A new fuzzy approach to improve fashion product development

Lau, T.W.; Chiu, Patrick; Ng, Frency Sau-Fun; Chan, Keith C. C.

doi:10.1016/j.compind.2005.04.003

Cited by 45 publications

(29 citation statements)

References 15 publications

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“…One important task of the Kansei engineering framework is the evaluation of relationships between the defined affective dimensions and the design attributes. Various approaches have been attempted in previous studies on modelling the affective relationships such as quantification theory I (Chang 2008), ordinal logistic regression (Barone, Lombardo, and Tarantino 2007), partial least-squares analysis (Nagamachi 2008), artificial neural network (Lai, Lin, and Yeh 2005;Chen, Khoo, and Yan 2006), fuzzy logic approach (Lau et al 2006;Lin, Lai, and Yeh 2007), FR (Sekkeli et al 2010), genetic programming-based FR , support vector regression model (Yang and Shieh 2010) and ANFIS (Kwong, Wong, and Chan 2009). Orsborn, Cagan, and Boatwright (2009) quantified aesthetic form preference using utility functions.…”

Section: Previous Studies On Affective Designmentioning

confidence: 99%

A methodology of integrating affective design with defining engineering specifications for product design

Jiang

Kwong

Liu

et al. 2014

International Journal of Production Research

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Affective design and the determination of engineering specifications are commonly conducted separately in early product design stage. Generally, designers and engineers are required to determine the settings of design attributes (for affective design) and engineering requirements (for engineering design), respectively, for new products. Some design attributes and some engineering requirements could be common. However, the settings of the design attributes and engineering requirements could be different because of the separation of the two processes. In previous studies, a methodology that considers the determination of the settings of the design attributes and engineering requirements simultaneously was not found. To bridge this gap, a methodology for considering affective design and the determination of engineering specifications of a new product simultaneously is proposed. The proposed methodology mainly involves generation of customer satisfaction models, formulation of a multi-objective optimisation model and its solving using a chaos-based NSGA-II. To illustrate and validate the proposed methodology, a case study of mobile phone design was conducted. A validation test was conducted and the test results showed that the customer satisfaction values obtained based on the proposed methodology were higher than those obtained based on the combined standalone quality function deployment and standalone affective design approach.

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Section: Previous Studies On Affective Designmentioning

confidence: 99%

A methodology of integrating affective design with defining engineering specifications for product design

Jiang

Kwong

Liu

et al. 2014

International Journal of Production Research

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show abstract

“…Surprisingly, however, very few research works address the NPD in the fashion industry. Lau et al (2006) proposed a fabric advisory system using fuzzy logic for fabric selection in fashion product development. The research work of Lau is limited to the selection of the mechanical properties of the fabric.…”

Section: Previous Work On Npd Using Kbsmentioning

confidence: 99%

A RFID-case-based sample management system for fashion product development

Choy

Chow

Moon

et al. 2009

Engineering Applications of Artificial Intelligence

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“…In such a case, the use of fuzzy numbers and linguistic terms may be more suitable. The application of fuzzy AHP has become popular in recent years [39][40][41].…”

Section: A Simplified Anp Model With Sensitivity Analysismentioning

confidence: 99%