Cold Gas Dynamics Manufacturing Process Development for Smart Parts

智能零件的冷气体动力学制造工艺开发

• 批准号: RGPIN-2017-04671
• 负责人: Jodoin, Bertrand
• 金额: $ 2.7万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=654697
• 关键词: Cold; Gas; Dynamics; Manufacturing; Process

Portrayed as “the next industrial revolution”, additive manufacturing (AM) is transforming consumer product design and manufacturing. AM differs drastically from traditional manufacturing methods (TMM) such as subtractive (milling or drilling), formative (casting or forging) and joining (welding or fastening) processes. ******AM of plastic parts is considered as the state-of-the-art. However, AM of metals and ceramics requires more extensive research and development efforts to expand the scope of applications to structural and high-performance functional parts. Efforts are required to reach maturation of AM as more work is required to understand the process parameters/process output relationships at the fundamental level (process mapping).******In recent years, uOttawa researchers have been instrumental in advancing the engineering science of Cold Gas Dynamic Spray Additive Manufacturing (CGDSAM). CGDSAM is still in its infancy, and can be considered as a (solid state) Material Jetting AM process for metals and cermets. Despite academic consensus that CGDSAM is a strong candidate for the market of large parts that are difficult/expensive to produce by TMM and early proof-of-concept successes, there is a lack of fundamental knowledge on what controls the process output. As such, the process “mapping” is required to allow process evaluation, improvement, transfer and commercial implementation. Furthermore the use of AM offers the potential to produce sensors allowing in-situ monitoring of AM mechanical parts performance. *********Studies have shown that CGDSAM can produce complex shapes of small dimension (mm-size) non-structural parts that are now used commercially. Recent work has focused on CGDSAM of titanium parts due to the large potential market as these are expensive and costly to machine using TMM. Demonstration of the CGDSAM process potential for sensor production has also recently been made.************Based on these recent progresses for potential market niche applications, the long-term objective of this program is to establish the CGDSAM process “map” and allow the production of cm-size titanium alloy parts imbedded with sensors for wireless in-situ performance monitoring of the produced parts. ******The outcome will establish the potential of CGDSAM for titanium alloy part production that don't require extremely fine intricate details and assess its advantage due to the process large throughput (orders of magnitudes beyond current existing AM processes) and the absence of “built tray” typically limiting the size of AM parts.***The positive outcome of this program will also make monitoring/transmission of in-situ performance possible. This could provide crucial feedback on parts performance for maintenance optimisation and failure prevention. It could also provide feedback for designers to allow refined modeling and revision of new designs.

增材制造（AM）被称为“下一次工业革命”，正在改变消费产品的设计和制造。增材制造与传统的制造方法（TMM）有很大的不同，例如减材（铣削或钻孔）、成形（铸造或锻造）和连接（焊接或紧固）工艺。** 塑料零件的增材制造被认为是最先进的。然而，金属和陶瓷的增材制造需要更广泛的研究和开发工作，以将应用范围扩大到结构和高性能功能零件。需要努力实现AM的成熟，因为需要更多的工作来理解基础水平上的过程参数/过程输出关系（过程映射）。**近年来，uOttawa的研究人员一直致力于推进冷气动态喷涂增材制造（CGDSAM）的工程科学。CGDSAM仍处于起步阶段，可以被认为是金属和金属陶瓷的（固态）材料喷射AM工艺。尽管学术界一致认为CGDSAM是TMM难以/昂贵生产的大型零件市场的有力候选者，并且早期概念验证成功，但缺乏关于控制过程输出的基本知识。因此，需要进行工艺“绘图”，以便进行工艺评估、改进、转让和商业实施。 此外，AM的使用提供了生产传感器的可能性，从而允许现场监测AM机械部件的性能。** 研究表明，CGDSAM可以生产目前商业上使用的小尺寸（mm尺寸）非结构零件的复杂形状。最近的工作集中在钛零件的CGDSAM上，因为这些零件的潜在市场很大，因为使用TMM加工成本很高。最近还证明了CGDSAM工艺在传感器生产中的潜力。*基于这些针对潜在市场利基应用的最新进展，该计划的长期目标是建立CGDSAM工艺“地图”，并允许生产嵌入传感器的厘米级钛合金零件，用于对生产的零件进行无线原位性能监测。** 结果将确定CGDSAM用于钛合金零件生产的潜力，这些零件不需要非常精细的复杂细节，并评估其优势，因为该工艺的产量很大（超过当前现有AM工艺的数量级），并且不存在通常限制AM零件尺寸的“构建托盘”。这一方案的积极成果还将使现场性能监测/传输成为可能。这可以为维护优化和故障预防提供有关零件性能的关键反馈。它还可以为设计师提供反馈，以允许改进建模和修改新设计。