NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving from Evolution to Revolution (ERC-HAMMER)

NSF 混合自主制造工程研究中心从进化到革命 (ERC-HAMMER)

• 批准号: 2133630
• 负责人: Glenn Daehn
• 金额: $ 2593.84万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2133630&HistoricalAwards=false
• 关键词: NSF; Engineering; Research; Center; Hybrid

The Engineering Research Center, Hybrid Autonomous Manufacturing, Moving from Evolution to Revolution (HAMMER), will advance national goals to assert American leadership in advanced manufacturing by developing and transitioning new manufacturing technologies to industry use. Simultaneously, the Center will drive new technical education and provide credentials that will prepare, upskill, or reskill the relevant workforce, and expand capabilities across the manufacturing supply chain to meet national needs. Core partners of the Center include The Ohio State University, Northwestern University, North Carolina Agricultural and Technical State University, Case Western Reserve University, and the University of Tennessee. They will work with collaborators from more than 70 industries, educational, and technical organizations to develop and implement new manufacturing technologies for agile, high-performance and quality-assured components. Through basic, applied, and translational research, HAMMER will accelerate the development and deployment of intelligent autonomous manufacturing systems that will use multiple processes to control material properties and component dimensions to allow rapid customization and high assured performance. These systems will learn from each operation, improving themselves over time. Importantly, as HAMMER works to develop a new class of engineers and technicians, it will also actively work to enhance diversity in the manufacturing talent pipeline, building on the evidence-based success of Fab Labs and Makerspaces to attract students and improve outcomes. Special emphasis will be focused on including urban, military, and Appalachian communities in educational pipeline programs. Ultimately, HAMMER will ensure this country’s competitive advantage, rebuild the U.S. industrial base, create new high-skilled, highly paid jobs, and unleash American ingenuity by providing cost-effective, local, customized production. HAMMER’s primary goal is to enable the concurrent design of products with novel manufacturing processes using hybrid (or multi-tool) manufacturing systems and pathways. This approach will automate and greatly extend the flexibility and ingenuity of practicing human artisans. The HAMMER framework will use designs that will enable leveraging recent developments in robotics and sensors, leading to novel convergent processes. New control, autonomy, and intelligence approaches will guide, and learn from prior manufacturing processes. Quality will be assured through understanding and predicting the local structure and properties of the material being processed within quantified uncertainty limits. Ultimately, HAMMER will advance the current state of technology to unite design, tools, artificial intelligence and computational materials engineering into a single framework, enabling the agile production of components. These components will possess locally optimized materials chemistry, microstructure, and properties in ways that are not attainable currently. The relevant systems are expected to improve in efficiency and performance with experience. Specific use cases to be considered include: 1) numerically controlled deformation sequences and equipment to create complex components that may be currently produced as closed die forgings, but with reduced lead-time and improved performance, 2) employing numerically-controlled deformation to locally optimize properties in additively manufactured components, 3) expanding capabilities for point-of-care manufacturing wherein automated operations including deformation are used to rapidly tailor medical devices to the patient anatomy, and 4) developing low-cost, desktop training systems that provide students hands-on learning in programming, operating, and maintaining new manufacturing systems, as well as experiences creating new physical products using incremental deformation and hybrid processes. Strong partnerships with industry, educational and technical organizations will enable HAMMER to train personnel at many levels from pre-college to practicing engineers. HAMMER will lead next-generation certification standards to facilitate widespread adoption of these technologies by the associated workforce.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

混合自主制造工程研究中心，从进化走向革命(HAMR)，将通过开发新的制造技术并将其转化为工业应用，推进美国在先进制造业中的领导地位的国家目标。同时，该中心将推动新的技术教育，并提供证书，以准备、提高技能或重新技能相关的劳动力，并扩大整个制造供应链的能力，以满足国家需求。该中心的核心合作伙伴包括俄亥俄州立大学、西北大学、北卡罗来纳农业技术州立大学、凯斯西储大学和田纳西大学。他们将与来自70多个行业、教育和技术组织的合作者合作，为敏捷、高性能和质量保证的组件开发和实施新的制造技术。通过基础、应用和翻译研究，HAMMER将加快智能自主制造系统的开发和部署，该系统将使用多个工艺来控制材料属性和部件尺寸，以实现快速定制和高保证的性能。这些系统将从每一次操作中学习，随着时间的推移不断改进自己。重要的是，随着HAMMER致力于培养一批新的工程师和技术人员，它还将积极致力于增强制造业人才管道的多样性，建立在FAB实验室和MakerSpace的循证成功的基础上，以吸引学生和改善结果。将特别强调将城市、军事和阿巴拉契亚社区纳入教育管道计划。最终，锤子将确保美国的竞争优势，重建美国的工业基础，创造新的高技能、高薪工作岗位，并通过提供具有成本效益的、本地化的定制生产来释放美国的创造力。HAMMER的主要目标是使用混合(或多工具)制造系统和路径，实现具有新制造工艺的产品的并行设计。这种方法将自动化并极大地扩展实践人类工匠的灵活性和独创性。HAMMER框架将使用能够利用机器人学和传感器最新发展的设计，导致新的融合过程。新的控制、自主和智能方法将指导以前的制造工艺，并从中学习。通过在量化的不确定范围内了解和预测被加工材料的局部结构和性能，质量将得到保证。最终，HAMMER将推进当前的技术水平，将设计、工具、人工智能和计算材料工程统一到一个单一框架中，从而实现零部件的敏捷生产。这些部件将以目前无法实现的方式拥有局部优化的材料化学、微观结构和性能。随着经验的积累，相关系统有望在效率和性能方面有所提高。要考虑的具体使用案例包括：1)数控变形序列和设备，以创建目前可作为闭合模具锻件生产的复杂部件，但缩短了交货期并提高了性能；2)采用数控变形以局部优化附加制造的部件的性能；3)扩展护理点制造的能力，其中包括变形在内的自动化操作用于根据患者的解剖快速定制医疗设备；以及4)开发低成本的桌面培训系统，为学生提供编程、操作和维护新制造系统的动手学习，以及使用增量变形和混合工艺创建新物理产品的经验。与工业、教育和技术组织的牢固合作关系将使HAMMER能够在从大学预科到实习工程师的多个层面上培训人员。哈默将领导下一代认证标准，以促进相关工作人员广泛采用这些技术。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Robot forming: Automated English wheel as an avenue for flexibility and repeatability

机器人成型：自动化英式轮作为灵活性和可重复性的途径

• DOI: 10.1016/j.mfglet.2023.08.104
• 发表时间: 2023
• 期刊: Manufacturing Letters
• 影响因子: 3.9
• 作者: Huang, Dean;Suarez, Derick;Kang, Putong;Ehmann, Kornel;Cao, Jian
• 通讯作者: Cao, Jian

A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems

• DOI: 10.1007/s40192-022-00280-5
• 发表时间: 2022-10-31
• 期刊: INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
• 影响因子: 3.3
• 作者: Casukhela, Rohan;Vijayan, Sriram;Niezgoda, Stephen R.
• 通讯作者: Niezgoda, Stephen R.

Error homogenization in physics-informed neural networks for modeling in manufacturing

• DOI: 10.1016/j.jmsy.2023.09.013
• 发表时间: 2023-12
• 期刊: Journal of Manufacturing Systems
• 影响因子: 12.1
• 作者: Clayton Cooper;Jianjing Zhang;R. X. Gao

Hybrid manufacturing by additive friction stir deposition, metrology, CNC machining, and microstructure analysis

通过增材搅拌摩擦沉积、计量、数控加工和微观结构分析进行混合制造

• DOI: 10.1016/j.mfglet.2023.08.021
• 发表时间: 2023
• 期刊: Manufacturing Letters
• 影响因子: 3.9
• 作者: Kincaid, Joshua;Zameroski, Ross;Charles, Elijah;No, Timothy;Bohling, John;Compton, Brett;Schmitz, Tony
• 通讯作者: Schmitz, Tony

Limited-constraint WAAM fixture for hybrid manufacturing

用于混合制造的有限约束 WAAM 夹具

• DOI: 10.1016/j.mfglet.2023.08.139
• 发表时间: 2023
• 期刊: Manufacturing Letters
• 影响因子: 3.9
• 作者: West, Justin;Betters, Emma;Schmitz, Tony
• 通讯作者: Schmitz, Tony