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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717987
• 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.

添加剂制造（AM），（即3维（3D）打印）是一种先进的制造技术，该技术旨在到2030年到2030年彻底改变全球制造业的行业。AM能够具有出色的机械性能的复杂形状制造，并且由于过去十年中的指数进步，有望超越较低的体积型原型制作，使其成为质地的质量质量，并具有较低的产品范围。 拟议的研究计划旨在推进激光粉末床融合（LPBF），即AM类，其中扫描激光选择性地融化了材料床上的粉末颗粒。由于其多功能性和灵活性，该技术对行业非常有吸引力。但是，存在重大挑战，例如存在复杂的管理物理学，超过100多个独立的过程参数，从监视设备流出的非常大的数据集以及文献中缺乏有关质量保证算法的信息。像所有常规制造技术一样，质量保证程序/工具对于协助制造商的质量管理和AM制造零件认证至关重要。这代表了AM研发中的关键差距，并且是宽度采用的瓶颈。 我对AM研究的长期愿景涵盖了可靠的监控，高速质量保证和闭环实时控制系统的LPBF的开发，可用于建立“认证 - 建造”策略。为此，拟议的研究计划将为LPBF开发创新的质量保证平台；不仅是为了应对LPBF中的现有挑战，而且还通过通过加速AM技术在连续生产中采用的整体方法来促进变革性研究。它还将促进对研究人员的世界一流培训，增强其AM多学科领域所需的理论和实用工程技能。 该提案的短期目标是：i）发展高保真，高速分析/实验模型； ii）增强高级连续和过程间歇性监测功能以表征过程签名； iii）制定基于智能的抽样策略，以从大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，将信号输出与实际缺陷相关联； v）开发高级连续和过程期限控制器，以补偿多孔缺陷，分层和残余压力等缺陷。 这项变革性研究将大大提高加拿大在高级制造技术的尖端领域的竞争力和创新能力。采用AM进入其业务计划/产品的工业需求是全球性的和紧迫的，因此拟议的计划具有强大的潜力，可以为国内和出口市场提供新的前沿技术。