Product innovation concept generation based on deep learning and Kansei engineering

doi:10.1080/09544828.2021.1928023

CORC > 兰州理工大学 > 兰州理工大学 > 设计艺术学院

	Product innovation concept generation based on deep learning and Kansei engineering
	Li, Xiong 1,2; Su, Jianning 3; Zhang, Zhipeng 3; Bai, Ruisheng 2
刊名	JOURNAL OF ENGINEERING DESIGN
	2021-10-03
卷号	32 期号:10 页码:559-589
关键词	deep learning PCGA-DLKE Kansei engineering PD-GAN product concept generation
ISSN号	0954-4828
DOI	10.1080/09544828.2021.1928023
英文摘要	Industrial designers often present their initial concepts as design sketches. Rapid creation of new product conceptual images that meet users' affective preferences remains challenging in real design environments. However, few published works in affective design directly assist industrial designers in creating product conceptual images. Thus, we propose a product concept generation approach framework based on deep learning and Kansei engineering (PCGA-DLKE) to assist industrial designers. Our work focuses on dataset collection, pre-processing, affective preferences recognition, conceptual image generation model and product style transfer networks. To mark users' affective preferences, we established an affective recognition model by Kansei engineering and deep convolutional neural networks. To address the product conceptual image generation problem, we proposed a product design GAN model (PD-GAN), generating product conceptual images with affective preferences. An improved fast neural style transfer network was successfully trained to meet users' style preferences. This study aims to assist industrial designers in finding innovative concepts with affective preference. The Kansei evaluation shows that the innovation of the new product concept has been enhanced, indicating that the approach can better assist industrial designers in creating designs that meet users' emotional needs. Hand drill design and bicycle helmet design are taken as a case study.
WOS研究方向	Engineering
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000657539500001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/148877]
专题	设计艺术学院
作者单位	1.Lanzhou City Univ, Sch Bailie Mech Engn, Lanzhou, Peoples R China; 2.Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou, Peoples R China; 3.Lanzhou Univ Technol, Sch Design Art, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Li, Xiong,Su, Jianning,Zhang, Zhipeng,et al. Product innovation concept generation based on deep learning and Kansei engineering[J]. JOURNAL OF ENGINEERING DESIGN,2021,32(10):559-589.
APA	Li, Xiong,Su, Jianning,Zhang, Zhipeng,&Bai, Ruisheng.(2021).Product innovation concept generation based on deep learning and Kansei engineering.JOURNAL OF ENGINEERING DESIGN,32(10),559-589.
MLA	Li, Xiong,et al."Product innovation concept generation based on deep learning and Kansei engineering".JOURNAL OF ENGINEERING DESIGN 32.10(2021):559-589.