Combining PCA-AHP Combination Weighting to Prioritize Design Elements of Intelligent Wearable Masks

Abstract

Intelligent wearable masks are gaining increasing interest due to COVID-19 and the problems and limitations of existing masks. This paper prioritizes the design elements of personal protective equipment-intelligent wearable masks from the perspective of the product design domain. Using principal component analysis (PCA), the principal components of the design elements were selected first in this paper. Using the combined weights (PCA-AHP) method, the intelligent wearable masks’ prioritized design elements at each level were determined. The highest priority among the primary elements is comfort (0.3422), with the adjustable ear strap (0.1870) receiving the highest priority among the primary elements of comfort. The highest priority in functionality (0.2733) is anti-respiratory droplets/air purification (0.1097), the highest priority in usability (0.1686) is the easy removal and replacement of filters (0.0761), the highest priority in the aesthetic design (0.1192) is styling (0.0509), and the highest priority in material (0.0967) is flexible fabric material (0.0355). Finally, the six prioritized design elements were evaluated using fuzzy comprehensive evaluation (FCE), and overall, 76% of the experts considered them “appropriate” or “very appropriate” and 18% considered them “fair.” Therefore, this study’s six most prioritized design elements proposed for intelligent wearable masks can satisfy users’ needs.

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