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.

增材制造允许创建高度定制和个性化的产品，然而，这一优势也为检查和鉴定零件带来了挑战。与传统的大规模制造相比，增材制造不允许破坏性测试，并且由于零件之间的固有差异，它很难适应统计过程控制方法。额外的、不正确的或缺失的材料放置可能导致部件不具备所需的机械完整性、性能和可靠性。最终，这种产量损失限制了增材制造的优势，导致浪费以及生产成本和时间的增加。这个学生项目旨在克服这个问题，通过使用计算机控制的混合3D打印技术实现无缺陷生产，该技术结合了添加剂沉积和减法工艺。实时监控过程将允许在创建层时识别缺陷。然后，该层可以通过减法操作进行再加工，并在正确的处理条件下进行再沉积。由于生产工程陶瓷的潜在广泛受益者和挑战，该学生奖学金将专注于这一应用领域。 本研究的目的是：1）检查不同的成像技术，以确定每层的最佳检查方法。2)使用图像分析方法来量化缺陷。3)开发机器学习以改进定制零件的缺陷识别。4)生成允许对特定层进行返工的刀具路径规划操作。5)展示无缺陷陶瓷部件的生产。