【作者】 丁满；

【导师】 孙伟；

【作者基本信息】 大连理工大学 ， 机械设计及理论， 2011， 博士

【摘要】 随着消费者生活品质的不断提升,产品色彩所引发的情感体验开始逐渐成为普通消费者的追逐目标,对于产品色彩的意象偏好与需求成为消费者决定购买和使用产品的重要因素。由于产品开发始终要围绕市场和消费者的需求,因此,多数企业已将产品色彩意象研究视为其生存竞争的主要工具。而传统方法无法充分体现消费者多样且多变的色彩意象需求的问题,已成为制约产品色彩设计水平的瓶颈。因此,如何准确把握及合理表达消费者对于产品色彩的复杂情感意象需求等成为解决这一难题的关键。为此,论文以消费者对于产品的色彩意象感知为研究对象,面向产品色彩设计的实际应用问题,建立一套能够适应产品特征变化,并切实符合消费者真实意象需求的产品色彩设计方法。具体内容如下：1)针对色彩空间分布形式对于消费者色彩意象空间存在影响问题,提出了考虑色彩空间分布的产品色彩意象评价方法。通过深入分析色彩空间分布形式对于消费者色彩意象感知的影响,将色彩空间分布形式引入到产品色彩意象评价模型中；联合分析被用来建构消费者色彩意象感知与各评价属性间的关联,建立了基于色彩空间分布的产品色彩意象评价模型,藉此推论出目标消费者对于未知色彩组合形式所能给予的意象评价值。通过设计实例验证了对于没有确定色彩空间分布形式的一类设计活动,该方法较孟·斯宾瑟美度评价方法更为贴近消费者的主观色彩意象。2)针对多工作模式产品存在色彩面积变化问题,提出了多工作模式产品色彩意象评价方法。重点分析存多工作模式产品的配色特征,将色彩面积变化因素考虑到产品色彩意象评价模型中；基于灰色关联分析法建立产品方案色彩与消费者意象之间的关联模型；运用灰色聚类法判断产品各作业模式下的色彩意象评价值；并将各评价值进行综合考虑,建立了多工作模式产品的色彩意象评价模型。设计实例验证了该方法在处理存在色彩面积变化因素的多工作模式产品的色彩设计问题时,较传统评价方法更加贴近消费者的色彩意象感知。3)针对消费者对于产品色彩意象很难明确给出期望值问题,提出了产品色彩模糊优化设计方法。针对消费者对于色彩意象表达存在的模糊性、不确定性问题,将决策信息不完全明确情况下的产品色彩设计问题转化为给定解空间的最优解模糊搜索问题,建立了产品色彩设计模糊设计模型,并采用将模糊变量进行离散化的方法产生备选方案解集；采用粒子群算法对该模型进行求解,实现产品色彩方案的快速生成;采用折衷规划的方法获得产品色彩的最佳调和方案。该方法能够改善产品色彩设计阶段所遭遇的不确定问题,提高产生满意解的几率,从而提高产品色彩设计品质。通过设计实例验证了该方法的可行性。4)针对消费者对于产品色彩意象的多维性及复杂性,提出了基于多维情感的产品色彩优化设计方法。在对多工作模式产品色彩设计模型扩展的基础上,建立了多维情感产品色彩设计模型；运用因素分析结合普氏分析建立消费者情感需求的多维度空间：采用模糊偏好的方法建立各情感维度间的重要程度关系；采用粒子群算法对多维情感产品色彩设计模型进行求解。该方法能够满足更多消费者的复杂情感意象需求,提高设计成功率,并为解决消费者复杂情感需求问题提供了理论基础。最后通过实例验证了考虑情感准则多维性的重要性以及所提方法的有效性。更多还原

【Abstract】 As life quality increasingly promotes, emotional experience caused by product color has been becoming the pursuing target of ordinary consumers. The preferences and requirements on product color images become the key factor which determines consumers’ purchasing and using behaviors. Product development should be always based on requirements of market and consumers, so most of corporations has considered product color image as a competitive tool. The traditional methods can not completely reflect the various and changeable color image requirements of consumers, which have become the restriction of product color design. Therefore, the key point to solve this problem is to exactly grasp and rationally express consumers’requirements of color image and multi-emotions. For this reason, this paper set consumers’perception on product color image as research object. Aiming at the actual application of product color design, this paper created an intelligent design method which could be adjust to product features and actually satisfy consumer’s image requirements. More details are as follows:Firstly, for the influence of color layout on consumers’color image space, this paper proposed a product color image evaluation method based on color layout. It made depth analysis about the influence of color layout on consumers’color image. It also introduced the factor of color layout into the product color image evaluation model, which was considered as evaluating attribute together with hue, value and chroma. This paper used Conjoint Analysis to construct the relationship between consumers’color image and each evaluation attribute. On this basis, a product color image evaluation method based on color layout was created, in order to deduce evaluation values of target consumers on unknown color combinations. Especially for the undefined color layout, through a design case this method was proved that it was closer to consumers’subjective images than color harmony aesthetics measure model of MoSpencer.Secondly, for the influence of color area changing on consumers’ color image space, this paper proposed an integrated color image evaluation method considering color area changing. It focused on the color combining features of multi-working modes products, and introduced color area changing factors into product color image evaluation model. On the basis of gray relational, the correlative model between product color and image was built. Furthermore, gray clustering method was used to determine image evaluating value for color combination. The color combination images for different working modes were all considered as evaluating attributes, to which the corresponding weights were assigned for synthesized evaluation. This method paid attention to both the variability of product with multiple working modes and the indeterminacy of customers’ subjective images, and then flexibly and directly evaluated the color combination image for the product with multi-working modes. For the color area changing issue, through a design case, it was proved that this method was closer to the subjective image of customers than single-attribute evaluating approach.In addition, for consumers may difficult to provide specific expectation values on product color image, this paper proposed a product color fuzzy design method. Considering the fuzziness and uncertainty of consumers’color image expression, this method transformd product color design with undefined decisions into fuzzy search for optimized solution with given solution space. It constructed product color fuzzy design model, and used fuzzy variables discretization to produce optional scheme solutions. It employed Particle Swarm Optimization to solve the model, and rapidly produced product color schemes. This method is able to improve the uncertainty problem of product color design, increase the generation rate of satisfied solution, and enhance the quality of product color design. Through design case, the feasibility of this method was proved.Finally, According to the multidimensionality and complexity of consumers’requirements on product color image, a product color planning method based on multi-emotion was proposed. This method constructed a multi-dimension space of consumers’emotion requirements. On the expansion of multi-working modes product color design model, it constructed a model of multi-emotion product color design, and used factor analysis and Protodyakonov Analysis to create image dimension. It employed Particle Swarm Optimization to find the solution. This method could meet consumers’multi-emotion requirements, improve design success rate, and provide theoretical basis for complex emotion requirements. Through design case, the importance of considering emotion multidimensionality and the validity of the proposed method were proved.更多还原