Presidential Young Investigator Award: Feature-based Manufacturing

这位总统青年调查员的研究有两个 目标. 第一个目标是创建软件技术来估计 根据存储的零件描述自动计算制造成本 在计算机辅助设计（CAD）系统中作为实体模型。 制造成本是机械加工过程的函数， 车削加工过程是零件特征的函数。 建议的成本估计器由两个模块组成：一个功能 识别器和特征解释器。 识别器作用于 实体模型边界表示以提取形状特征。 的 解释器在选择制造工艺时使用特征 以及确定处理成本。 除了明显的好处之外， 能够在设计过程中估计成本， estimator将帮助确定一组有用的表单特征， 制造业一般。 第二个目标是开发一种功能语言， 用于根据几何和拓扑描述要素 基元，例如面、边、顶点和顶点-边循环。 特征在CAD中的使用还处于起步阶段，主要是因为没有 已经形成了完整的分类体系。 分类法取决于 基于某些特征对特征进行排序的能力。 一 具有格式良好的语法的特征语言将允许明确的 为各种类别的特征编写定义。 候选语言构造包括句法模式语法和 图文法 这项研究的结果将产生一个纲要， 功能，并以有组织的数学方式定义 并储存起来 这一进步将有助于那些参与这两个 特征识别和基于特征的设计。

The research of this Presidential Young Investigator has two goals. The first goal is to create software techniques to estimate automatically manufacturing costs based on a part description stored in a computer-aided design (CAD) system as a solid model. Manufacturing costs are a function of the machining process, and, in turn, the machining process is a function of the features of a part. The proposed cost estimator consists of two modules: a feature recognizer and a feature interpreter. The recognizer acts on a solid model boundary representation to extract form features. The interpreter uses the features in selecting manufacturing processes and determining processing costs. In addition to the clear benefit of being able to estimate costs during the design process, the estimator will help determine a useful set of form features for manufacturing in general. The second goal is to develop a feature language that can be used to describe features in terms of geometric and topological primitives such as faces, edges, vertices, and vertex-edge loops. The use of feature in CAD is in its infancy, primarily because no complete taxonomy has been developed. The taxonomy depends on the capability to sort features based upon certain characteristics. A feature language with a well-formed grammar would allow unambiguous definitions to be written for various classes of features. Candidate language constructs include syntactic pattern grammars and graph grammars. The results of this research will yield a compendium of features together with an organized and mathematical way to define and store them. This advances will aid those involved in both feature recognition and feature-based design.