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.

该 I-Corps 项目更广泛的影响/商业潜力是增材制造 (AM) 工程软件技术的开发。 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。它提供了一种方法来全面评估组件的打印准备情况，并自信地识别哪些组件可以使用增材制造工艺可靠地制造。此类评估可以显着减少错误和打印失败，避免昂贵的试错练习，并消除手动评估过程中产生的偏见和不一致。此外，所提出的技术可帮助设计师和制造商快速将有问题的现有组件几何形状转化为成功的 3D 打印设计，从而避免从头开始设计用于增材制造制造的新组件。所提出的技术通过将智能和自动化引入所需的评估中，为处理大批量生产的行业带来价值，以节省大量能源、计算和财务资源。该 I-Corps 项目基于集成的工程软件技术的开发用于增材制造（AM）的多个智能评估和重新设计推荐系统。 尽管众多行业越来越多地实施增材制造，但增材制造对于许多零部件来说并不是一种可行的制造方法，实施不当可能会导致资源浪费和产品故障。当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多个技术和经济角度监控部件的设计准备情况。该系统使用计算方法，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。 拟议的增材制造技术提供了一个全自动校正系统，可以纠正有问题的组件的几何形状，从而实现即时增材制造兼容性。所提出的重新设计解决方案还可以通过最少的用户迭代和不同的增材制造技术为 3D 打印组件提供成功的几何形状。此外，所提出的技术提出了一个设计推荐系统，该系统使用机器学习技术智能分析与增材制造密切相关的组件的广泛数据库，并为当前几何形状增材制造不可行的组件集群提供有效的重新设计建议。该奖项反映了 NSF 的法定使命通过使用基金会的智力优点和更广泛的影响审查标准进行评估，并被认为值得支持。