Casestudie Breakdown prediction Contell PILOT - Transumo

1 Introduction
1.1 Initial Position and Problem
As more and more technical devices do “mission critical” tasks within industry and
medical research, monitoring of such devices is becoming increasingly important.
Possible malfunctions could damage these expensive products or its contents, which
can lead to very high costs (both direct and indirect costs; so called collateral
damage). That is why electronic sensor based monitoring systems have become
popular during the last years.
One of these systems is XiltriX, a hard- and software combination from the company
Contell/IKS, which is currently applied to laboratory equipment. The basic
functionality is to monitor and to record temperature of fridges and/or CO 2
concentration within incubators to prevent damage of goods, stored in these devices.
Elementary functionalities as well as some useful tools are already implemented. The
customer or Contell/IKS defines critical minimum and maximum temperature limits
and as soon as a value is exceeded, the system warns by means of E-Mail or SMS.
The main question is now in which direction the development of the software should
continue. The idea of this study is to extend the existing “reactive” XiltriX to a more
“pro-active” system that recognizes trends and notifies a person in charge before
minimum and maximum critical temperature limits are exceeded. In addition to that,
XiltriX should offer additional decision support to allow a person in charge to better
classify the system’s condition within situations of exceptional temperature levels.
After comparing XiltriX to other major monitoring products, this diploma thesis will
work out some promising ideas to show the possibilities for further development. The
main focus is the recorded monitoring data as currently obtained from the field by
XiltriX. At the moment this data is only accessible numerically or in form of a graph.
Analyzing the graphs manually in retrospect already helped to predict malfunctions,
but the results rely on experience and especially instinct of Contell/IKS staff. At
present it is not clear how reliable this intuitive data analysis really is. It is also
problematic that with this kind of data analysis even an experienced person needs a
lot of time, because graphs from every single sensor have to be looked at manually.
1.2 Goals of this Study and Approach
The main task of research is now to determine, whether and in which way it is
possible to reliably predict malfunctions and to give decision support to the customer.
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