Comfortable automotive seat design and big data analytics: A study in thigh support

Abstract

This study demonstrates how big data analytics can improve automotive seat design practices pertaining to thigh support and cushion length, a consistent customer complaint across the automotive seating industry. The method featured an analysis of survey feedback (complaint and self-reported anthropometry) obtained from 92,258 buyers of new vehicles in the North American market. Driver seat three dimensional scans from 139 vehicles (representing 12 manufacturers) provided metrics related to cushion length allowing for determination of the percentage of an average occupant's thigh supported by an automotive seat cushion in relation to customer complaints. The range determined to provide thigh support leading to minimal complaints for overall cushion length is 83.46%–88.49% and for cushion length to trim prominence is 73.63%–80.60%. A specific vehicle program was used to confirm the targets established using big data analytics were effective in minimizing customer issues related to thigh support and cushion length.