产品感性评价系统的模糊D-S推理建模方法与应用

建立了用户对产品的感性评价与模糊D-S证据理论的关联模型;利用产生式规则来表达用户感性评价知识;以产品的部件外形来构成推理的证据部分;以感性词汇集及相应的语意差分值来定义规则的目标集.通过模糊D-S证据理论的规则合成算法,最终获得了用户对整体产品评价及可靠度.该方法能有效地解决感性认知中的"未知性"及评价日标的单一性问题,并在以汽车为例的概念设计中得到较好应用.     

基于模糊逻辑的产品意象造型设计研究

为设计出符合消费者感性需求的产品,采用基于模糊逻辑的产品意象造型设计方法.首先确定感性词汇与造型设计要素,利用模糊逻辑建立二者之间的关系.通过模糊化、模糊规则的构建、模糊推理以及反模糊化等过程进行模糊逻辑控制器的设计,用Matlab 建立仿真模型,最后通过测试验证了模型的有效性.结合折叠自行车造型设计进行研究,结果表明...     

基于美学特征的参数化产品外形设计及其美学评价

运用形态控制参数表达产品的形态要素,提出一种基于美学特征的工业缝纫机参数化外形设计方法.修改模型特征参数,可生成不同形态的缝纫机外形;将模型特征参数及对应的美学评价结果作为训练样本,构建了基于神经网络的美学评价系统.最后利用该评价系统给出了最佳美学评价指标下的缝纫机外形模型.     

基于犹豫模糊语言术语集和粒子群优化算法的产品造型设计感性评价方法

产品造型感性评价反映了用户的意象感知,具有模糊性与不确定性,用户常难以准确描述其感 性偏好而表现出犹豫。针对该问题,引入犹豫模糊语言术语集(HFLTSs)描述用户感性评价,基于其数学算子构 建犹豫模糊语言共识模型以测度用户认知一致性程度,借助粒子群优化算法(PSO)实现非共识条件下用户评价 矩阵的优化与共识达成,通过逼近理想解排序法对产品造型方案进行优劣排序,提出了基于 HFLTSs 和 PSO 的 产品造型设计感性评价流程。以汽车充电桩造型方案感性评价为例,验证了 HFLTSs 有助于解决用户感性认知 的不确定问题,结合 PSO 能够提高犹豫模糊语言评价的一致性,从而提升产品造型感性评价质量。     

基于可拓表征与神经网络的苗族图案设计

针对苗族图案的文化传承及设计应用问题,提出基于可拓表征和神经网络的民族图案创新设计方法,对苗族蜡染图案进行解构、映射和重构.首先对苗族蜡染图案进行可拓表征,运用发散树法构建设计生长阶段模型对苗族图案基元进行拓展分析.其次基于感性工学对苗族蜡染图案进行感性意象分析,提出一种面向图案构型、纹样语义和种类的图案解构方法,构建图案特征要素解构空间和情感意象认知空间.运用神经网络构建感性预测模型根据用户意象偏好推荐图案构型等设计要素,对设计思维进行收敛,并与线性回归预测模型进行对比验证其优势性.最后根据神经网络感性预测模型推荐的特征要素应用形状文法对苗族蜡染图案进行细化设计.以苗族蜡染图案为例,验证该方法的可行性,为其他民族图案的解构及创新设计提供参考.     

基于感性工学的产品客户化配置设计

基于感性工学理论及产品平台设计思想,提出了一种产品客户化配置设计方法.通过感性评价的问卷调查方式及回归分析方法建立感性意象与设计参数间的量化关系,同时辨识出平台参数与个性参数;在保持平台参数不变的基础上,改变个性参数进行产品造型以作为第二次问卷调查的样本.通过喜好评价的问卷调查形式,采用聚类分析方法对顾客进行基于喜好相似度的客户群聚类,并采用多项式回归模型建立各自的喜好度与个性参数间的量化关系模型,从而得到各个客户群的符合其最佳满意度的个性参数配置.最后,以手机机身设计为例进行说明.     

基于大型模糊认知图的复杂系统建模与推理研究

模糊认知图作为一种智能计算工具,具有直观的知识表达、快速的数值推理能力等优点,适用于系统建模与推理.为了实现复杂系统关联认知与聚类的集成挖掘,进而达到对它的有效分析与决策,在面向复杂系统的大型模糊认知图研究基础之上,提出了用于三江源生态决策的大型模糊认知图关联认知、状态建模与推理的思路与方法,它不仅可以提升大型模糊认知图在复杂系统建模与推理方面的理论研究,也将拓展其应用领域.     

面向产品造型风格的用户认知模式及量化模型研究

针对产品造型设计过程中存在的主观感性认知偏见问题,提出一种面向产品造型风格的用户认知模式及量化模型。首先对产品造型风格中的特征元素进行显著性分析,并结合"风格曲线"及特征线概念探究了特征元素收敛至线性轮廓的用户认知模式;继而在特征整合的基础上提出产品造型风格的一般认知模式,即伴随着用户认知的不断深化,产品造型风格在用户头脑中将逐渐收敛至产品特征元素的线性轮廓;最后结合MATLAB相关系数概念提出特征元素线性轮廓的量化模型,为产品设计提供客观、理性的决策依据。以中国高速列车CRH380系列产品造型进行眼动跟踪实验,验证了该理论模型的可行性。     

考虑客户感性需求下的产品模块化配置方法

感性需求是客户需求的重要组成部分,也是影响其购买行为的重要因素.为了在产品配置中满足客户感性需求的目标,遵循感性需求特性和在产品上作用机制的特点,提出了在感性需求和功能需求双重驱动下的产品模块化配置方法.该方法按照客户感性需求表达的特点,设计了从客户感性空间压缩到设计感性空间而获取感性偏好的方法;进而根据感性需求实现的特殊性,提出了符合其要求的映射规则和配置规则;在此基础上,根据对感性需求和功能需求的权衡提出产品模块化配置的求解策略,充分符合了感性需求性质特点.最后通过一个汽车产品实例说明了考虑感性需求下的产品模块化配置过程.     

基于BP神经网络的壁挂式充电桩产品形态研究

通过对壁挂式充电桩感性意象与形态设计要素的分析,建立两者间对应的BP神经网络设计模型,从而得到各感性意象对应的产品形态。利用感性工学中的李克特量法对收集到的壁挂式充电桩形态样本和感性词汇进行设计评价并得到感性评价结果,将形态设计要素作为BP神经网络模型的输入层参数,感性评价结果数值作为输出层参数,利用Matlab软件进行壁挂式充电桩BP神经网络模型的反复训练和测试,最终得到壁挂式充电桩形态设计要素BP神经网络模型。最后通过MSE度量该BP神经网络模型准确性,研究表明建立的壁挂式充电桩感性意象和形态设计要素间的BP神经网络模型具有可行性。     

产品形态多意象蛛网灰靶决策模型

针对概念设计中多意象设计方案决策困难的现象,提出了一种产品形态多意象蛛网灰靶决策方法。首先,运用感性工学相关方法获取设计主体的认知数据,结合熵权法及博弈论思想构建基于设计主体认知数据的综合评价模型,并根据各意象的设计主体综合评价数据确定各意象的权重关系;其次,通过人工选择的方式从产品形态进化系统中选择多个进化方案,运用蛛网图表征各进化方案的意象关系,构建多意象蛛网灰靶决策模型,计算决策系数,对其进行比较排序,得到符合设计主体认知的相对最优方案;最后,应用灰色关联分析法验证该决策模型的可行性。结果表明,该模型能够帮助设计师在设计决策阶段快速、准确地确定符合多设计主体认知的多意象方案,为产品方案的多意象决策提供了新的理论和方法。     

基于感性工学的文具产品形态设计研究

随着社会发展,消费者对于产品的精神和情感需求越来越高。因此,如何有效的获取消费者的心理情感需求,并进行有效转化至产品设计之中,成为设计中的新课题。感性工学正是在这种情形下产生,其旨在探求消费者情感与产品特性的对应关系,服务于消费者。本文将以文具设计为例,简述感性工学在文具设计中的应用。     

基于人群感性认知的产品符号提炼及运用

当今已进入"感性消费"时代。这就要求产品设计者不但要了解感性认知如何影响消费者行为。也要掌握体现产品形态语意的符号的获取方式。本文利用心理描述测试法和聚类分析验证了情感矩阵的感性人群分类方式在中国的可适用性。并以座椅为例,利用SD语意差异法和主成因子分析法,对其感性认知经验进行了产品符号的提炼和验证运用。提炼出的产品符号在帮助设计者构思或验证未来感性产品设计这点上具有一定的参考价值和意义。     

Relationship between eye fixation patterns and Kansei evaluation of 3D chair forms

Understanding how to induce Kansei (emotion or affect) in consumers through form is critical in product design and development. Conventional Kansei evaluations, which involve subjectively evaluating the overall form of a product, do not clarify the effects of the individual parts of a product on people’s Kansei evaluation. A microscale analysis of eye movement of people looking at product form may redeem this flaw in subjective evaluation. However, simultaneously recording eye movement when people making Kansei evaluation is challenging, previous studies have typically investigated either the relationship between form and eye movement or the relationship between form and Kansei separately. The eye movement of people while performing Kansei evaluations on product forms still has not been clarified. To address this issue, the present study used an eye tracking system to analyze the changes in the fixation points of people performing various Kansei evaluations. Twenty participants were recruited for 8 Kansei evaluations on the form of 16 chairs by using the semantic differential (SD) rating, while their eye movements on these evaluations were tracked simultaneously. Through factor analysis on the data of Kansei evaluations, two principal factors, valence (pleasure) and arousal, were extracted from the 8 Kansei scales to constitute a Kansei plane which is compatible to Russell’s circumplex model (plane) of affect By adopting the factor scores of the 16 chairs as coordinates, the 16 chairs were mapped into the Kansei plane. Further analysis on the eye fixation on the chairs located in this plane concluded the following results: (a) Pleasure had a more significant effect on the participants’ visual attention compared to arousal; the participants required more fixation points when evaluating the chair form that induced displeasure. (b) The participants typically fixated on two parts of the chairs during their Kansei evaluations, namely the seat and the backrest, indicating that seats and backrests are the two primary features people consider when evaluating chairs. The results clarify the effect of various Kansei on eye movements; thereby enable predicting people’s Kansei evaluations of product forms through analyzing their eye movement.     

Constructing a hybrid Kansei engineering system based on multiple affective responses: Application to product form design

This study proposes an expert system, which is called hybrid Kansei engineering system (HKES) based on multiple affective responses (MARs), to facilitate the development of product form design. HKES is consists of two sub-systems, namely forward Kansei engineering system (FKES) and backward Kansei engineering system (BKES). FKES is utilized to generate product alternatives and BKES is utilized to predict affective response of new product designs. Although the idea of HKES and similar hybrid systems have already been applied in various fields, such as product design, engineering design, and system optimization, most of existing methodologies are limited by searching optimal design solutions using single-objective optimization (SOO), instead of multi-objective optimization (MOO). Hence the applicability of HKES is limited while adapting to real-world problems, such as product form design discussed in this paper. To overcome this shortcoming, this study integrates the methodologies of support vector regression (SVR) and multi-objective genetic algorithm (MOGA) into the scheme of HEKS. BKES was constructed by training SVR prediction model of every single affective response (SAR). The form features of these product samples were treated as input data while the average utility scores obtained from all the consumers were used as output values. FKES generates optimal design alternatives using the MOGA-based searching method according to MARs specified by a product designer as the system supervisor. A case study of mobile phone design was given to demonstrate the analysis results. The proposed HKES based on MARs can be applied to a wide variety of product design problems, as well as other MOO problems involving with subjective human perceptions.     

A product configuration analysis method for emotional design using a personal construct theory

Identifying emotion-related product attributes (perceived by consumers) is no easy task in the realm of emotional design. Conventionally, this process relies heavily on the researchers who conduct the Kansei experiments selecting product attributes such as color, form, and texture for Kansei studies. However, in so doing, other product attributes that also play a vital role in product-emotion associations might be neglected by the researchers. More importantly, the identification of product attributes should be based on consumer's point of view (and feelings). Accordingly, a personal construct theory based product configuration analysis method is proposed in this work. The method develops the customer's mind map for each Kansei tag in order to capture replications of candidate products. A means-value chain is used to generate targets which are later compared with candidate products by consumers. The comparison results could suggest product attributes that are relevant to the desired Kansei. The proposed approach is presented and illustrated using a case study of Graffiti designs on notebooks. Results obtained are discussed. It appears that the proposed method is promising in identifying product attributes with desired Kansei impacts.     

The influence of user cognition on consumption decision-making from the perspective of bounded rationality

Consumer decision-making is related to the success or failure of enterprises, and products that cater to the cognitive preferences of users have become a focus of current research. Based on the theory of bounded rationality, this paper explores the cognitive process of consumer decision-making. Then, how product shape affects consumption decision-making is analyzed with eye-tracking technology. Finally, the design principle of the product form is further explored. The results demonstrate the following: (1) the perceptual cognition of users has a driving effect on consumption behavior; (2) as a key factor affecting the perceptual cognition of users, product form affects consumer decision-making by influencing the degree of approach motivation; (3) by establishing the mapping relationship between product form elements and user images, the principles of product form design can be more consistent with user image preferences. This study provides useful suggestions for how to increase the purchase behavior of users from the perspective of bounded rationality.