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

加法制造或3D打印被誉为第三次工业革命，因为它改变了产品构思、设计、制造和分配给最终用户的独特方式。这一研究项目解决了目前阻碍在工业相关规模上生产添加制造产品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部件组装成最终产品相关的制造限制和挑战，更好地设计将通过添加制造生产的产品。这项研究将产生快速算法，用于生成和选择设计概念，这些概念具有覆盖所有功能要求所需的最少部件数量，并满足添加制造工艺施加的约束。这将促进3D打印产品的大批量生产，从而进一步提高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)和罗彻斯特理工学院(RIT)的共同努力，跨越了几个学科。该项目将通过将这项研究的成果引入现有课程，加强两所参与大学与添加剂制造设计有关的课程。外展活动将通过与亚利桑那大学精通技术计划合作组织的针对K-12学生的讲习班，促进招募妇女和少数族裔进入先进制造业。研究界将通过一次关于基于决策的设计的计算效率方法的道路测绘讲习班参与其中。这项研究的目的是定义一个规定的理论框架和实用方法，用于分类和生成可通过加法制造有效实现的物理集成设计概念。该框架基于功能需求无关性原则，将物理集成问题建模为图着色问题。这项研究将产生新的、计算效率高的(多项式时间)图着色算法，该算法基于放电技术和组合零点。新的算法和设计框架将在典型的设计问题上进行演示和评估，最终的设计将通过加法制造实现。将考虑制造生产率措施，如表面粗糙度、组装时间和成本。

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.