Emotional Design Of Product Appearance Based On Online Review And Subjective Evaluation

Users’ demand is the key to promoting product design.Previous product design was mainly focused on functional attributes.However,with the improvement of consumption level and the development of users’ personalized demands,consumers are paying more and more attention to whether the product design could meet their emotional demands.Emotional design has become a leading research issue in human factors engineering and become the future development trend of enterprises product design.In the main research field of emotional design,how to accurately obtain users’perceptual evaluation data and effectively identify the key design elements of the product,so as to establish a relationship model between the product design elements and users’ emotions has become a theoretical problem to be solved in the emotional design practice.By referring to the theories of kansei engineering and online text mining technology,this paper proposed a method of emotional design for product appearance based on the combination of online review data and the subjective evaluation methods.The main research contents and conclusions of this article are as follows:(1)Aiming at some existing problems in the process of product design and perceptual evaluation in traditional kansei engineering research,online text mining technology was used to collect a large number of users’ online review data to obtain users’perceptual evaluation information.(2)Processing the acquired text data to extract emotional words that described the product.Since the online review data can fully reflect the user’s true emotional demands,these emotional words are screened and sorted by frequency,and the emotional words with the same or similar expressions are summarized so that finally the frequency can be combined to determine the kansei words for emotional evaluation of products.(3)Considering multi-dimensional design features of the product,the wireless mouse products were deconstructed and analyzed according to functional features and non-functional features.Combined with online review data,this paper extracted terms describing product design features,and obtained some product design features that users were more concerned about,and then determined 12 key design elements of the wireless mouse.Orthogonal experimental design method was used to generate 32 prototypes of wireless mouse products in this paper,and Rhino software was used to build 3D product prototypes so that the colors and materials could be rendered using KeyShot software.(4)According to the determined kansei words and combined with the generated product prototypes,a questionnaire was designed using the semantic difference method and Likert scale so that a perceptual evaluation experiment could be conducted.Next,design elements of product were coded in 01,and the obtained perceptual evaluation data was analyzed.Then this paper used RBF neural network method to build a relationship model between users’ kansei words and product design elements,and then the model was verified.(5)The MOPSO algorithm in the particle swarm optimization algorithm was proposed in this paper,which used the trained RBF neural network model as the objective function to construct a multi-objective design optimization model.According to the relevant constraints,optimal plans for the emotional design of the product appearance was obtained,and the optimization results were analyzed and verified.The finally results showed that the optimized plan could obtain a better users’ perceptual evaluation.