Assessing the Robustness of a Factory Amid the COVID-19 Pandemic: A Fuzzy Collaborative Intelligence Approach

Tin-Chih Chen, Yu Cheng Wang*, Min Chi Chiu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The COVID-19 pandemic has affected the operations of factories worldwide. However, the impact of the COVID-19 pandemic on different factories is not the same. In other words, the robustness of factories to the COVID-19 pandemic varies. To explore this topic, this study proposes a fuzzy collaborative intelligence approach to assess the robustness of a factory to the COVID-19 pandemic. In the proposed methodology, first, a number of experts apply a fuzzy collaborative intelligence approach to jointly evaluate the relative priorities of factors that affect the robustness of a factory to the COVID-19 pandemic. Subsequently, based on the evaluated relative priorities, a fuzzy weighted average method is applied to assess the robustness of a factory to the COVID-19 pandemic. The assessment result can be compared with that of another factory using a fuzzy technique for order preference by similarity to ideal solution. The proposed methodology has been applied to assess the robustness of a wafer fabrication factory in Taiwan to the COVID-19 pandemic.

Original languageEnglish
Article number481
Number of pages26
JournalHealthcare
Volume8
Issue number4
DOIs
StatePublished - Dec 2020

Keywords

  • COVID-19 pandemic
  • robustness
  • fuzzy collaborative intelligence
  • wafer fabrication
  • AHP-TOPSIS
  • COMPETITIVENESS
  • PERFORMANCE
  • CONSENSUS
  • LOCATION
  • PRODUCT
  • TIME

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