SBIR PHASE I: Manufacturing Workforce - Novice to Expert - Training Program

SBIR 第一阶段：制造劳动力 - 新手到专家 - 培训计划

• 批准号: 0512323
• 负责人: Lester Wilson
• 金额: --
• 依托单位: 3DH CORPORATION
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2005-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0512323&HistoricalAwards=false
• 关键词: SBIR; PHASE; Manufacturing; Workforce; Novice

This Small Business Innovation Research Phase I project is designed to produce a prototype manufacturing workforce training curriculum, enhanced software programs, and methodology that specifically address Composite Design and Product Lifecycle Management (PLM), including more effective use of Catia V5 (an integrated suite of Computer Aided Design (CAD), Computer Aided Engineering (CAE), and Computer Aided Manufacturing (CAM) applications for digital product definition and simulation), by increasing its visualization capabilities, in the assembly of the Boeing 7E7 production workforce. A knowledgeable and resourceful production workforce, not only in aerospace, but also in other manufacturing industries, is essential in order to meet the competitive requirements of a global market. There is a gap between the availability of sophisticated hardware, software, and manufacturing processes and the skills and competence of the workforce who must utilize them. This project, therefore, proposes to empirically demonstrate the value of "cognitive learning", using state-of-the-art 3d holographic technology as a knowledge transfer tool. The research design features two workforce-training cohorts based on a random assignment to control and experimental groups. The control group will receive traditional training and the experimental group will receive the technology-driven "cognitive learning" model curriculum. Competency-based assessments, in addition to trainee pre- and post-knowledge assessments, will demonstrate that the experimental group will progress from "novice" workers to "expert" workers in a dramatically shorter and more effective training process through the use of the "cognitive learning" model. Current and future engineers and technicians in aerospace, automotive, consumer goods, electronics, heavy equipment, biomedical devices and machine tools, will be required to have a level of understanding of a variety of materials and composites and new manufacturing processes. To be competitive, they must have access to a combination of advanced manufacturing and materials education and training to help produce highly-durable goods using less expensive processes while increasing efficiency. That is precisely what the scientifically-based, technology-driven Cognitive Learning" manufacturing workforce training model prototype, when field-tested and documented empirically, will do. Just demonstrating that the prototype works well, and then expanding into the next phase of the research and development to fully verify and expand the model, will open the door to tremendous commercialization opportunities. In summary, manufacturing workforce training will move from the traditional structure of education to a student-focused learning environment that provides for virtual teaming, three-dimensional visualization, critical thinking and real-life scenarios and problem solving for advanced manufacturing.

这个小型企业创新研究第一阶段项目旨在通过提高波音7E7生产劳动力组装的可视化能力，产生专门针对复合设计和产品生命周期管理(PLM)的原型制造劳动力培训课程、增强的软件程序和方法，包括更有效地使用CATIA V5(用于数字产品定义和模拟的计算机辅助设计(CAD)、计算机辅助工程(CAE)和计算机辅助制造(CAM)应用程序的集成套件)。为了满足全球市场的竞争要求，不仅在航空航天，而且在其他制造行业，拥有一支知识渊博和足智多谋的生产劳动力是必不可少的。复杂的硬件、软件和制造流程的可用性与必须使用它们的劳动力的技能和能力之间存在差距。因此，该项目建议使用最先进的3D全息技术作为知识转移工具，从经验上证明“认知学习”的价值。这项研究设计的特点是两个劳动力培训队列，基于随机分配到控制组和试验组。控制组将接受传统培训，试验组将接受技术驱动的“认知学习”模式课程。除了实习生知识前和知识后评估外，基于能力的评估还将表明，试验组将通过使用“认知学习”模式，在大大缩短和更有效的培训过程中，从“新手”工作人员发展为“专家”工作人员。航空航天、汽车、消费品、电子、重型设备、生物医学设备和机床领域的现有和未来工程师和技术人员将被要求对各种材料和复合材料以及新的制造工艺有一定程度的了解。为了具有竞争力，它们必须能够获得先进制造和材料教育和培训的结合，以帮助使用成本较低的工艺生产高度耐用的产品，同时提高效率。这正是基于科学、技术驱动的认知学习的制造业劳动力培训模型原型，当经过现场测试和经验记录时，将会做到这一点。仅仅展示原型运行良好，然后扩展到下一阶段的研发，以充分验证和扩展该模型，将打开巨大的商业化机会的大门。总而言之，制造业劳动力培训将从传统的教育结构转向以学生为中心的学习环境，为先进制造业提供虚拟团队、三维可视化、批判性思维和现实生活场景和问题解决。