Ford Motor Company Product Development Center, 20901 Oakwood, Dearborn, MI, 48124, United States.
Appl Ergon. 2019 Feb;75:257-262. doi: 10.1016/j.apergo.2018.08.020. Epub 2018 Nov 17.
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.
本研究展示了大数据分析如何改进汽车座椅设计实践，以提高大腿支撑和座垫长度，这是汽车座椅行业一直存在的客户抱怨。该方法对从北美市场购买新车的 92258 名买家的调查反馈（投诉和自我报告的人体测量学）进行了分析。从 139 辆汽车（代表 12 个制造商）中获取了驾驶员座椅三维扫描，提供了与座垫长度相关的指标，从而确定了汽车座垫支撑平均乘客大腿的百分比与客户投诉的关系。确定为整体座垫长度提供最小投诉的大腿支撑范围为 83.46%-88.49%，为座垫长度到饰边突出的范围为 73.63%-80.60%。具体的车辆计划用于确认使用大数据分析确定的目标在最小化与大腿支撑和座垫长度相关的客户问题方面是有效的。
