Enabling Design Re-use through Predictive CAD

工程设计工作通常包括重用、配置和组装现有组件、解决方案和知识。有人提出，超过75%的设计活动包括对先前存在的知识的再利用。然而，尽管设计重用活动很重要，研究人员估计，69%的公司没有系统的方法来防止“车轮的重新发明”。支持设计重用的主要问题是提供部分重用以前的设计以满足新需求的解决方案。尽管十多年来，致力于创建“3D形状的谷歌”的3D搜索技术在能力和速度上都在不断提高，但它们并没有得到广泛的应用，被称为“寻找问题的解决方案”！这个项目的动机是相信，随着一种新型的用户界面的出现，3D搜索可以成为解决设计重用问题的解决方案。在手机上，“预测文本”系统通过将片断与之前消息中使用的词典或短语进行匹配来完成单词或短语的拼写。类似地，“预测性CAD”系统将使用“形状搜索”技术来完成3D模型，以交互方式将部分CAD特征与部件数据库进行匹配。以这种方式，系统将向用户提示完成或延伸用户添加的几何图形的3D组件的片段。这样的系统可以通过使已建立的设计的重用成为工程设计的有效部分来潜在地提高设计生产率。虽然到目前为止，许多研究人员已经证明了从三维元件数据库中检索元件的基于特征的方法，但所报道的系统相对较慢，不能作为交互式设计系统的元件。然而，最近在子图匹配算法方面的突破使新一代形状检索算法的出现成为可能，这些算法与多核硬件相结合，现在足够快，可以支持交互式、预测性设计界面。这项提议旨在调查这样一种假设，即“预测性CAD”系统将允许工程师更有效地设计包含已建立的或标准的、功能或制造几何图形的新部件。这将在大型或分布式的工程组织中找到商业应用。该项目可被视为应用“大数据”来提高设计生产力的一个例子，因为即使是小型工程公司也将拥有数百兆字节的CAD数据，而“预测性CAD”系统将有效地与之进行模式匹配。

Engineering Design work typically consists of reusing, configuring, and assembling of existing components, solutions and knowledge. It has been suggested that more than 75% of design activity comprises reuse of previously existing knowledge. However in spite of the importance of design reuse activities researchers have estimated that 69% of companies have no systematic approaches to preventing the "reinvention of the wheel". The major issue for supporting design re-use is providing solutions that partially re-use previous designs to satisfy new requirements. Although 3D Search technologies that aim to create "a Google for 3D shapes" have been increasing in capability and speed for over a decade they have not found widespread application and have been referred to as "a solution looking for a problem"! This project is motivated by the belief that, with a new type of user interface, 3D search could be the solutions to the design reuse problem.The novel user interface proposed can be best understood in term of an analogy to the text message systems of mobile phones. On mobile phones 'Predictive text' systems complete words or phrases by matching fragments against dictionaries or phrases used in previous messages. Similarly a 'predictive CAD' system would complete 3D models using 'shape search' technology to interactively match partial CAD features against component databases. In this way the system would prompt the users with fragments of 3D components that complete, or extend, geometry added by the user. Such a system could potential increase design productivity by making the reuse of established designs an efficient part of engineering design. Although feature based retrieval of components from databases of 3D components has been demonstrated by many researchers so far the systems reported have been relatively slow and unable to be components of an interactive design system. However recent breakthroughs in sub-graph matching algorithms have enabled the emergence of a new generation of shape retrieval algorithms, which coupled with multi-core hardware, are now fast enough to support interactive, predictive design interfaces. This proposal aims to investigate the hypothesis that a "Predictive CAD" system would allow engineers to more effectively design new components that incorporate established, or standard, functional or manufacturing geometries. This would find commercial applications within large or distributed engineering organizations.This project can be regarded as an example of "big data" being employed to increase design productivity because even small engineering companies will have many hundreds of megabytes of CAD data that a "Predictive CAD" system would effectively pattern match against.