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2020
Journal Article
Title

Data-driven product generation and retrofit planning

Abstract
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.
Author(s)
Meyer, M.
Frank, M.
Massmann, M.
Wendt, N.
Dumitrescu, R.
Journal
Procedia CIRP  
Conference
Conference on Manufacturing Systems (CMS) 2020  
Open Access
DOI
10.1016/j.procir.2020.04.122
Additional link
Full text
Language
English
Fraunhofer-Institut für Entwurfstechnik Mechatronik IEM  
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