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A method for implementation of machine learning solutions for predictive maintenance in small and medium sized enterprises

  • In recent years, machine learning algorithms have made a huge development in performance and applicability in industry and especially maintenance. Their application enables predictive maintenance and thus offers efficiency increases. However, a successful implementation of such solutions still requires high effort in data preparation to obtain the right information, interdisciplinarity in teams as well as a good communication to employees. Here, small and medium sized enterprises (SME) often lack in experience, competence and capacity. This paper presents a systematic and practice-oriented method for an implementation of machine learning solutions for predictive maintenance in SME, which has already been validated.

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Author of HS ReutlingenWelte, Rebecca; Estler, Manfred; Lucke, Dominik
Erschienen in:Procedia CIRP
Place of publication:Amsterdam
Document Type:Journal article
Publication year:2020
Tag:implementation method; machine learning; predictive maintenance
Page Number:6
First Page:909
Last Page:914
DDC classes:670 Industrielle und handwerkliche Fertigung
Open access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International