Abstract

Objectives. Addressing the prevalent issue of size misfits in large-scale issued firefighter uniforms due to diverse and complex body morphologies, this article presents an objective method for intelligent garment sizing matching without subjective weighting. Methods. The method employs criteria importance through inter-criteria correlation (CRITIC) and the catastrophe progression method (CPM) for more accurate and reliable sizing. Traditional methods, reliant on limited indicators such as height and chest girth and often subjectively determined by experts, are prone to reliability concerns. Matching decisions made based on our approach are evidence-based, transparent and reproducible, thus minimizing subjectivity and expert intervention. Results. A case study of 388 cases validates the method's efficacy in providing garment size recommendations, surpassing traditional experience-based approaches by reducing subjective bias. Conclusion. Despite some differences, the optimal alternatives for examinees are almost consistent across the different methods. Compared with traditional subjective weighting methods, this method has potential advantages in situations such as large-scale matching of firefighter protective clothing where individual customization or direct try-on is not feasible.

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