Common design structures and substitutable feature discovery in CAD databases
Common design structures and substitutable feature discovery in CAD databases
复制标题
DOI：
10.1016/j.aei.2021.101261
复制
发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
G. Vasantha;David Purves;J. Quigley;J. Corney;A. Sherlock;Geevin Randika
中科院分区：
文献类型：
--
作者：
G. Vasantha;David Purves;J. Quigley;J. Corney;A. Sherlock;Geevin Randika
据广泛报道，在新的工程设计中重用以前创建的组件或功能将提高公司产品开发过程的效率。虽然工程部件的重用已经建立了度量和方法，但在文献中，特定设计特征（例如加强肋、孔模式或润滑槽等）的重用受到的关注较少。通常，研究人员已经报道了部分设计重用的方法，这些方法主要根据几何上相似的形状（即一组特征）来识别模式，这些模式的元素是相邻的、内聚的，并且与组件的整体形式解耦。相比之下，本文将公共设计结构（CDS）定义为CAD数据库中具有共同参数值（例如直径）的频繁出现的特征（例如孔）的集合（无论其位置或组件上其他特征之间的空间连接）。通过利用已建立的关联规则和项集数据挖掘技术，作者展示了如何有效地计算数百个3D CAD模型的cds。通过一个从公开可用的液压阀数据集中提取的井眼数据的案例研究，展示了如何计算与CDS相关的项目集，并通过识别交互设计过程中潜在的“可替代特征”来支持预测设计。这是使用关联规则和几何兼容性检查的组合来确保系统的建议是可实现的。使用Kullback-Leibler散度来评估组件之间的相似程度被认为是识别“最佳”建议过程中的关键步骤。结果说明了原型实现如何成功地挖掘CDSs，并在工业阀门设计数据集中识别可替代的孔特征。
It has been widely reported that the reuse of previously created components, or features, in new engineering designs will improve the efficiency of a company’s product development process. Although the reuse of engineering components has established metrics and methodologies, the reuse of specific design features (e.g. stiffening ribs, hole patterns or lubrication grooves, etc.) has received less attention in the literature. Typically, researchers have reported approaches to partial design reuse that identify patterns predominately in terms of geometrically similar shapes (i.e. a set of features) whose elements are adjacent, cohesive, and decoupled from the overall form of a component.In contrast, this paper defines a common design structure (CDS) as collections of frequently occurring features (e.g. holes) with common parametric values (e.g. diameters) in a CAD database (irrespective of their locations or spatial connectivity between other features on a component). By exploiting the established data-mining technology of association rules and item-sets the authors show how CDSs can be efficiently computed for hundreds of 3D CAD models. A case study, with hole data extracted from a publicly available dataset of hydraulic valves, is presented to illustrate how item-sets associated with CDS can be computed and used to support predictive design by identifying potentially ‘substitutable features’ during an interactive design process. This is done using a combination of association rules and geometric compatibility checks to ensure the system’s suggestion are implementable. The use of the Kullback–Leibler divergence to assess the degree of similarity between components is identified as a crucial step in the process of identifying the “best” suggestions. The results illustrate how the prototype implementation successfully mines the CDSs and identifies substitutable hole features in a dataset of industrial valve designs.