论文信息 - An Empirical Approach to Optimal Experimental Design Selection and Data Analysis for the Synthesis Phase of Kansei Engineering

An Empirical Approach to Optimal Experimental Design Selection and Data Analysis for the Synthesis Phase of Kansei Engineering

Kansei Engineering (KE) is a methodology able to incorporate, systematically and concretely, people’s emotions into product design solution, above all in concept design phase. This work aims at testing the appropriateness and the robustness of statistical methods which are at this moment new in KE applications. In particular, in order to reduce the length and the reliability of the evaluation session in Virtual Reality environment, optimal experimental designs and methods of analysis are suggested.

[1] Antonio Lanzotti,et al. Kansei Engineering Approach for Identifying “Total Quality” Elements , 2008 .

[2] Stefano Barone,et al. Analysis of user needs for the re-design of a wheelchair , 2008 .

[3] Claudio Conversano,et al. PREDICTION AND CLASSIFICATION IN NONLINEAR DATA ANALYSIS: SOMETHING OLD, SOMETHING NEW, SOMETHING BORROWED, SOMETHING BLUE , 2003 .

[4] P. McCullagh,et al. Generalized Linear Models , 1972, Predictive Analytics.

[5] Dennis K. J. Lin,et al. A new class of supersaturated designs , 1993 .

[6] Jacqueline J. Meulman,et al. Prediction and classification in nonlinear data analysis: Something old, something new, something borrowed, something blue , 2003 .

[7] Dennis K. J. Lin. Another Look at First-Order Saturated Designs: The p-efficient Designs , 1993 .

[8] Stefano Barone,et al. A weighted logistic regression for conjoint analysis and Kansei engineering , 2007, Qual. Reliab. Eng. Int..

[9] Sidney Addelman,et al. trans-Dimethanolbis(1,1,1-trifluoro-5,5-dimethylhexane-2,4-dionato)zinc(II) , 2008, Acta crystallographica. Section E, Structure reports online.

[10] J. Kruskal. Analysis of Factorial Experiments by Estimating Monotone Transformations of the Data , 1965 .