Objective multi-criteria decision-making for optimal firefighter protective clothing size selection

Area of Science:

• Industrial Engineering
• Apparel Design
• Ergonomics

Background:

• Firefighter uniforms often have size misfits due to complex body morphologies.
• Traditional sizing methods rely on limited, subjective indicators like height and chest girth.
• Existing methods lack reliability and transparency, leading to poor garment fit.

Purpose of the Study:

• To present an objective, intelligent garment sizing method for firefighter uniforms.
• To minimize subjectivity and expert intervention in the sizing process.
• To improve the accuracy and reliability of large-scale uniform size matching.

Main Methods:

• Utilized the Criteria Importance Through Inter-criteria Correlation (CRITIC) method.
• Employed the Catastrophe Progression Method (CPM) for enhanced sizing accuracy.
• Developed an evidence-based, transparent, and reproducible matching decision framework.

Main Results:

• A case study with 388 participants validated the method's effectiveness.
• The objective method demonstrated superior performance over traditional experience-based approaches.
• Subjective bias was significantly reduced in garment size recommendations.

Conclusions:

• The proposed method offers potential advantages for large-scale firefighter protective clothing matching.
• It is particularly beneficial where individual customization or direct try-on is impractical.
• Optimal sizing alternatives were found to be consistent across methods, despite minor differences.