A Predictive Maintenance Model for Flexible Manufacturing in the Context of Industry 4.0

The Industry 4.0 paradigm is the focus of modern manufacturing system design. The integration of cutting-edge technologies such as the Internet of things, cyber–physical systems, big data analytics, and cloud computing requires a flexible platform supporting the effective optimization of manufacturi...

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Bibliographic Details
Main Authors: Go Muan Sang, Lai Xu, Paul de Vrieze
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Big Data
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2021.663466/full
Description
Summary:The Industry 4.0 paradigm is the focus of modern manufacturing system design. The integration of cutting-edge technologies such as the Internet of things, cyber–physical systems, big data analytics, and cloud computing requires a flexible platform supporting the effective optimization of manufacturing-related processes, e.g., predictive maintenance. Existing predictive maintenance studies generally focus on either a predictive model without considering the maintenance decisions or maintenance optimizations based on the degradation models of the known system. To address this, we propose PMMI 4.0, a Predictive Maintenance Model for Industry 4.0, which utilizes a newly proposed solution PMS4MMC for supporting an optimized maintenance schedule plan for multiple machine components driven by a data-driven LSTM model for RUL (remaining useful life) estimation. The effectiveness of the proposed solution is demonstrated using a real-world industrial case with related data. The results showed the validity and applicability of this work.
ISSN:2624-909X