Liebherr-werk Nenzing Gmbh

Michael Kocher

Martin Rajek

Zornica Vaskova Vasileva

Christian Borgelt

A method for evaluation of faulty behavior of at least one event-data-generating machine including a data logging device for providing event data, comprising: transferring logged event data, the logged event data representing a sequence of events, from the event-data-generating machines to a central processor, mining multi-dimensional sequential patterns and/or mining multi-dimensional sequential rules and/or mining anomalies and/or exceptions within the transferred event data wherein the event data additionally comprises at least one dimensional attribute holding information indicating the event-data-generating machine or at least one event-data-generating machine property; the difference between timestamps of first and last events included in an identified sequential pattern and/or sequential rule and/or anomaly and/or exception may not exceed a predefined time window; and storing at least one reference sequential pattern, sequential rule and/or anomaly and/or exception as an output of the mined multi-dimensional sequential patterns and/or sequential rules, and/or anomalies and/or exceptions in a central database.

Method and system for evaluation of a faulty behaviour of at least one event data generating machine and/or monitoring the regular operation of at least one event data generating machine

The present disclosure is related to a method for monitoring at least one event data generating machine, including a data logging device for providing event data. The method comprises transferring logged event data from at least one of the event data generating machines to a central processor, mining a multi-dimensional sequential pattern within said transferred event data wherein at least one dimensional attribute holds information indicating said event data generating machine or the at least one event data generating machine property, and matching said mined multi-dimensional sequential pattern with patterns stored in a central pattern database.

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Sulz, Austria

Michael Kocher