This paper aims at defining a structured process of continuous innovation in the product concept development phase by a statistical‐based Kansei engineering (KE) approach. It consists in the identification of quality elements satisfying both functional and emotional user needs, i.e. the total quality elements.
The approach is developed integrating results from Kano and KE analysis. Three statistical methods considered to be suitable for KE study, are used: supersaturated design for concept configuration, ordinal logistic regression for data analysis, and EVA method for quality evaluation of the optimal concept. These methods are compared with the most used ones in KE regarding their efficacy, efficiency and easiness of use. An innovative procedure to exhibit concepts in a KE session is also presented. It uses the abstraction and association idea principles to elicit users' grade of agreement for a particular Kansei word.
The proposed approach is fully exploited through a case study on train interior design, developed in a virtual reality (VR) laboratory. The evaluation of comfort improvements obtained by means of a new handle and handrail design is carried on with expert users in VR. A consistent increase of a quality index, by using the defined approach, was obtained.
This work aims at contributing to the conception of new product solutions, which are appealing and saleable. The availability of virtual reality technologies and software capable to manage complex statistical analyses, will concretely aid designers and engineers in the ideation of high‐emotional‐quality products, which can be helpful for innovative enterprises to maintain and even increase their market position.
Lanzotti, A. and Tarantino, P. (2008), "
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