Defect Free Hybrid Additive Manufacturing

无缺陷混合增材制造

• 批准号: 2599010
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2599010
• 关键词: Defect; Free; Hybrid; Additive; Manufacturing

Additive Manufacturing allows the creation of highly customised and personalised products, however, this advantage also creates challenges with inspecting and qualifying parts. Compared with traditional mass manufacturing, additive manufacturing does not allow destructive testing and due to the inherent differences between parts, it struggles to accommodate statistical process control methods. Defects from additional, incorrect or missing material placement can result in parts that do not have the required mechanical integrity, performance and reliability. Ultimately this yield loss restricts the advantages of Additive Manufacturing by causing wastage alongside increased production cost and time. This studentship seeks to overcome this issue to enable defect-free production through the use of computer-controlled hybrid 3D Printing which combines additive deposition and subtracting processes. Monitoring the process in real-time will allow the identification of defects when creating a layer. This layer can then be re-worked through a subtractive operation and redeposited with the correct processing conditions. Due to the potential widespread beneficiaries and challenges with producing engineered ceramics, this studentship will focus on this application area. The objectives of this studentship are: 1) Examination of different imaging techniques to determine the optimal inspection methods per layer. 2) Using image analysis methods to quantify defects. 3) Develop machine learning to improve defect identification for bespoke parts. 4) Generation of toolpath planning operations that allow reworking of a specific layer. 5) Demonstrating the production of defect-free ceramic parts.

添加剂制造允许创建高度定制和个性化的产品，但是，此优势还通过检查和合格零件构成了挑战。与传统的质量制造相比，添加剂制造不允许破坏性测试，并且由于零件之间的固有差异，因此努力适应统计过程控制方法。来自其他，错误或缺失材料放置的缺陷可能会导致没有所需的机械完整性，性能和可靠性的零件。最终，这种收益率损失限制了添加剂制造的优势，从而造成浪费以及增加的生产成本和时间。该学生旨在克服这个问题，以通过使用计算机控制的混合3D打印来实现无缺陷的生产，该打印结合了加性沉积和减去流程。实时监视过程将允许在创建图层时识别缺陷。然后可以通过减法操作重新工作，并通过正确的处理条件重新沉积。由于生产工程陶瓷的广泛受益人和挑战，该学生将着重于该应用领域。 该学生的目标是：1）检查不同成像技术以确定每层最佳检查方法。 2）使用图像分析方法量化缺陷。 3）开发机器学习以改善定制零件的缺陷识别。 4）生成允许重新加工特定层的工具路径计划操作。 5）证明无缺陷陶瓷零件的产生。