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

Xu, L. and de Vrieze, P. T., 2021. A Predictive Maintenance Model for Flexible Manufacturing in the Context of Industry 4.0. Frontiers in Big Data, 4, 663466.

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Official URL: https://www.frontiersin.org/journals/big-data

DOI: 10.3389/fdata.2021.663466

Abstract

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.

Item Type:Article
Uncontrolled Keywords:Industry 4.0; predictive maintenance; big data analytics; maintenance schedule plan; flexible manufacturing
Group:Faculty of Science & Technology
ID Code:35933
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:27 Aug 2021 10:14
Last Modified:27 Aug 2021 10:14

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