A Survey on Predictive Maintenance for Industry 4.0

TL;DR

This survey reviews the latest advancements in predictive maintenance within Industry 4.0, emphasizing its importance for reducing production downtime and financial losses in modern smart manufacturing environments.

Contribution

It provides a comprehensive classification and analysis of current predictive maintenance techniques and recent developments in Industry 4.0 and Industrial IoT contexts.

Findings

Predictive maintenance significantly reduces downtime and costs.

Recent developments leverage IoT and AI for improved maintenance accuracy.

Structured classification aids in understanding current research directions.

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.