Page 128 - IJB-7-4

Mass Customization of Respiratory Protective Equipment
Users must pass a fit test to ensure an effect seal users . Despite having a more updated dataset, several
[20]
is achieved before they are deployed in high-risk large-scale comparative anthropometric studies have
environment. Despite its importance, there is clear reported statistically significant differences (P < 0.05) in
evidence that current commercially available disposable key face dimensions (e.g. face width, length, and nose
RPE or reusable elastomeric RPE are inadequate at protrusion) between males and females, different ethnic
[4]
[5]
creating an effective seal for all demographic user groups. groups (Asian, White, African, Hispanic, etc.), and age
There are numerous reports of demographic bias in RPE groups (18 – 29 years old and above 45 years old) [21-24] in
fit test failure rates. It has been found that female users the updated panel. Respirator manufacturers may create
were nearly twice as likely to fail a fit test compared to different product sizes based on demographic-specific
male users [6-10] . Fit test failure rates were also found to anthropometric sizing to accommodate such differences.
be skewed across different ethnic groups. Asian users However, each additional size will incur additional
have failure rate as high as 54% and African users at tooling costs for mass production, therefore making it
[11]
86% [12] as compared to about 5 – 10% among Caucasian economically undesirable. The anthropometric sizing-
users [7,8,13] . Other than gender and ethnicity, age has based design methodology was developed decades ago to
also been reported as another factor that affects fit test enable affordable mass customization (MC) of wearables
failure rate . More importantly, it was found that certain through conventional mass production methods, such
[14]
combination of subdemographic groups will lead to a as injection molding, and it had been shown to result
higher fit test failure rate. For example, McMahon et al. in design bias toward certain demographic groups and
[7]
reported statistical significant difference (P < 0.05) in higher failure rates in protective equipment as mentioned
fit test passing rates among age groups in women (19 above. With the maturation of advanced manufacturing
– 71 years old with an average 10 years increment for techniques such as additive manufacturing (AM) which
each age group), but not in men. Sandkovsky et al. also can create custom-fit product at near-zero tooling cost,
[15]
found that only females with body mass index (BMI) >25 it is time to re-think and develop new design methods to
are at higher risk of failing a fit test, but not males. facilitate the use of such new manufacturing methods to
These demographically biased fit test failure rates provide well fitted masks for people from all backgrounds,
are potentially caused by the limitations associated with regardless of their gender, ethnicity, age, or BMI.
design methodologies employed for mass producing AM has been identified as the next generation agile
wearables. The conventional design method is based on manufacturing system that enables the MC of custom-fit
anthropometric sizing, which are anthropometric surveys products [25-29] . A key strength of AM is its near-zero tooling
that collect body dimensions from a sample population cost associated with every new design, which greatly
and statistically analyze them to suggest a sizing system reduces the per part manufacturing cost as compared to
(e.g. three-size system that consists of small, medium, and mass production processes such as injection molding. AM
large) to cover majority of the population [16,17] . For RPE has been widely adopted to produce custom-fit products
masks, respirator fit test panels (two-Dimensional charts) including traditionally custom-made medical devices
are typically developed from analyzing 1-Dimensional such as maxillofacial prosthetics [30-32] , foot orthosis [33,34] ,
facial dimensions collected from thousands of subjects to removable partial denture , or mass-produced
[35]
provide an objective tool for selecting a few representative ergonomic products such as shoe insoles [36,37] , and aircrew
human test subjects based on their facial characteristics seats . In recent years, AM has been explored to produce
[25]
for use in research, product development, testing, and custom-fit specialty masks, such as Bi-level/Continuous
certification . The panel is built with the aim to cover Positive Airway Pressure (BiPAP/CPAP) masks [38-40] ,
[18]
about 95% facial variation of a population and can be where they have been shown to have less leakage and
segmented into a few broad categories to inform a sizing better comfort as compared to conventional generically
system to guide the design of RPE. One of the earliest and designed masks. For RPE, custom-fit face seals have been
most referenced respirator fit test panels was developed shown to distribute contact pressure more evenly across
based on bivariate distribution of face length and lip length the contact area, reducing the occurrence of high pressure
(for half-face piece RPE) or face length and face width (for imposed by commercial mass-produced RPE masks on
full-face piece RPE) data from an anthropometric survey areas such as the nose bridge, upper cheek, middle cheek
of 4000 male subjects in the US Air Force by Los Alamos and lower cheek and chin . There are also ongoing
[41]
National Laboratory in the early 1970s. Recently in investigations on whether three-dimensional (3D) printed
[19]
2007, the National Institute for Occupational Safety and tailored RPE can improve fit test passing rate and provide
Health (NIOSH) recognized the unsuitability of using better sustained comfort than conventional RPE [42,43] . AM
outdated military data for the design of civilian RPE, and can also serve as an agile supply chain solution during
developed a new fit test panel using data (3997 subjects) an emergent public health crisis [44-48] . During the earlier
from a 2001 anthropometric survey of civilian respirator days of the COVID-19 pandemic, various government

124 International Journal of Bioprinting (2021)–Volume 7, Issue 4