基于感性工学的电动平衡车外观设计研究

为掌握消费者对平衡车的需求,设计符合消费者需求的产品,文章运用感性工学的基本原理分析感性工学在电动平衡车设计中的作用。通过收集市面上最具代表性的平衡车作为研究样本,对平衡车类别进行分类。运用调查问卷、语义差异法、形态分析法等方法构建感性评价系统,从而为平衡车设计提供设计思路,以达到良好的市场效应。     

感性微分法在产品设计中的探讨

感性工学是将感性与工学相结合的一种技术,其在产品设计中的应用,主要通过分析人的感性来建立产品构想模型,并据此来设计产品。感性微分法是感性工学中的一种定性研究方法,这种方法可以通过感性概念的逐步细分从而和设计元素建立起一一对应关系,本文试图应用感性微分法在产品设计中的作用进行探讨,并以行李箱的拉杆设计为例就感性微分法的应用进行探讨。     

产品设计的感性品质

如何使产品具有感性品质,正成为当前设计的研究方向。越来越多的研究者认识到需要在工程技术领域导入人类的感性分析。本文介绍了作为非物质因素的感性工学在产品设计中的作用,探讨了人的情感与产品设计特征的微妙关系,阐述了产品设计中的感性品质以及感性工学在工业设计中的应用前景。     

浅析感性工学理论在家用理疗产品上的运用

"感性工学"一词是由山本健一于1986年在美国演讲时提出"Kansei Engineering"设计理念时出现的,并广泛引起了汽车界的关注。通过对使用者情感因素的分析研究,从而设计出能够满足使用者情感诉求的产品,这是感性工学的最终目的,因而通过对感官因素的分析研究,把握家用理疗产品中的感性设计,才可以设计出让使用者各方面都感觉舒适的家用理疗产品。     

多意象驱动下的产品造型个性化定制系统研究

构建了一种基于多意象驱动下的产品个性化定制系统,增加用户对个性化定制的体验度,从而实现智能的产品个性化定制设计。通过对当下三种产品个性化定制模式的比较研究和分析,提出了个性化定制系统的构架模型和系统流程。然后通过用户参与模式、感性意象挖掘、关联方法建立多意象驱动机制,并结合感性工学的相关研究方法、BP神经网络以及多目标粒子群算法构建了面向产品意象造型的智能设计模型,实现了多意象驱动下的产品造型个性化定制。最后以人形卡通文具的个性化定制进行了实例验证。结果表明多意象驱动的产品造型个性化定制系统更加丰富了消费者对产品造型意象风格的体验,满足了消费者日益迫切的个性化设计需求,符合智能时代对产品设计开发的需要。     

基于传统心理学和现代认知神经科学的产品情感获取方法研究

文章从传统心理学和现代认知神经科学的双重角度出发,总结多种消费者对产品的情感获取方式,并对其进行对比,预测发展趋势,提出了只有综合运用多种方式才能更加准确有效的获取情感,并为情感量化打下基础,旨在为感性工学在中国的发展提供理论基础,从而指导产品设计的方向。     

感性消费的情感诉求和产品设计的战略

研究及把握消费者的感性消费心理,能注重了解客户,把握消费者心理需求从而推出适合于消费者的产品设计和战略。使设计出的产品是企业、社会和消费者真正需要的产品,不仅给企业、社会带来良好的经济效益,也会成为消费者真正解决生活中的问题与需求。     

网络符号在产品设计中的应用探析

以文具设计为例,分析青少年的生活习惯,指出网络符号是青少年交流的重要工具,能反映他们的喜好,进而根据符号消费理论,制定产品设计策略并进行设计实践,探索符号在产品设计中的应用路径。启示设计师在消费社会,要平衡产品、符号、消费者之间的关系,要挖掘消费者潜在的符号需求。     

网页人机界面感性化研究

通过阐述感性工学与网页人机界面设计两者的关系,从而论证将感性工学应用在网页人机界面设计的必要性。采用逆向式感性工学的以用户为中心的方法对少儿网站进行调查分析,再将调查结果采用前推式感性工学的方法得出少儿网站界面感性意向树状图,提出目前网站设计中的不足以及应该改进的方向,从而为感性化少儿网站设计提供理念支持。     

面向大众消费者的产品感性定制模型及其应用

为了使产品定制模型更加适合缺少相关领域专业知识的大众消费者,建立了基于感性工学的产品感性定制模型.将顾客对产品的感性意象作为定制需求,对其进行分类并量化,利用层次分析法评价待选的产品工程配置实例,获得最符合顾客感性意象需求的产品工程配置.最后用自行车定制系统实例说明了该模型的应用.     

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.     

Application of Evolutionary Neural Networks on Optimization Design of Mobile Phone Based on User's Emotional Needs

Taking users’ emotional needs into consideration, this research aims to propose a new method to present product design features exactly and completely. On the basis of genetic algorithm integrated with back‐propagation (BP) neural networks, taking the mobile phone as research object, an optimization design algorithm was finally designed. First, the continuous and discrete design variables that describe mobile phones were screened with methods of dimensions, coordinate label, and morphological analysis. Forty three‐dimensional (3D) mobile phone models were designed by using 3D design software PROE. Accordingly, 12 representative mobile phones were selected through multidimensional scaling analysis and cluster analysis. Fourteen pairwise Kansei image words were obtained by collecting, screening, surveys, and statistical analysis method. Second, a BP neural networks model between design variables and user preference along with Kansei image words was established and verified with questionnaire survey data. Finally, the optimization design model for mobile phones was established considering design requirements and users’ emotional needs. A genetic algorithm integrated with BP neural networks was used to optimize mobile phone design. The results show that the optimization scheme is superior to others, and this paper will provide design suggestion for mobile phone designers.     

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.     

Kansei assessment of the constituent elements and the overall interrelations in car steering wheel design

In most studies on Kansei, the product form analysis model is based on the external features or elements of the product components. However, such an approach cannot completely convert consumer emotional perceptions into design elements. Therefore, this study combined the ergonomic technology used in Kansei engineering with the unique cognitive ability of humans to identify patterns and establish an emotional perception model that can integrate the overall interrelations of the constituent elements. Steering wheel design was used as the object of examination. Three types of adjectives were applied to describe the constituent elements. The first type was esthetic factors and involve external esthetics. The second type comprised two pairs of adjectives, sturdy/delicate and lightweight/heavy, called operational strength factors because they relate to form and strength. The third type comprised simplistic/changeful and artificial/spontaneous, called modernity factors because they pertain to the modern sense of beauty of the parts. Multiple linear regression analysis was used to construct a Kansei engineering model and compare the performance of individual elements and the product as a whole. The results show that the R² values in the overall model were greater than those in the element-oriented model, indicating that the integrated model outperformed the element-oriented model in variance explanation. The differences between the numerical values of the adjective pairs classic/fashionable (esthetic factors), sturdy/delicate (operational strength factors), and simplistic/changeful and artificial/spontaneous (modernity factors) were significant, demonstrating that the overall model is useful in predicting how consumers make assessments according to emotional perceptions. The R² increase of the modernity factors was the most obvious, indicating that the overall model assesses modernity more accurately. Comparing results and verifying test samples demonstrated that the overall model is more useful in predicting consumer appraisals that are based on emotional perception.Relevance to industryThis study determined that esthetics, operational strength, and modernity are the three most crucial factors in the emotional perceptions and preferences of consumer regarding steering wheel design. The results demonstrate that a model that integrates constituent elements can evaluate consumer behavior and assist product designers in understanding consumers.     

The modified Kansei Engineering-based application for sustainable service design

Considering the human-centered design, this paper shows a modified-integrated approach of how to quantify the impact of perceived Kano's attractive services on perceived emotional satisfaction (Kansei), followed by the formulation of innovative ideas for sustainable services using TRIZ (known as Theory of Inventive Problem Solving). The Kano's attractive service attribute is deemed to be a significant emotional booster (known as Kansei). Kansei Engineering (KE) is used to highlight the level of customer emotional satisfaction due to perceived service offerings. For the past seven years, there has been a rapid concern in Kansei Engineering (KE) in services. However, previous research of KE has mainly focused on the improvement and analysis of general service domains. There is little attention to sustainable services. Hence, this study provides a modified KE-based approach and aims to understand and satisfy customer emotional needs (Kansei) considering the social, environmental and economic performance. An empirical study in an international airport lounge and lobby services was conducted to confirm the applicability of the proposed model. Purposive sampling through in-depth-interview and face-to-face questionnaires which involved 100 valid subjects was used. Theoretically, these studies show the importance of Kansei's role in sustainable service development, highlighting more innovative and breakthrough solutions with less contradiction and “true-meaning” of Kansei. Practically, it provides a guideline for service designer and manager in identifying which attractive-based service attributes need to be prioritized considering Kansei satisfaction.     

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.     

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。     

基于网络的产品可用性评价系统的设计与实现

随着科学技术的不断发展和产品智能化水平的不断提高,产品的可用性已是消费者决定是否购买产品的主要因素,因此,提高产品的可用性已成为提高产品竞争力的核心。如何保证设计的产品既符合用户的需求又方便易用,即可用性问题,成为必须不断深入研究的问题。论文将目前国内外企业针对界面设计的可用性理论引入到工业产品设计中,从产品设计的角度对工业产品的可用性评估原则、流程和方法进行了探讨性研究。     

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。     

Optimization Design of a Webpage Based on Kansei Engineering

Webpage design has become an important component affecting user satisfaction when they surf the Internet. Interface designers are struggling to improve the quality of user experience by designing webpages that meet users’ emotional needs. An optimization design method of webpage interface is proposed in this study based on Kansei engineering theory, and a job‐hunting website homepage is taken as the research example. After determining the materials, the semantic differential (SD) method is used to extract user‐centered emotional dimensions, and the key design factors of homepages’ appearance are acquired. Next, based on the obtained semantic differential evaluation data, back propagation neural network (BPNN) is conducted to identify quantitative relations between key design factors and emotional dimensions. Finally, genetic algorithm (GA) is employed to search for a near‐optimal design. The proposed method is helpful to design webpages that can satisfy participants’ emotions. It can also be used in a variety of design cases.