CM/Collaborative Research: A Computational Approach to Customizing Design

创建物理事物，包括形状和结构，网络机械设备以及其他功能性工件和机器，是一个费力且经常出错的过程，通常仅限于领域专家和工程师。通常，制造专家与设备设计师不同，导致知识和能力差距，使得最终用户很难（如果不是不可能）创建定制产品。尽管如此，在许多应用领域（包括例如医疗保健、运动装备、家具和车辆）的产品设计中需要定制和个性化。该项目将研究算法，方法和工具，以允许临时最终用户利用工程专家的知识，轻松有效地为定制对象创建经过验证和可验证的可制造设计。该项目将通过软件和设计作品吸引K-12学校和社区大学的学生，妇女和少数民族，从而促进和激励STEM教育。该项目将开发一个完整的计算管道，使设计和制造参数化的对象，可以定制和实例化的非专家。 更具体地说，给定一个参数化的计算机辅助设计（CAD）模型，研究人员将开发转换方法，将其转换为具有少量直观参数的可定制数字模型。该框架还将提供将这些数字模型组合成新模型的机制。给定所需的参数值，每个模型将被转换为制造过程及其数字指令。为此，将探讨一些基本问题，包括：（1）用于可定制的、可制造的数字模型的一般表示，（2）用于将标准参数CAD模型转换成这些新表示的转换过程，（3）能够将这些数字模型组合成新模型的方法，以及（4）将新的数字模型转换为驱动特定制造机器的数字指令的计算后端。

Creating physical things,including shapes and structures, cyber-mechanical devices, and other functional artifacts and machines, is a laborious and often error-prone process, typically limited to domain experts and engineers. Often the manufacturing expert is distinct from the device designer, leading to a knowledge and ability gap that makes it difficult if not impossible for end users to create custom products. Nonetheless, there is a need for customization and personalization in product design across many application spaces, including, for example, healthcare, sports gear, furniture, and vehicles. This project will investigate algorithms, methods, and tools to allow casual end-users to leverage the knowledge of engineering experts to easily and effectively create validated and verifiable manufacturable designs for custom objects. The project will engage students in K-12 schools and community colleges, women, and minorities through the software and design artifacts, thus promoting and inspiring STEM education. This project will develop a complete computational pipeline to enable designing and manufacturing parameterized objects that can be customized and instantiated by non-experts. More specifically, given a parametric Computer Aided Design (CAD) model, the investigators will develop translation methods that convert it to a customizable digital model with a small number of intuitive parameters. The framework will also provide mechanisms to compose these digital models into new ones. Given desired parameter values, each model will be translated to a manufacturing process and its digital instructions. To this end, a number of fundamental questions will be addressed including: (1) general representations for customizable, manufacturable digital models, (2) translation processes for converting standard parametric CAD models to these new representations, (3) methods that enable composition of these digital models into new ones, and (4) computational backends that translate the new digital models into digital instructions that drive specific manufacturing machines.