GOALI: Improved Tool-Path Design to Reduce Assembly Costs of High-Speed-Machined Wrought and Additive Metal Parts

这一学术与工业联系机会(GOALI)项目提供了必要的基础研究，以显著提高飞机生产中使用的铝部件的质量。这些高价值的零件是通过在高速铣床上将大块铝切割出复杂形状而制成的。由于所有部件在组装成飞机时都需要完美地配合，因此它们具有非常精确的尺寸是至关重要的。当部件无法正确组装时，航空航天行业会因为返工和报废而导致严重的延误和成本超支。此外，对更精密零件的需求给制造它们的机械厂带来了巨大的技术和经济负担。因此，本研究项目旨在创造新的高速加工技术，以改善零件质量，提高生产率，减少材料损失。除了帮助航空航天行业，美国的机械厂也将从该项目中受益，因为他们目前在制造飞机零部件时面临着代价高昂的反复试验。因此，这个项目直接有助于经济福利和国家安全，因为航空航天和机械加工行业与这两个行业都有很强的联系。这项研究的知识还将有助于刺激具有竞争力的新制造业，例如3D打印金属部件的加工。不同学生(包括一名残疾退伍军人)的参与以及工程教育对患有自闭症的青少年的影响，将带来有价值的教育和社会影响。研究目标是调查锻造和添加制造的铝合金中的初始残余应力分布，以及这些知识如何导致新的刀轨设计，从而改善高速加工零件的尺寸公差。该技术方法包括结合逆柯西应力预测、机械加工引起的残余应力建模和残余应力测量，以确定初始残余应力是否导致整体铝件的尺寸变形的程度大于综合的热、磨损和机械加工效应。特征丰富的整体零件的裂纹顺应性测试、中子衍射和高密度点云几何图形将被用来识别加工前经常存在于变形铝材料中的残余应力模式。残馀应力的知识将被用来为高速加工过程设计新的应力补偿刀轨。这项研究的贡献包括：关于高速加工过程中残余应力模式及其对几何偏差的影响的知识；将逆应力预测与实验测量相结合以将残余应力表征为随机场的新的统计推断技术；以及设计新的应力补偿的随机机床轨迹的方法。除了在改善高速加工操作方面的重要性外，开发的研究技术还将在新兴的混合(加法/减法)制造工艺上进行测试。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Grant Opportunity for Academic Liaison with Industry (GOALI) project provides the fundamental research needed to significantly improve the quality of aluminum parts used in aircraft production. These high-value parts are made by cutting complex shapes out of large blocks of aluminum on high-speed milling machines. Because all parts need to fit perfectly when assembled into an aircraft, it is critical that they have very precise dimensions. When parts fail to assemble correctly, significant delays and cost overruns are incurred by the aerospace industry because of re-work and scrap. Furthermore, the demand for more precise parts creates significant technical and economic burdens on the machine shops that make them. Therefore, this research project aims to create new high-speed machining techniques that improve part quality, raise production rates, and reduce material losses. In addition to helping the aerospace industry, machine shops in the United States will benefit from the project as they currently face costly trial-and-error when manufacturing aircraft parts. As such, this project directly aids in economic welfare and national security, since the aerospace and machining industries are strongly tied to both. Knowledge from the research will also help spur competitive new manufacturing, such as the machining of 3D-printed metal parts. The participation of diverse students in this project (including a disabled veteran) as well as the exposure of engineering education to teens with autism, will provide for valuable educational and societal impacts.The research goal is to investigate initial residual stress distributions in wrought and additively manufactured aluminum alloys, and how this knowledge can lead to new tool-path designs that improve dimensional tolerances for high-speed-machined parts. The technical approach involves combining inverse Cauchy stress prediction, machining-induced residual stress modeling, and residual stress measurements to determine whether initial residual stresses cause dimensional distortions in monolithic aluminum parts to a greater extent than the aggregated thermal, wear, and machining effects. Crack compliance tests, neutron diffraction, and high-density point-cloud geometry mapping of feature-rich monolithic parts will be used to identify residual stress patterns that regularly exist in wrought aluminum materials prior to machining. Knowledge of the residual stresses will be used to design new stress-compensated tool-paths for high-speed machining processes. Contributions of the research include: knowledge regarding residual stress patterns and their effect on geometric deviations during high-speed machining; new statistical inference techniques that combine inverse stress predictions with experimental measurements to characterize residual stresses as random fields; and methods to design new stress-compensated stochastic machine tool-path trajectories. Besides their significance in improving high-speed-machining operations, the developed research techniques will also be tested on emerging hybrid (additive/subtractive) manufacturing processes.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.