Casestudie Breakdown prediction Contell PILOT - Transumo

Aside from determination of changes on the short-run, section 5.10.1 suggested to
offer visualization possibilities for occurred door openings. Furthermore, a graphical
temperature distribution was suggested to obtain the accuracy of a cooling device.
Figure 6-11 pictures these additional ideas. The overview of door openings allows an
easy comparison of usage to other devices. Moreover, the pictured distribution allows
a very fast overview of the devices accuracy on the long-run: the sharper the peak,
the higher the accuracy. Remarkable at this example is the second peak, which
indicates the significant change in behavior.
Figure 6-11: Daily Door Openings and Temperature Distribution of the Selected Dataset
This section proved that already the simple appliance of basic statistical measures
can discover changes in general behavior. Up to the calculation of these results, the
corresponding cooling device was classified as well running. No one recognized
these changes.
6.2.2 Detection of Changes in Behavior by the Use of Regression
Section 5.10.2 introduced the promising idea to detect changes in general behavior
on the long-run by the use of regression. An appliance of linear regression to the
selected dataset leads to the regression function from Formula 6-1. Remarkable is
the high coefficient of determination, which indicates a very good approximation. 83
Figure 6-12 offers a graphical representation.
yˆ
= 0.0019307x
−1409.6
R
2 =
0.97492
Formula 6-1: Regression Function and Coefficient of Determination
83 See 5.4.2 section for details
98