Presidential Faculty Fellow: Material Processing and Intelligent Manufacturing

校长研究员：材料加工与智能制造

• 批准号: 9350209
• 负责人: John Coulter
• 金额: $ 40万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 1999-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9350209&HistoricalAwards=false
• 关键词: Presidential; Faculty; Fellow; Material; Processing

9350209 Coulter The objective of the reserch and teaching program is to contribute to the return of the United State to a position of world leadership in material processing and manufacturing science technology. This objective will be pursued through the development of an interdisciplinary effort in the area of intelligent material processing and manufacturing. Two fundamental problems associated with U.S. process development today are: (1) the majority of manufacturing processes are not completely understand, and (2) product quality is not monitored and optimally adjusted during fabrication. While initially emphasizing molded or advanced composite products, the effort will address these two basic problems by focusing on three coupled manufacturing science areas. These are: (1) improved process models for molding and advanced composites msnufacturing situations, (2) sensor subsystems for in situ product quality assessment during manufacturing, and (3) knowledge based tools for real time manufacturing processs adapation. In the improved process model area, a software package for the simulation of molding processes that occur during the manufacture of monolithic and advanced composite materials will be improved through a sequence of developmental computational research phases. A concurrent effort will focus on the development of a generic methodology for the utilization of process model information in an inverse manner. This inverse process model utilization will be done in a real time feedback control environment to compensate for the fact that even the best models are rarely perfect. The sensor subsystem component of the program will focus on the developme nt of hardware/software subsystems for monitoring product quality in real time during fabrication cycles. A methodology for determining temporal flow progression and temporal spatial rheology during operations will be developed. Several sensory transducer mechanisms will be investigated, but the initial focus will be on the usage of electronic and optical fiber sensors. The knowledge based process adaptation phase of the program will focus on the need for generic computer based control tools fir implementating real time inverse process model information. The effort will include the use of artifical neural networks, with necessary training information obtained from process simulation models rather than from actual manufacturing datqa. Fundamental research advancement in the three coupled interdisciplinary manufacturing science areas described will help facilitate an improved capability for intelligemt adaptive manufacture of molded and composite products for U. S. military and commercial applications. A parallel teaching effort will be undertaken and directd at educating engineers who are well grounded in scientific fundamentals, capable of crossing traditiiiional disciplinary boundaries, and comfortable in environmentals charqcterized by design oriented, open ended asignments. Students will develop these traits as a result of being exposed to an academic environment that mimics professional situations throughout the education process. The development and improvement of interdisciplinary undergraduate and graduate courses in the arcas h) 0*0*0* of manufacturing science and intelligent material systems will continue. In all cases, student driven learning rather than instructor dominated lecture presentation will be encouraged , as it has been found that such a format increases student enthusiasm and does not constrain the upper level to which subject are explored. All educationL efforts will be carried out with the following simple goal in mind: to identify knowledge that is of critcal importance to our American society and to guide individuals as they apply enjoyable and effiecient techniques to thoroughy acquire this knowledge.

9350209 Coulter 研究和教学计划的目标是帮助美国恢复材料加工和制造科学技术的世界领先地位。 这一目标将通过在智能材料加工和制造领域发展跨学科的努力来实现。 当今与美国工艺开发相关的两个基本问题是：(1) 大多数制造工艺尚未完全理解，(2) 产品质量在制造过程中没有得到监控和优化调整。 虽然最初强调模制或先进复合材料产品，但该工作将通过关注三个耦合的制造科学领域来解决这两个基本问题。 这些是：（1）用于成型和先进复合材料制造情况的改进工艺模型，（2）用于制造过程中现场产品质量评估的传感器子系统，以及（3）用于实时制造工艺适应的基于知识的工具。 在改进的工艺模型领域，用于模拟整体和先进复合材料制造过程中发生的成型工艺的软件包将通过一系列开发计算研究阶段得到改进。 同时进行的工作将集中于开发一种以逆向方式利用过程模型信息的通用方法。 这种逆过程模型的利用将在实时反馈控制环境中完成，以弥补即使是最好的模型也很少是完美的这一事实。 该计划的传感器子系统组件将重点开发用于在制造周期中实时监控产品质量的硬件/软件子系统。 将开发一种确定操作过程中时间流动进程和时间空间流变学的方法。 将研究几种感觉传感器机制，但最初的重点将是电子和光纤传感器的使用。 该程序的基于知识的过程适应阶段将重点关注对用于实现实时逆过程模型信息的通用计算机控制工具的需求。 这项工作将包括使用人工神经网络，并从过程模拟模型而不是从实际制造数据中获得必要的训练信息。 所述三个耦合的跨学科制造科学领域的基础研究进展将有助于提高美国军事和商业应用的模制和复合产品的智能自适应制造能力。 将开展并行教学工作，旨在培养具有良好科学基础、能够跨越传统学科界限、能够适应以设计为导向、开放式任务的环境的工程师。 在整个教育过程中，学生将处于模拟专业情境的学术环境中，从而发展出这些特质。 制造科学和智能材料系统领域h) 0*0*0*跨学科本科生和研究生课程的开发和完善将继续。 在所有情况下，将鼓励学生驱动的学习而不是教师主导的讲座演示，因为已经发现这种形式可以提高学生的热情，并且不会限制探索主题的上层水平。 所有教育工作都将牢记以下简单目标：识别对我们美国社会至关重要的知识，并指导个人应用有趣且有效的技术来彻底获取这些知识。