TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Welte, Rebecca
A1  - Estler, Manfred
A1  - Lucke, Dominik
T1  - A method for implementation of machine learning solutions for predictive maintenance in small and medium sized enterprises
JF  - Procedia CIRP
N2  - 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.
KW  - predictive maintenance
KW  - machine learning
KW  - implementation method
Y1  - 2020
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-28125
SN  - 2212-8271
SS  - 2212-8271
U6  - https://doi.org/10.1016/j.procir.2020.04.052
DO  - https://doi.org/10.1016/j.procir.2020.04.052
VL  - 93
SP  - 909
EP  - 914
S1  - 6
PB  - Elsevier
CY  - Amsterdam
ER  -