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The application of digital manufacturing tools has been continuously increasing in order to deal with product and process complexity in shortened product lifecycles. The resulting comprehensive digital documentation of the product emergence process provides an opportunity to support concurrent engineering processes. By identifying correlations and recurrent patterns with the aid of data mining techniques, tacit planning knowledge can be revealed and reintegrated into new process planning workflows in order to enhance planning efficiency and facilitate decision making. Based on the classification and clustering of both product and process data and the determination of their respective linkages, this paper presents a novel approach for the knowledge-based support of product emergence processes.
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