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

Xingyu Li, Baicun Wang, Chao Liu, Theodor Freiheit, Bogdan I. Epureanu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

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.

Original languageEnglish
Article number58
Number of pages5
JournalChinese Journal of Mechanical Engineering (English Edition)
Volume33
Issue number1
DOIs
Publication statusPublished - 28 Aug 2020
Externally publishedYes

Keywords

  • COVID-19 pandemic
  • Industrial network
  • Intelligent manufacturing system
  • Optimization
  • Supply chain disruption

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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