29.09.2014 Views

Casestudie Breakdown prediction Contell PILOT - Transumo

Casestudie Breakdown prediction Contell PILOT - Transumo

Casestudie Breakdown prediction Contell PILOT - Transumo

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

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 />

55

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!