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Zusammenfassung:

Many producers of industrial goods and users of industrial plants will try and reduce their operating
costs by the use of smart sensors. This includes - but is not limited to - the producers of
locomotives, trucks, high speed milling machines, ships etc.

Technically that means that the industrial goods and plants will be equipped with smart sensors at
the most informative locations and continuously monitored. In case deterioration or unexpected
failures are detected, it is possible to intervene immediately. That will lead to better industrial
products with higher availability and less operating costs. For the producers of sensor equipped
products this will in the long term result into higher market shares.

In order to exploit these opportunities, the producers and operators will have to store general
product and real-time data in one backend system and run a variety of analyses. These analyses will
support different processes belonging to different phases of the product lifecycle. Prominent
examples are the identification of design errors, breakdown forecast, residual lifetime analysis or
optimal decommissioning of products. Each of these objectives needs different data and different
methods of decision support. However, the evaluation of the sensor data is the most important step
for optimizing the processes and increasing profitability. These methods might sometimes be quite
simple; in other cases they might be highly complex and need advanced statistical algorithms. It is
often the case that a better algorithm leads to substantial benefits without increasing the cost side.

PARASUITE is a software framework which offers a set of functions which are important for a
variety of engineers, maintenance personnel and technicians.