Voraussetzungen für den Einsatz datengetriebener Methoden in der Produktentwicklung

DS 111: Proceedings of the 32nd Symposium Design for X (DFX2021)

Year: 2021
Editor: Dieter Krause, Kristin Paetzold, Sandro Wartzack
Author: Jan Mehlstäubl, Simon Nicklas, Benjamin Gerschütz, Nicolai Sprogies, Benjamin Schleich, Thomas Lohner, Sandro Wartzack, Karsten Stahl, Kristin Paetzold
Series: DfX
Institution: Institut für Technische Produktentwicklung, Universität der Bundeswehr München
Section: Digital Engineering
Page(s): 10
DOI number: 10.35199/dfx2021.13


Data mining and machine learning are successfully applied in many business areas such as marketing or production. Due to the increasing complexity in data and information flows and the large amount of data, data-driven solutions have also great potential in product development. Nevertheless, many companies are not able to integrate data-driven methods into their product development process. In order to support the application of data-driven methods, this paper identifies necessary prerequisites for their integration in product development. Based on a data analysis process, the prerequisites are elaborated and, subsequently, levers for their design are derived.

Keywords: Data-driven Methods, Product Development, Data Mining, Machine Learning


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