I-Corps: An Intelligent Re-Design Recommender System for Additive and Hybrid Manufacturing

I-Corps：用于增材和混合制造的智能重新设计推荐系统

• 批准号: 2120516
• 负责人: Kemper Lewis
• 金额: $ 5万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120516&HistoricalAwards=false
• 关键词: Corps; Intelligent; Re; Design; Recommender

The broader impact/commercial potential of this I-Corps project is the development of engineering software technology for additive manufacturing (AM). The proposed technology may be used to help solve some of the significant challenges by implementing a variety of intelligent assessments, re-design strategies, and learning processes. It provides a way to evaluate comprehensively the print-readiness of components and confidently identify which components may reliably be manufactured using AM processes. Such evaluations may significantly reduce mistakes and printing failures, avoid costly trial-and-error exercises, and remove biases and inconsistencies that arise from manual evaluation processes. In addition, the proposed technology assists designers and manufacturers in rapidly converting problematic existing component geometries to successful 3D-printable designs, avoiding the need to design new components for AM fabrication from scratch. The proposed technology presents a value for industries dealing with high-volume production by introducing intelligence and automation into the required assessments to save significant energy, computational, and financial resources.This I-Corps project is based on the development of an engineering software technology integrating multiple intelligent assessment and re-design recommender systems for additive manufacturing (AM). While numerous industries are increasingly implementing AM, AM is not a feasible manufacturing method for many components, and improper implementation may cause resource waste and product failure. The current technology presents a multi-variable algorithm for feasibility evaluation that monitors the design-readiness of components from several technical and economic perspectives before printing the part. Using computational approaches, this system intelligently calculates feasibility scores representing the precise feasibility status of various parts. The proposed AM technology presents a fully automated correction system that rectifies the geometries of problematic components, allowing for immediate AM compatibility. The proposed re-design solutions also may provide successful geometries for 3D-printing components with minimal user-iteration and for different AM techniques. In addition, the proposed technology presents a design recommender system that intelligently analyzes an extensive database of closely related components for AM using machine learning techniques and provides effective re-design recommendations for component clusters whose current geometries are AM infeasible.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目更广泛的影响/商业潜力是开发用于增材制造（AM）的工程软件技术。 所提出的技术可用于通过实施各种智能评估、重新设计策略和学习过程来帮助解决一些重大挑战。它提供了一种全面评估组件打印就绪性的方法，并自信地确定哪些组件可以使用AM工艺可靠地制造。这种评价可以大大减少错误和印刷故障，避免代价高昂的试错做法，并消除人工评价过程中产生的偏见和不一致。此外，所提出的技术有助于设计人员和制造商将有问题的现有组件几何形状快速转换为成功的3D打印设计，从而避免从头开始设计用于AM制造的新组件。该技术通过将智能和自动化引入所需的评估中，为大批量生产的行业提供了价值，从而节省了大量的能源，计算和财务资源。该I-Corps项目基于工程软件技术的开发，该技术集成了多种智能评估和增材制造（AM）的重新设计推荐系统。 虽然许多行业越来越多地实施AM，但AM对于许多组件来说并不是一种可行的制造方法，并且不适当的实施可能会导致资源浪费和产品故障。目前的技术提出了一种用于可行性评估的多变量算法，该算法在打印部件之前从几个技术和经济角度监控部件的设计就绪性。使用计算方法，该系统智能地计算代表各个部件的精确可行性状态的可行性分数。 所提出的AM技术提供了一种全自动校正系统，该系统可以校正有问题组件的几何形状，从而实现即时AM兼容性。所提出的重新设计解决方案还可以以最小的用户迭代和不同的AM技术为3D打印组件提供成功的几何形状。此外，本发明还提供了一种方法，所提出的技术提出了一种设计推荐系统，该系统使用机器学习技术智能地分析用于AM的密切相关的组件的广泛数据库，并提供有效的推荐。对于那些目前的几何形状不符合增材制造要求的部件组群提出设计建议。该奖项反映了美国国家科学基金会的法定使命，并被认为是值得通过利用基金会的知识价值和更广泛的影响评审进行评估来支持的的搜索.