Abstract
Extrusion of rubber profiles, e.g., for the automotive industry, is a highly complex continuous production process which is nevertheless influenced strongly by variability in input materials and other external conditions. As analytical models exist only for small parts of such processes, experience continues to play an important role here, very similar to the situation in the early phases of process engineering studied in CRC IMPROVE. This section therefore describes a transfer research project called MErKoFer conducted jointly with an industrial application partner and a software house founded by former CRC members.
In MErKoFer, results from the CRC projects on direct process support (B1, see Sect. 3.1), process data warehousing (C1, Sect. 4.1), and plastics engineering (A3, see Sect. 5.4) were applied and extended. Specifically, knowledge about extrusion processes is captured by ontology-based traceability mechanisms for both direct process support of extrusion operators, and for process analysis and improvement based on an integration of data mining techniques. The accumulated knowledge assists in ensuring defined quality standards and in handling production faults efficiently and effectively. The approach was experimentally implemented and evaluated in the industrial partner’s site, and some generalizable parts of the environment were taken up by the software house partner in their aiXPerience software environment for process automation and process information systems.
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© 2008 Springer-Verlag Berlin Heidelberg
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Brandt, S.C., Jarke, M., Miatidis, M., Raddatz, M., Schlüter, M. (2008). Management and Reuse of Experience Knowledge in Extrusion Processes. In: Nagl, M., Marquardt, W. (eds) Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support. Lecture Notes in Computer Science, vol 4970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70552-9_32
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DOI: https://doi.org/10.1007/978-3-540-70552-9_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70551-2
Online ISBN: 978-3-540-70552-9
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