A collaborative tagging system design framework for supporting affective design

Affective or kansei design engineering is a design approach that can help designers to produce emotionally pleasing products. One of the research challenge of this approach lies in understanding customers' affective needs and how to associate such needs with product design features. Previously, we have proposed a collaborative tagging methodology towards understanding associations between affective needs and product design features through analyzing product reviews. In this paper, we proposed a framework for collaborative tagging system design as an extension of our previous work and actual web-based implementation of our approach. We showcase the design of our web-based system which includes client interface layer, web application layer and back-end application processing layer with detailed elaboration on essential system components and modules. Some potential benefits of implementing such a collaborative platform are also briefly discussed.

[1]  C. K. Kwong,et al.  A multi-objective genetic algorithm approach to rule mining for affective product design , 2012, Expert Syst. Appl..

[2]  Roger Jianxin Jiao,et al.  A Kansei mining system for affective design , 2006, Expert Syst. Appl..

[4]  Jitesh H. Panchal,et al.  Extracting the Structure of Design Information From Collaborative Tagging , 2011, J. Comput. Inf. Sci. Eng..

[5]  Weiming Shen,et al.  Computer supported collaborative design: Retrospective and perspective , 2008, Comput. Ind..

[6]  Hui-Ming Wee,et al.  A distributed change control workflow for collaborative design network , 2008, Comput. Ind..

[7]  Soonhung Han,et al.  Collaborative Engineering Design Based on an Intelligent STEP Database , 2002, Concurr. Eng. Res. Appl..

[8]  Shusaku Nomura,et al.  Kansei’s Physiological Measurement and Its Application (2): Estimation of Human States Using PCA and HMM , 2011 .

[9]  Yaokai Feng,et al.  Kansei Database and AR*-Tree for Speeding up the Retrieval , 2011 .

[10]  Mitsuo Nagamachi,et al.  Statistical Analysis for Kansei/Affective Engineering , 2016 .

[11]  Hideki Aoyama,et al.  A study of kansei engineering in pet bottle silhouette , 2011 .

[12]  Mary Lou Maher,et al.  Shared understanding in computer-supported collaborative design , 1996, Comput. Aided Des..

[13]  Jae Yeol Lee,et al.  AR/RP-based tangible interactions for collaborative design evaluation of digital products , 2009 .

[14]  Duck Young Kim,et al.  CO 2 DE: a decision support system for collaborative design , 2010 .

[15]  Ming-Chuan Leu,et al.  A Web-based Intelligent Collaborative System for Engineering Design , 2007 .

[16]  W. Marsden I and J , 2012 .

[17]  Mitsuo Nagamachi,et al.  Innovations of Kansei Engineering , 2016 .

[18]  Yuh-Min Chen,et al.  Enabling collaborative product design through distributed engineering knowledge management , 2008, Comput. Ind..

[19]  Davy Monticolo,et al.  A collaborative Design for Usability approach supported by Virtual Reality and a Multi-Agent System embedded in a PLM environment , 2010, Comput. Aided Des..

[20]  Jiang Xu,et al.  Employing rough sets and association rule mining in KANSEI knowledge extraction , 2012, Inf. Sci..

[21]  Indira Thouvenin,et al.  Supporting design with 3D-annotations in a collaborative virtual environment , 2009 .