Adaptive Machining of Carbon Fiber Reinforced Composites Informed by Prior Manufacturing Processes

该项目的目标是开发具有自适应工艺参数的碳纤维增强聚合物（CFRP）部件智能加工的合作研究。切边和钻孔等机加工操作用于实现CFRP部件的最终几何形状和表面。然而，在加工之前的CFRP制造链中的工艺不确定性导致其机械性能的显著变化。提出的自适应加工策略将考虑由于先前的制造工艺的CFRP属性的不确定性，从而实现最佳的加工性能。 制造业占加拿大国内生产总值的10%以上（1740亿美元），占所有商品出口的68%以上，并维持着170万个全职工作岗位。航空航天工业是加拿大应用先进制造技术的经济支柱。制造碳纤维基复合材料是促进加拿大航空航天和国防工业的关键技术之一。该项目旨在解决复合材料制造所面临的关键挑战，其研究成果有望使加拿大的航空航天制造业受益，并进一步提高其经济增长和在先进制造业，航空航天和国防领域的全球领导地位。 这项合作是在不列颠哥伦比亚大学和华盛顿大学（UW）的研究小组之间进行的，其专业知识相互补充。UW复合材料集团是复合材料制造研究的全球领导者，拥有波音等公司的强大工业支持。具体而言，拟议的研究将产生新的知识，以了解CFRP的机械性能变化如何定量影响加工中的材料去除机制和表面生成。将采用基于物理学的建模和机器学习综合方法。实际上，一个最佳的加工工艺规划策略，包括加工路径，工艺参数和刀具将开发，以实现一个有效的过程和提高零件质量。

The objective of this project is to develop collaborative research on smart machining of carbon fiber reinforced polymer (CFRP) components with adaptive process parameters. Machining operations such as edge trimming and hole drilling are used to achieve the final geometry and surface of the CFRP components. However, the process uncertainties in the manufacturing chain of CFRP prior to machining cause substantial variations in its mechanical property. The proposed adaptive machining strategy will consider the CFRP property uncertainties due to prior manufacturing processes, therefore achieving the optimum machining performance. Manufacturing represents more than 10% ($174B) of Canada's total GDP, more than 68% of all merchandise exports, and sustains 1.7M full-time jobs. The aerospace industry is a pillar of Canada's economy in applying advanced manufacturing technology. Manufacturing carbon fiber-based composites is one of the key enabling technologies to boost Canada's aerospace and defense industries. This project is proposed to address the critical challenges faced in composites manufacturing, with the research outcome expected to benefit the aerospace manufacturing industry in Canada, and further enhance its economic growth and global leadership in advanced manufacturing, aerospace, and defense. This collaboration is between the research groups at UBC and University of Washington (UW) with the expertise complementing each other. The UW Composites Group is a global leader in composite manufacturing research with strong industrial support from Boeing etc. Specifically, the proposed research will generate new knowledge to understand how the mechanical property variation in CFRP quantitatively influences the material removal mechanism and surface generation in machining. An integrated physics-based modeling and machine learning approach will be implemented. Practically, an optimum machining process planning strategy including the machining path, process parameters, and tooling will be developed to achieve an efficient process and enhanced part quality.