Intelligent Manufacturing Systems in COVID-19 Pandemic and Beyond:Framework and Impact Assessment

Abstract

Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks. The intelligent manufacturing (IM) systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms. The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network, which mitigates the severity of industrial chain disruption. In this study, we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks. Considering the constraints of the IM resources, we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.

Publication DOI: https://doi.org/10.1186/s10033-020-00476-w
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Funding Information: This work was supported by the International Postdoctoral Exchange Fellowship Program (20180025).
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Funding Information: This work was supported by the International Postdoctoral Exchange Fellowship Program (20180025).
Uncontrolled Keywords: COVID-19 pandemic,Industrial network,Intelligent manufacturing system,Optimization,Supply chain disruption,Mechanical Engineering,Industrial and Manufacturing Engineering
Publication ISSN: 2192-8258
Last Modified: 16 Feb 2024 08:13
Date Deposited: 08 Mar 2022 13:06
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-12-01
Published Online Date: 2020-08-28
Authors: Li, Xingyu
Wang, Baicun
Liu, Chao (ORCID Profile 0000-0001-7261-3832)
Freiheit, Theodor
Epureanu, Bogdan I.

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