Study of Sensitivity Knowledge for Quantitative Evaluations to the car Exterior Design

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• 作者：Takumi Kato ; Kazuhiko Tsuda ; ^{takumi11040@gmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Design engineering ; Natural language processing ; Deep Learning
• 刊名：Procedia Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：96
• 期：Complete
• 页码：1106-1111
• 全文大小：243 K

文摘

In recent years, the manufacturing industry has seen a shift of the domain of competition from “performance” which can easily be expressed numerically to “design” which is hard to be represented with numerical values. The rise of companies that focus on design, such as Apple, Samsung and IKEA, is remarkable. However, design presents two challenges for the manufacturing industry. Firstly, it is difficult to conduct a questionnaire survey on a design to external customers due to confidentiality. Secondary, subjectivity is involved as evaluators tend to use their experiences and feelings, which makes it quantitative evaluation almost impossible. Therefore, this study takes up automobile exterior design as a subject and aims to realize customer-oriented evaluation process by linking customers’ sensibilities to feature values of automobile exterior designs to enable simulating new designs.