Volltext-Downloads (blau) und Frontdoor-Views (grau)

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.

Download full text files

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author of HS ReutlingenWelte, Rebecca; Estler, Manfred; Lucke, Dominik
URN:urn:nbn:de:bsz:rt2-opus4-28125
DOI:https://doi.org/10.1016/j.procir.2020.04.052
ISSN:2212-8271
Erschienen in:Procedia CIRP
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Journal article
Language:English
Publication year:2020
Tag:implementation method; machine learning; predictive maintenance
Volume:93
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