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A Method for Implementation of Machine Learning Solutions for Predictive Maintenance in Small and Medium Sized Enterprises

: Welte, Rebecca; Estler, Manfred; Lucke, Dominik

Fulltext ()

Procedia CIRP 93 (2020), pp.909-914
ISSN: 2212-8271
Conference on Manufacturing Systems (CMS) <53, 2020, Online>
Journal Article, Conference Paper, Electronic Publication
Fraunhofer IPA ()
Instandhaltung; maschinelles Lernen; Vorhersage

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 significant 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.