DAKA: design activity knowledge acquisition through data-mining
DAKA: design activity knowledge acquisition through data-mining
复制标题
DOI：
10.1080/00207540600654533
复制
发表时间：
2006-07
影响因子：
9.2
通讯作者：
Yan Jin;Y. Ishino
中科院分区：
文献类型：
--
作者：
Yan Jin;Y. Ishino
工程知识是工业企业的重要资产。本研究的重点是设计活动的知识，它试图开发有效的方法来捕捉这种操作知识的设计过程中监测的设计事件。设计活动被定义为一系列有意义的设计操作，由设计人员执行，以将设计从当前状态推进到新状态。本文提出了一个设计活动知识获取（DAKA）框架，提取设计师的设计活动知识，从计算机辅助设计（CAD）操作事件数据，通过商业CAD系统。DAKA是由一个产品模型路线图捕捉设计师的设计动作的轨迹和一个基于功能的设计操作挖掘算法提取有意义的设计操作从CAD事件数据库。DAKA已通过案例研究使用真实的CAD操作事件数据以及计算机生成的合成数据进行了评估。在本文中，DAKA框架的细节进行了描述，并提出了一个案例，涉及汽车车门设计，以证明所提出的方法的有效性。
Engineering knowledge is an important asset of industrial companies. The present research focuses on design activity knowledge and it attempts to develop effective ways to capture this operational knowledge from the design events monitored during the design process. A design activity is defined as a sequence of meaningful design operations carried out by designers to advance the design from its current state to the new state. The paper proposes a design activity knowledge acquisition (DAKA) framework that extracts designers’ design activity knowledge from the computer-aided design (CAD) operation event data obtained through commercial CAD systems. DAKA is composed of a product model roadmap for capturing the trajectory of designers’ design moves and a function-based design operation-mining algorithm for extracting meaningful design operations from CAD event databases. DAKA has been evaluated through case studies using real CAD operation event data as well as computer-generated synthetic data. In this paper, the details of the DAKA framework are described and a case example involving automotive door design is presented to demonstrate the effectiveness of the proposed approach.