Apparel sizing using trimmed PAM and OWA operators

This paper is concerned with apparel sizing system design. One of the most important issues in the apparel development process is to define a sizing system that provides a good fit to the majority of the population. A sizing system classifies a specific population into homogeneous subgroups based on some key body dimensions. Standard sizing systems range linearly from very small to very large. However, anthropometric measures do not grow linearly with size, so they can not accommodate all body types. It is important to determine each class in the sizing system based on a real prototype that is as representative as possible of each class. In this paper we propose a methodology to develop an efficient apparel sizing system based on clustering techniques jointly with OWA operators. Our approach is a natural extension and improvement of the methodology proposed by McCulloch, Paal, and Ashdown (1998), and we apply it to the anthropometric database obtained from a anthropometric survey of the Spanish female population, performed during 2006.

► Definition and main characteristics of a sizing system.
► A new methodology to develop more efficient apparel sizing systems.
► Trimmed k-medoids algorithm.
► Dissimilarity measurement and ordered weighted averages.
► Build a sizing system from a anthropometric survey of the Spanish female population.