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Manufacturing companies nowadays face growing numbers of heterogeneous customer requirements. Due to that, internal and external complexity lead to an increase in the associated costs. Especially companies with a high Engineer-to-Order business are strongly affected. To reduce external and internal complexity, Starting Solutions are a suitable way to do that. Starting Solutions require on the one hand the evaluation of product flexibility, on the other hand the evaluation of customer requirements. These two requirements are compared to each other and Starting Solutions are thereby derived.

Complex products and shorter development cycles lead to an increasing number of engineering changes. In order to be able to process these changes more effectively and efficiently, this paper develops a description model as a first step towards a data driven approach of processing engineering change requests. The description model is systematically derived from literature using text mining and natural language processing techniques. An example of the application is given by an automated classification based on similarity calculations between new and historic engineering change requests.

Kurzfassung Unternehmen stehen heute vor der Herausforderung Komplexität zu reduzieren. Externe Komplexität wird insbesondere vom Kunden der Unternehmen wahrgenommen und ist auf die kundenseitige Variantenvielfalt bei der Produktauswahl zurückzuführen. Als Reaktion auf die gesteigerte Komplexität können sogenannte Produktkonfiguratoren eingesetzt werden. Innerhalb von Produktkonfiguratoren sind Starting Solutions implementierbar, welche die Komplexität bei der Produktauswahl weiter reduzieren können.