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HANNOVER MESSE 2018, 23 - 27 April
Homepage>Exhibitors & Products >Prozess Mining for Industry

Prozess Mining for Industry

Software Competence Center

Exhibitor details
Logo Prozess Mining for Industry

Exhibition stand

Hall 2, Stand A44

Contact(s)
Mr. Mag. Manfred Schwanthaler
Business Development
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Product description

Processes are the heart of an enterprise and describe the interconnections of tasks in day-to-day operations. Modeling, analysis and improvement of these processes has been a research interest for many decades and for some years a focus of research and industrial projects at Software Competence Center Hagenberg.
The classical approach in identifying processes consists of conducting interviews, observing operations and taking samples. Results require a huge amount of effort and often reflect more the target processes rather than the actual processes (for lack of exact data on execution frequency/times).
The basic idea behind process mining is to detect, monitor and improve real processes by extracting knowledge from event logs. Events relate to numerous processes in enterprises. Depending on the application domain to be analyzed, events can pertain to conducting a financial transaction, receiving an electronic product inquiry, joining metal components in a processing step, or invoking a method in a software component.The data that serve as the basis for process analysis are generally already available in the enterprise, e.g., as event log data directly from machines or processed in databases. These data are analyzed and linked. This valuable knowledge about current processes in an enterprise can serve as the basis for implementation of a software system, for improvement of the processes, or for monitoring adherence to the processes. Process analysis offers methods and tools that enable extraction of processes. SCCH possesses the required know-how due to years of experience in data mining/analysis as well as fundamental expertise regarding processes. In multiple industrial projects, SCCH has analyzed and optimized both structured and unstructured production processes.

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