English

A Survey on Predictive Maintenance for Industry 4.0

Machine Learning 2020-02-20 v1

Abstract

Production issues at Volkswagen in 2016 lead to dramatic losses in sales of up to 400 million Euros per week. This example shows the huge financial impact of a working production facility for companies. Especially in the data-driven domains of Industry 4.0 and Industrial IoT with intelligent, connected machines, a conventional, static maintenance schedule seems to be old-fashioned. In this paper, we present a survey on the current state of the art in predictive maintenance for Industry 4.0. Based on a structured literate survey, we present a classification of predictive maintenance in the context of Industry 4.0 and discuss recent developments in this area.

Cite

@article{arxiv.2002.08224,
  title  = {A Survey on Predictive Maintenance for Industry 4.0},
  author = {Christian Krupitzer and Tim Wagenhals and Marwin Züfle and Veronika Lesch and Dominik Schäfer and Amin Mozaffarin and Janick Edinger and Christian Becker and Samuel Kounev},
  journal= {arXiv preprint arXiv:2002.08224},
  year   = {2020}
}
R2 v1 2026-06-23T13:46:54.369Z