Detecting design trends using perceptive tests based on an interactive genetic algorithm

Emilie Poirson (1) , Jean-François Petiot (1) , Julien Bénabès (1) , Ludivine Boivin (2) , David Blumenthal (3)

1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes
2 Renault
3 GENIAL - Génie industriel alimentaire

To avoid flops, the control of the risks in product innovation and the reduction of the innovation cycles require valid and fast customer's assessments. An Interactive Genetic algorithm is proposed for eliciting user's perceptions concerning the shape of a product, in order to stimulate creativity and detecting design trends. Interactive users' assessment tests are conducted on virtual products, for capturing and analyzing users' responses. The IGA is interfaced with a CAD software (CATIA V5) and allows the creation in real time of a set of parameterized designs, which are presented iteratively by a graphical interface to the user for evaluation. After a description of the IGA, we present a study on the convergence of the IGA, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 20 users on a particular product, table glasses. We describe the implementation of the perceptive tests and an analysis of the results. These results show how the IGA can be used to elicit user perception and detecting design trends.

Mots clés: interactive genetic algorithms; shape design; convergence; perceptive tests

Domaines: Génie mécanique [physics.class-ph]; Génie mécanique [physics.class-ph]

Emilie Poirson, Jean-François Petiot, Julien Bénabès, Ludivine Boivin, David Blumenthal. Detecting design trends using perceptive tests based on an interactive genetic algorithm. IDETC 2011, Aug 2011, Washington, United States. pp.DETC 2011/DTM-47923. ⟨hal-00620213⟩