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Data-driven product generation and retrofit planning

: Meyer, M.; Frank, M.; Massmann, M.; Wendt, N.; Dumitrescu, R.

Volltext ()

Procedia CIRP 93 (2020), S.965-970
ISSN: 2212-8271
Conference on Manufacturing Systems (CMS) <53, 2020, Online>
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer IEM ()

Industry 4.0 and digitalization have transformed the industry. Many manufacturers create additional customer value by offering data-based services. However, companies can benefit from analyzing data themselves. Learning from product usage and behavior data enables them to systematically improve their products in future generations and retrofits. But using data in product planning is not trivial. Henceforth, we propose a methodology for data-driven product generation and retrofit planning. It includes all steps from data-based identification of optimization potentials to the implementation of improvements in future product generations and retrofits. The application of the methodology is demonstrated in a case study.