Collaborative Research: Improving Design for Additive Manufacturing through Physically-integrated Design Concepts Generated from Computationally Efficient Graph Coloring Techniques

协作研究：通过计算高效的图形着色技术生成的物理集成设计概念改进增材制造的设计

• 批准号: 1727743
• 负责人: Sogol Jahanbekam
• 金额: $ 16.76万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1727743&HistoricalAwards=false
• 关键词: Collaborative; Research; Improving; Design; Additive

Additive manufacturing or 3D printing has been hailed as the third industrial revolution because of the unique way it changes how products are conceived, designed, manufactured and distributed to end users. This research project addresses key scientific and engineering barriers that currently prevent the production of additively manufactured products at an industrially-relevant scale. In particular, the project focuses on how to better design products that will be produced via additive manufacturing by considering manufacturing constraints and challenges associated with assembling parts into final products. The study will result in fast algorithms for generating and selecting design concepts that have the minimum number of parts required to cover all functional requirements and that meet constraints imposed by the additive manufacturing process. This will facilitate high-volume, mass production of 3D printed products, thereby furthering the practicality and economic impact of additive manufacturing. The project spans several disciplines through a joint effort between the University at Buffalo (UB) and Rochester Institute of Technology (RIT). The project will enhance the curriculum related to design for additive manufacturing at the two participating universities by introducing results from this research into existing courses. Outreach activities will promote the recruitment of women and minorities to advanced manufacturing through workshops aimed at K-12 students organized in partnership with the Tech-Savvy program at UB. The research community will be engaged through a road-mapping workshop on computationally efficient methods in decision-based design. The objective of this research is to define a prescribed theoretical framework and practical methods for classifying and generating physically integrated design concepts that can be realized effectively through additive manufacturing. The framework is based on the independence of functional requirements principle and modeling of physical integration problems as graph coloring problems. The research will result in new, computationally efficient (polynomial-time) graph-coloring algorithms based on discharging techniques in combination with Combinatorial Nullstellensatz. The new algorithms and design framework will be demonstrated and evaluated on representative design problems with the resulting designs being realized through additive manufacturing. Manufacturing productivity measures such as surface roughness, buildup time and cost, will be considered.

增材制造或3D打印被誉为第三次工业革命，因为它改变了产品的设计，设计，制造和分发给最终用户的独特方式。该研究项目涉及目前阻止以工业相关的添加性制造产品生产的关键科学和工程障碍。特别是，该项目的重点是如何通过考虑与将零件组装成最终产品相关的制造约束和挑战来更好地设计将通过添加剂制造生产的产品。这项研究将导致快速算法生成和选择具有涵盖所有功能要求所需零件数量最少的设计概念，并且满足添加剂制造过程施加的约束。这将有助于大量生产3D印刷产品，从而促进添加剂制造的实用性和经济影响。该项目通过布法罗大学（UB）和罗切斯特理工学院（RIT）的联合努力跨越了几个学科。该项目将通过将这项研究的结果引入现有课程中，从而增强与两所参与大学的增材制造设计相关的课程。外展活动将通过针对与UB的精通技术计划合作组织的K-12学生的研讨会来促进妇女和少数民族招募高级制造业。研究社区将通过有关基于决策设计的计算有效方法的公路映射研讨会来参与。这项研究的目的是定义一个规定的理论框架和实用方法，用于分类和生成物理整合的设计概念，这些概念可以通过增材制造有效地实现。该框架基于功能要求原理的独立性和物理整合问题作为图形问题的建模。这项研究将导致基于排放技术与组合无效的nullstellensatz结合使用的新的计算高效（多项式）图形色算法。新算法和设计框架将在代表性设计问题上进行演示和评估，并通过增材制造实现所得设计。将考虑制造生产力措施，例如表面粗糙度，积累时间和成本。