Statistical methods in Kansei engineering: a case of statistical engineering
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Document typeArticle
Defense date2012-07
Rights accessRestricted access - publisher's policy
Abstract
Kansei engineering (KE) is a methodology used to incorporate emotions in products and services design. Its basic purpose is
discovering in which way some properties of a product or a service convey certain emotions in its users. Data are typically
collected using questionnaires. KE studies follow a model with three main steps: (i) defining the elicited emotions (semantic
space); (ii) deciding on the factors that might affect the responses (space of properties); and (iii) modeling how each factor
affects each response (synthesis phase). The procedure resembles that of an experimental design in an industrial context.
However, practitioners of KE are hardly ever statisticians. Statistical techniques in KE are sometimes misused, and the
discipline could benefit from a more extensive use of statistical methods. KE is thus a good area of application of statistical
engineering: focusing not in advancement of statistics but on how current techniques can be best used in a new area.
The aim of this paper is twofold: (i) to present the fundamentals of KE while giving an easy to understand example to
illustrate the procedure; and (ii) to explain why KE is a good example of statistical engineering by proposing improvements
that emanate from the adequate use of statistical techniques.
CitationMarco, L.; Tort-martorell, J. Statistical methods in Kansei engineering: a case of statistical engineering. "Quality and reliability engineering international", Juliol 2012, vol. 28, núm. 5, p. 563-573.
ISSN0748-8017
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