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Utilizing text mining and kansei engineering to support data-driven design automation
Conference paper   Open access

Utilizing text mining and kansei engineering to support data-driven design automation

Kong-Zhao Lin and Ming-Chuan Chiu
Advances in Transdisciplinary Engineering, Vol.5, pp.949-958
2017

Abstract

Data-driven Design Design Automation Kansei Engineering Product Development Process Text Mining Computer Science Applications Industrial and Manufacturing Engineering Software Algebra and Number Theory Strategy and Management
With the rapid expansion of Web 2.0, more and more people express their views and comments about products online. To understand and satisfy customer requirements, designers need to find out helpful information from online reviews and design a new one as fast as possible. It's an important phase to identify customer requirements in product development process. However, popular products can get hundreds of reviews, designers often spend a lot of time on identifying customer needs. Therefore, to meet customer requirements and speed up product development process, this research proposes a data-driven design method which combines text mining and Kansei engineering. Text mining is dedicated to capture and analyze the key words from customer reviews. Kansei engineering aims to translate customer needs into the product development domain. According to the result of Kansei Engineering, a CAD model will be generated to visualize prototype. Moreover, a case study of bike is provided to demonstrate the practical viability of proposed method. Under the trend of data-driven design, this is the first study that integrates text mining and Kansei engineering in product development process.
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https://doi.org/10.3233/978-1-61499-779-5-949View
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