摘要
为解决用户认知差异性及局限性所导致的需求获取不充分的问题,提出一种面向相似认知用户集群的TRIZ系统资源需求获取模型。该模型通过模糊卡诺方法对产品用户需求进行分类优化,使用K-modes算法对用户进行聚类分析,获取具有相似认知类型的用户集群;分析集群中已存在的用户属性、使用环境属性等超系统资源并进行拓展演化,获取潜在超系统资源;根据新资源特性得到产品潜在需求与产品设计目标。以自走式圆捆机为例证明了该方法的有效性。
To solve the problem of insufficient demand acquisition caused by user cognitive differences and limitations,a demand acquisition model by Triz system resource analysis was proposed for similar cognitive user clusters.User demands trend of product were differentiated by fuzzy Kano method and clustered users with K-modes algorithm to get user clusters with similar cognitive types.The existing super-system resources such as user attributes and usage environment attributes in the cluster was analyzed and expanded to get potential super system resources.Potential product requirements and product design goals was established based on new resource characteristics.The effectiveness of the method was illustrated by a self-propelled round baler.
作者
苏珂
崔元
SU Ke;CUI Yuan(Institute of Automation, Qilu University of Technology(Shandong Academy of Sciences), Jinan 250013, China;School of Arts and Design, Qilu University of Technology(Shandong Academy of Sciences), Jinan 250353, China;School of Mechanical and Automotive Engineering, Qilu University of Technology(Shandong Academy of Sciences), Jinan 250353, China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2021年第7期2065-2077,共13页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(51405252)
中国博士后科学基金面上资助项目(2020M672101)
山东省博士后基金创新资助项目(202002046)
齐鲁工业大学(山东省科学院)国际合作资助项目(QLUTGJHZ2018022)。
关键词
产品创新
用户集群
用户认知
潜在需求
超系统资源
product innovation
user cluster
user cognition
potential demand
super systems resources
