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During the last 10 to 15 years, a renaissance of industrial engineering can be observed in manufacturing industry, as well as in scientific research. As a consequence, time and motion studies (TMS) become more important again. During the downturn of methodical approaches in industrial engineering in the 1980s, TMS-related competencies were lost in industry. Many companies are still missing the know-how for establishing a proper time data management (TDM). This paper presents a morphology of time data management (MoTDM), which was developed in order to create a comprehensive view on the processes of TDM as well as to detect relevant areas of improvement. The MoTDM can be used to optimise TDM processes within a company and also acts as scientific fundament for research in the field of industrial engineering

Kurzfassung Produzierende Unternehmen setzen zunehmend digitale Planungswerkzeuge in der Produktentstehung ein, um die Produkt-sowie Prozesskomplexität zu beherrschen und auf stetig wachsenden Kosten- und Zeitdruck zu reagieren. In diesem Beitrag sollen ausgehend von dem aktuellen Handlungsbedarf zukünftige Entwicklungspotenziale der digitalen Planungsunterstützung vor dem Hintergrund des Product Lifecycle Management aufgezeigt werden. Hierzu werden Ansätze zur intelligenten Nutzung von implizitem Planungswissen der Digitalen Fabrik am Beispiel von Zeitdaten skizziert.

The application and functional scope of digital assembly planning tools have been permanently increasing in order to deal with product and process complexity. Consequently a large amount of assembly-related data is stored in different systems alongside the product emergence process. By means of data mining techniques an intelligent utilization of this data can be accomplished for future assembly planning. This paper presents an approach for data mining-supported generation of assembly process plans to enhance planning efficiency. The approach is based on the classification and clustering of both product and process data as well as on the identification of their correlations.