing problems partially. 43 In fact, no introduced product did fully comply<br />
with the requirements from section 2.5.<br />
In addition to that, the fourth chapter pointed out that there seems to be no research<br />
activity within this particular setting of sensor based temperature monitoring of<br />
cooling devices within medical laboratories. That is the reason why this chapter tries<br />
to find ways to gain additional information of monitored devices by the use of<br />
statistical analysis and data mining. Due to missing specialized methods, the current<br />
research begins with an analysis of basic statistical and data mining methods. Aside<br />
from that, other specialized methods from the fourth chapter are introduced and<br />
tested on applicability.<br />
5.1 The Six Possible Levels of Data Analysis<br />
To be able to categorize different approaches of data analysis, it is important to<br />
review its possible kinds. Data analysis can be divided into six different levels of<br />
detail. Depending on the demands of the underlying setting, data analysis ranges<br />
from highly abstract to very detailed. According to the chosen level, one of the<br />
following kinds of results is aimed: ([Berthold99], p. 171)<br />
41 See section 2.4.1 for details<br />
42 See section 2.2.5 for details<br />
43 See section 3.3.2 for details<br />
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