Towards In-Situ Qualification of Additively Manufactured Parts: Real Time Monitoring and Intelligent Intermittent Control of Laser Powder-Bed Fusion Additive Manufacturing

迈向增材制造零件的现场鉴定：激光粉末床熔融增材制造的实时监控和智能间歇控制

• 批准号: RGPIN-2020-06306
• 负责人: Toyserkani, Ehsan
• 金额: $ 4.01万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760446
• 关键词: Towards; Situ; Qualification; Additively; Manufactured

Additive manufacturing (AM), (i.e., 3-dimensional (3D) printing), is an advanced manufacturing technology slated to revolutionize the global manufacturing industry by 2030. AM enables the manufacturing of complex shapes with superior mechanical properties and, owing to exponential advancements in the last decade, promises to move beyond low volume prototyping towards becoming a legitimate serial and mass production platform. The proposed research program aims to advance laser powder-bed fusion (LPBF), a class of AM, in which a scanning laser selectively melts powder particles on a material bed. This technology is extremely attractive for industry due to its versatility and flexibility. However, significant challenges exist such as the existence of complex governing physics, more than 100 independent process parameters, very large data sets streaming from monitoring devices, and a lack of information on quality assurance algorithms in the literature. Like all conventional manufacturing techniques, quality assurance procedures/tools are paramount to aiding manufacturers in the quality management and certification of AM-made parts. This represents a critical gap in AM research and development and is a bottleneck for widespread adoption. My long-term vision for AM research encompasses development of reliable monitoring, high-speed quality assurance, and closed-loop real-time control systems for LPBF that can be used towards establishing a "Certify-as-you-build" strategy. To this end, the proposed research program will develop an innovative quality assurance platform for LPBF; not only to address the existing challenges in LPBF, but also to foster transformative research through a holistic approach that accelerates AM technology adoption in serial production. It will also promote the world-class training of research personnel, enhancing their theoretical and practical engineering skills required for the multidisciplinary area of AM. The short-term objectives of this proposal are: i) Development of high-fidelity, high-speed analytical/experimental models; ii) Enhancement of advanced continuous and process intermittent monitoring capabilities for characterizing process signatures; iii) Development of intelligent based sampling strategies to collect rich data from big data streams; iv) Development of real-time detection algorithms as process estimators to correlate signal outputs to actual defects; and v) Development of advanced continuous and process-intermittent controllers to compensate for defects such as porous defects, delamination, and residual stress. This transformative research will significantly enhance Canada's competitiveness and innovation capacity in this cutting-edge area of advanced manufacturing technology. The industrial need to adopt AM into their business plans/products is global in scale and urgent, thus the proposed program has strong potential to provide new leading-edge technologies for domestic and export markets.

增材制造（AM），（即，3-三维（3D）打印是一种先进的制造技术，预计到2030年将彻底改变全球制造业。AM能够制造具有上级机械性能的复杂形状，并且由于过去十年的指数级进步，有望超越小批量原型制造，成为合法的系列和大规模生产平台。拟议的研究计划旨在推进激光粉末床聚变（LPBF），这是一类AM，其中扫描激光选择性地熔化材料床上的粉末颗粒。该技术由于其多功能性和灵活性而对工业极具吸引力。然而，存在重大的挑战，如存在复杂的管理物理，超过100个独立的过程参数，非常大的数据集流从监控设备，以及缺乏文献中的质量保证算法的信息。与所有传统制造技术一样，质量保证程序/工具对于帮助制造商进行AM制造零件的质量管理和认证至关重要。这代表了AM研究和开发中的一个关键差距，也是广泛采用的瓶颈。我对AM研究的长期愿景包括为LPBF开发可靠的监控、高速质量保证和闭环实时控制系统，这些系统可用于建立“即造即认证”战略。为此，拟议的研究计划将为LPBF开发一个创新的质量保证平台;不仅要解决LPBF现有的挑战，还要通过整体方法促进变革性研究，加速AM技术在批量生产中的采用。它还将促进研究人员的世界级培训，提高他们在AM多学科领域所需的理论和实践工程技能。 这一建议的短期目标是：㈠开发高保真、高速分析/实验模型; ㈡加强先进的连续和过程间歇监测能力，以确定过程特征; ㈢开发基于智能的采样战略，从大量数据流中收集丰富的数据; iv）开发实时检测算法作为过程估计器，以将信号输出与实际缺陷相关联;和v）开发先进的连续和工艺间歇控制器，以补偿诸如多孔缺陷、分层和残余应力的缺陷。这项变革性的研究将大大提高加拿大在先进制造技术这一前沿领域的竞争力和创新能力。工业需要采用增材制造到他们的商业计划/产品是全球规模和紧迫的，因此拟议的计划有很大的潜力，为国内和出口市场提供新的领先技术。