A scalable mass customisation design process for 3D-printed respirator mask to combat COVID-19

Purpose A three-dimensional (3D) printed custom-fit respirator mask has been proposed as a promising solution to alleviate mask-related injuries and supply shortages during COVID-19. However, creating computer-aided design (CAD) model for each is currently manual process thereby not scalable pandemic crisis. This paper aims develop novel reduce overall cost time, thus enabling the mass customisation of 3D masks. Design/methodology/approach Four data acquisition methods were used collect facial from five volunteers. Geometric accuracy, equipment time method evaluated identify most suitable Subsequently, three-step was developed scripted generate CAD models volunteer. Computational geometric accuracy masks via one-sided Hausdorff distance. Findings Respirator successfully generated all meshes, taking <2 min/mask meshes 50,000?100,000 vertices <4 min ?500,000 vertices. The average ranged 0.3 mm 1.35 mm, depending on method. mesh obtained different 0.56 mm. smartphone with depth sensor found be appropriate Originality/value presented, which can automatically in few minutes raw mesh. methods, including use statistical shape model, sensor, light stage structured scanner compared; one recommended crisis considering cost, accuracy.