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Prioritizing the barriers of manufacturing during COVID-19 using fuzzy AHP
Advances in Soft Computing Applications ; : 205-216, 2023.
Article in English | Scopus | ID: covidwho-20232704
ABSTRACT
COVID-19 has wreaked havoc on the global economy, supply chains, and government, posing an unparalleled health threat. The manufacturing sector was one of the most disruptive systems in the world at the time of the COVID-19 pandemic. Most manufacturing companies have faced a lock-down situation and are focusing on the production of essential products. Furthermore, COVID-19 has altered customer behavior. The short-term and long-term effects of COVID-19 on the manufacturing sector must be evaluated to hasten recovery and build preparedness measures should another such disruption occur. The limitations affecting the construction system during this period were discussed and prioritized in this study. The ambiguous nature of human thinking makes it difficult to evaluate the qualitative parameters;hence, it is preferred to incorporate an approach that converts the variables into triangular fuzzy numbers to better represent the values of the criteria. A fuzzy analytical hierarchical procedure (FAHP) is applied to evaluate the limitation criteria in an ambiguous environment. "Growing demand for existing products" is considered the heaviest limit after "financial stagnation" and "setback in logistics services." The study results will help the manufacturing company in formulating and implementing strategies to overcome the pandemic situation. © 2023 River Publishers. All rights reserved.
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Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Qualitative research Topics: Long Covid Language: English Journal: Advances in Soft Computing Applications Year: 2023 Document Type: Article

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Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Qualitative research Topics: Long Covid Language: English Journal: Advances in Soft Computing Applications Year: 2023 Document Type: Article