FW-HTF-RL/Collaborative Research: The Future of Aviation Inspection: Artificial Intelligence and Mixed Reality as Agents of Transformation

FW-HTF-RL/合作研究:航空检查的未来:人工智能和混合现实作为转型的推动者

基本信息

  • 批准号:
    2326185
  • 负责人:
  • 金额:
    $ 155.84万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-10-01 至 2027-09-30
  • 项目状态:
    未结题

项目摘要

Globally, economies rely on safe air travel; however, with human error accounting for 70% of aircraft accidents, an emphasis needs to be placed on helping those responsible for ensuring the safety and reliability of modern and future aircrafts. Aviation maintenance technicians routinely struggle to keep pace with the needs of the aviation industry as they are impacted by a hazardous work environment, high cognitive load, a complex task, and growing worker shortages, and this struggle is only poised to grow as the need for them is slated to increase in the future. This Future of Work at the Human-Technology Frontier - Research: Large (FW-HTF-RL) award supports a collaborative research project to address this challenge, led by a group of universities, professional organizations and industry partners: Clemson University, Purdue University, Greenville Technical College, SA Technologies, National Center for Autonomous Technologies, Aviation Technician Education Council, ChooseAerospace, Frontier Airlines, AAR, Republic Airways, Atlas Air, Stevens Aerospace, Vericor, AMFA, and Lockheed Martin. The goal of this research project is to merge expertise and technological advancements in Artificial Intelligence (AI) and Extended Reality (XR) technologies to enhance the cognitive capabilities of aviation maintenance technicians during inspection tasks. The central idea is that this augmentation could increase their inspection capabilities, reduce workload, and ultimately reduce the number of aviation accidents caused by maintenance errors. In the long term, these efforts will continuously improve the overall health of both future aviation maintenance technicians and aircraft fleets. Furthermore, while this work has prioritized the immediate exploration of the aviation maintenance sector, similar domains that leverage information-rich tasks, visual inspection, and routine maintenance stand to benefit from the demonstrated technological integrations. This project brings together several disciplines, including Human Factors Engineering, Computer Science, Human-Computer Interaction, Behavioral and Social Science, Economics, and Aviation Maintenance. The investigator team is structured to achieve multiple convergent goals. First, this work leverages human factors, behavioral science, and human-computer interaction disciplines to understand the impacts that merged AI and XR technologies will have on the cognitive process of aviation maintenance technicians and the potential risks associated with the integration of these technologies into this workforce. Second, this research project leverages computer science and human-computer interaction to design and develop novel AI models that perform aircraft inspections and make maintenance recommendations based on information gathered through XR technologies. The research team will help design communication and interaction paradigms so future aviation maintenance technicians can understand and accept these recommendations. Third, the project could provide the breakthrough integration of AI and XR technology within the aviation maintenance field to help aviation maintenance technicians in real time. Finally, this effort continuously synthesizes the results of the other three goals with society and workforce-derived data to quantify the economic feasibility and impact that AI and XR technologies will have on the aviation maintenance domain and adjacent workplace sectors. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote a deeper fundamental understanding of the interdependent human-technology partnership in work contexts by advancing the design of intelligent work technologies that operate in harmony with human workers.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.
在全球范围内,各经济体都依赖于安全的航空旅行;然而,由于人为错误占飞机事故的 70%,因此需要重点帮助那些负责确保现代和未来飞机安全性和可靠性的人员。航空维修技术人员经常难以跟上航空业的需求,因为他们受到危险的工作环境、高认知负荷、复杂的任务和日益严重的工人短缺的影响,而且这种斗争只会随着对航空维修的需求而加剧。未来预计还会增加。人类技术前沿工作的未来 - 研究:大型 (FW-HTF-RL) 奖项支持一项应对这一挑战的合作研究项目,该项目由克莱姆森大学、普渡大学等大学、专业组织和行业合作伙伴领导。 、格林维尔技术学院、SA Technologies、国家自主技术中心、航空技术员教育委员会、ChooseAerospace、边疆航空、AAR、共和航空、阿特拉斯航空、史蒂文斯航空航天、Vericor、AMFA 和洛克希德马丁.该研究项目的目标是融合人工智能(AI)和扩展现实(XR)技术的专业知识和技术进步,以增强航空维修技术人员在检查任务期间的认知能力。 中心思想是,这种增强可以提高他们的检查能力,减少工作量,并最终减少因维护错误引起的航空事故的数量。从长远来看,这些努力将不断改善未来航空维修技术人员和机队的整体健康状况。此外,虽然这项工作优先考虑对航空维修领域的直接探索,但利用信息丰富的任务、目视检查和日常维护的类似领域也将从所展示的技术集成中受益。该项目汇集了多个学科,包括人因工程、计算机科学、人机交互、行为和社会科学、经济学和航空维护。研究人员团队的结构是为了实现多个趋同目标。首先,这项工作利用人为因素、行为科学和人机交互学科来了解人工智能和 XR 技术的融合将对航空维修技术人员的认知过程产生影响,以及将这些技术集成到航空维修技术人员中的潜在风险。劳动力。其次,该研究项目利用计算机科学和人机交互来设计和开发新颖的人工智能模型,这些模型可以执行飞机检查并根据通过 XR 技术收集的信息提出维护建议。研究团队将帮助设计沟通和交互范例,以便未来的航空维修技术人员能够理解并接受这些建议。第三,该项目可以实现人工智能与XR技术在航空维修领域的突破性融合,实时帮助航空维修技术人员。最后,这项工作不断地将其他三个目标的结果与社会和劳动力衍生的数据进行综合,以量化人工智能和 XR 技术对航空维修领域和邻近工作场所部门的经济可行性和影响。该项目由“人类技术前沿跨部门工作的未来”计划资助,旨在通过推进与人类和谐相处的智能工作技术的设计,促进对工作环境中相互依存的人类技术伙伴关系的更深入的基本理解。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值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

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Anand Gramopadhye其他文献

Anand Gramopadhye的其他文献

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{{ truncateString('Anand Gramopadhye', 18)}}的其他基金

The Center for Aviation and Automotive Technological Education using E-Learning: Providing E-learning Resources and Increasing Knowledge about Their Effectiveness
使用电子学习的航空和汽车技术教育中心:提供电子学习资源并增加对其有效性的了解
  • 批准号:
    2033801
  • 财政年份:
    2020
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Continuing Grant
NSF INCLUDES DDLP Statewide Consortium: Supporting Underrepresented Populations in Precalculus by Organizational Redesign toward Engineering Diversity
NSF 包括 DDLP 全州联盟:通过面向工程多样性的组织重新设计,支持初级微积分领域代表性不足的人群
  • 批准号:
    1744497
  • 财政年份:
    2017
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Standard Grant
NSF INCLUDES DDLP Statewide Consortium: Supporting Underrepresented Populations in Precalculus by Organizational Redesign toward Engineering Diversity
NSF 包括 DDLP 全州联盟:通过面向工程多样性的组织重新设计,支持初级微积分领域代表性不足的人群
  • 批准号:
    1744497
  • 财政年份:
    2017
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Standard Grant
A Sustainable ATE Coordination Network for Enhancing Personalized Learning Using Virtual and Augmented Reality-based Technology Innovations in Technician Education
可持续的 ATE 协调网络,利用技术人员教育中基于虚拟和增强现实的技术创新来增强个性化学习
  • 批准号:
    1700621
  • 财政年份:
    2017
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Standard Grant
Center for Aviation and Automotive Technological Education Using Virtual E-School [CA2VES]: A Resource to Meet Technician Workforce Needs
使用虚拟电子学校的航空和汽车技术教育中心 [CA2VES]:满足技术人员劳动力需求的资源
  • 批准号:
    1501695
  • 财政年份:
    2015
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Continuing Grant
Center for Aviation and Automotive Technology Education using Virtual E-School [CA2VES]: A Resource to Meet Technician Workforce Needs
使用虚拟电子学校 [CA2VES] 的航空和汽车技术教育中心:满足技术人员劳动力需求的资源
  • 批准号:
    1104181
  • 财政年份:
    2011
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Continuing Grant
Center for Aviation and Automotive Technology Education using Virtual E-School [CA2VES]: Workforce Preparedness for Automotive and Aviation Technicians
使用虚拟电子学校的航空和汽车技术教育中心 [CA2VES]:汽车和航空技术人员的劳动力准备
  • 批准号:
    0903226
  • 财政年份:
    2009
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Standard Grant
A Hybrid Solution to the Human/Machine Inspection Systems Design Problem in Manufacturing and Service Industries
制造和服务行业中人机检查系统设计问题的混合解决方案
  • 批准号:
    9800817
  • 财政年份:
    1998
  • 资助金额:
    $ 155.84万
  • 项目类别:
    Standard Grant

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