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Assessing the Robustness of a Factory Amid the COVID-19 Pandemic: A Fuzzy Collaborative Intelligence Approach
| Content Provider | MDPI |
|---|---|
| Author | Chen, Toly Wang, Yu-Cheng Chiu, Min-Chi |
| Copyright Year | 2020 |
| Description | 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. |
| Starting Page | 481 |
| e-ISSN | 22279032 |
| DOI | 10.3390/healthcare8040481 |
| Journal | Healthcare |
| Issue Number | 4 |
| Volume Number | 8 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-11-12 |
| Access Restriction | Open |
| Subject Keyword | Healthcare Cybernetical Science Covid-19 Pandemic Robustness Fuzzy Collaborative Intelligence Wafer Fabrication |
| Content Type | Text |
| Resource Type | Article |
