A Decision Model for Concept Design Evaluation for Mechanical Ventilator Machines Used During the COVID-19 Pandemic
doi: 10.14456/mijet.2023.12
Keywords:
human’s lung, COVID-19 virus, ventilator machine, WHO, concept design, intuitionistic fuzzy setAbstract
Ventilator machine which has been approved for the treatment of the acute respiratory distress syndrome associated with the novel COVID-19 disease, is used for getting in oxygen and carbon dioxide out of human lungs. With the urgent need for the machines in our hospitals, their designs are been localized. To select the best design, considering the many factors associated with its development, a comprehensive study of the concept designs evaluations process has been presented. In this paper, an extended intuitionistic fuzzy multi-criteria decision-making (EIFMCDM) model which is based on the integration of the Complex Intuitionistic Fuzzy Bonferroni Mean (CIFBM) operator and the Intuitionistic Fuzzy (IF) Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method has been proposed for concepts design evaluation of some new mechanical ventilator machine prototypes. The EIFMCDM model, which allows for multi-dimensional fuzzy information typically associated with real problems like concept design selection to be captured in the evaluation process, addresses a significant challenge in the concept design evaluation literature. Results from the concept design evaluation shows that the concept design described with the code VD2, VD4 and with the ranking values 0.525 and 0.439 respectively has the best and least designs, and the chances to be manufactured and used for COVID-19 treatment. This study has presented a new model for concept design evaluation, and attempt has been made to validate the feasibility of the model performance, the study conclude therefore that the model is feasible.
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