Product Form Optimization Design Method Considering The Coupling Of Design Elements And User Perception Differences ——Take The Thermos As An Example

With the globalization of the market and the development of modern science and technology,many similar products are functionally equivalent,and it is difficult for customers to distinguish and choose them.Functional design and usability design no longer give products a competitive advantage.Therefore,it is necessary to design a product by attracting the emotion or attention of customers.The perceptual needs of the target user group are exacerbating the complex characteristics of personalization and diversification,and the user segmentation is deepened.At the same time,the perceptual needs of individual users are composed of multiple perceptual images,and there may be conflicts between each perceptual image;In addition,in the process of product shape design research and development,the unified and coordinated coupling relationship between design elements in product shape should also be fully considered.Therefore,how to accurately express the user’s emotional response to the product and how to integrate the user’s emotional needs into the product form design perceptual reasoning mechanism considering the coupling of design elements will become very important.In this paper,questionnaire surveys are used to obtain the perceptual evaluation data of product form design by different user groups.GABP neural network and NSGA-Ⅱalgorithm are combined to construct a hybrid inductive engineering reasoning mechanism to achieve computer-aided product form optimization design.The main conclusions are as follows:（1）Representative product selection and prototype design.Through market research,it is determined that the research object is a thermos flask product,and a representative product sample library is constructed through preliminary product screening and gray treatment;through the preliminary determination of the beauty index and the product form beauty evaluation experiment,the final representative product is determined.Representative products were deconstructed by morphological analysis,basic design elements and design element levels were determined,and 95 product prototypes were determined by orthogonal test methods for subsequent product form sensitivity evaluation experiments.（2）User group demand extraction considering multi-faceted needs.Due to different consumer preferences,consumers can be divided into different groups according to their aesthetic preferences.This study extracts the needs of grouped users through product form preference evaluation experiments,cluster analysis,morphological perceptual evaluation experiments,and advantage rough sets;and extracts and describes the characteristics of grouped users,confirming this hypothesis that the perception patterns of specific user groups are homogeneous Between "average users" and completely heterogeneous personalized users,that is,their potential common needs have multiple sides（perceptual preference-driven user segmentation）,and the needs of each side are a fusion of personality and commonality.（3）Construct a closed-loop engineering constraint knowledge base and an open-loop geometric constraint knowledge base.In view of the infinite and idealistic characteristics of human material requirements,it tends to pursue the superiority of each element in the scheme.The combination of local optimals often leads to global imbalance.The coupling of closed-loop design elements is proposed through the coupling of design elements.Knowledge base;At the same time,an open-loop geometric constraint knowledge base of design elements is constructed taking into account human-machine characteristics,user personalized requirements,and expert experience.The combination of the two provides constraints for subsequent product form optimization.（4）A multi-objective optimization hybrid inductive reasoning mechanism considering engineering constraints and geometric constraints is established.In this study,based on the perceptual response data sets of different user groups,the associations between the design elements and the perceptual imagery words that represent the needs of each group are separately established as the fitness function of the NSGA-II optimization algorithm.Perceptual imagery is the target of multi-objective optimization,and combined with constraints based on design element coupling,multi-objective optimization is performed to obtain the optimal product form parameters of each user group.Then use SolidWorks 2018 software to perform 3D modeling and Keyshot 6 software rendering to get the final optimization solution,and compare and analyze the optimization results and preference ranking results to verify the feasibility of the solution.This article proposes representative product selection based on the beauty of product form,user grouping based on multi-faceted common needs and preferences,and user emotional needs extraction based on advantage rough sets,which can better build the association between design elements and user emotional needs Rules;combined with engineering constraints based on coupling design elements and geometric constraints based on human-machine performance,multi-objective product form optimization design can be better performed.The combination of the two is a perfect hybrid inductive engineering reasoning machine,which can further improve the development of the inductive engineering system,serve product form design,provide new ideas and methods for product form design,and help thermos bottle companies to better perform product development.