MRI: Acquisition of An Automated Assembly System and RFID Equipment for Research and Education in Advanced Manufacturing

MRI：采购自动装配系统和 RFID 设备，用于先进制造的研究和教育

• 批准号: 0722923
• 负责人: Can Saygin
• 金额: $ 37.45万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0722923&HistoricalAwards=false
• 关键词: MRI; Acquisition; Automated; Assembly; System

Integration of radio frequency identification (RFID) technologies and advanced sensing capabilities provides a potential to establish a data-rich manufacturing environment, which can be exploited to improve manufacturing system performance via enhanced decision-making. Existing production control methods, based on centralized decision-making, are not suitable for effective utilization of such voluminous data coming in real-time from RFID tags and other sensors on the shop floor. In this project, we will explore novel control architectures that capture the real-time data, facilitate intelligent decision-making, and communicate the decisions for timely execution on the shop floor. In this project, a test-bed that integrates flexible manufacturing systems with RFID technologies and other sensors will be designed and developed. Furthermore, the test-bed will be integrated with simulation platforms in order to facilitate hardware-in-the-loop simulation. Such a test-bed will allow for real-time interaction of simulation models with actual production equipment and controllers in order to scale up applications that range from shop floor to supply chain level so that realistic solutions can be investigated.This project aims to achieve the following by utilizing the capabilities of the test-bed:1) Research investigate decentralized control architectures and decision-making models driven by shop floor level real-time data for dynamic monitoring and allocation of resources and parts across the supply chain.2) Research Training provide a stimulating and flexible environment for both undergraduate and graduate students to undertake research challenges in advanced manufacturing areas, such as manufacturing system control, real-time routing of parts, asset management, and industrial controllers. 3) Education facilitate hands-on experience for students in undergraduate and graduate courses that are crucial to the new Manufacturing and Enterprise Engineering curricula at the University of Texas at San Antonio (UTSA).The fundamental uniqueness of this proposal stems from three factors:1) A holistic approach as opposed to traditional, myopic RFID implementations,2) A scaleable modeling approach "Hardware-in-the-loop Simulation", and3) Integration of shop floor with supply chain.This project contributes significantly to the competitiveness of US manufacturing industries and its objectives fit well with the vision of the Department of Defense and the Army Research Office from the standpoint of distributed, network-centric systems. Effective and timely decision-making is the most important factor in order to sustain competitiveness in manufacturing. This project aims to integrate RFID technology with a suite of industry-grade controllers and to develop decision making schemes that involve an effective blend of RFID data and other manufacturing data for effective and timely decision making. In addition, this project includes supply chain level business processes integrated with shop floor level operations so that the impact of sensor data (RFID and other sensing technologies) not only on the shop floor but also supply chain level can be investigated. In addition, this project is an important contribution to UTSA's mission to launch new manufacturing programs in Manufacturing and Enterprise Engineering and to establish the Center for Advanced Manufacturing and Lean Systems (CAMLS).

射频识别（RFID）技术和先进的传感能力的集成提供了建立一个数据丰富的制造环境，可以利用它来提高制造系统的性能，通过增强决策的潜力。 现有的基于集中决策的生产控制方法不适合于有效利用来自RFID标签和车间上的其他传感器的实时大量数据。 在这个项目中，我们将探索新的控制架构，捕获实时数据，促进智能决策，并传达决策，以便在车间及时执行。 在这个项目中，将设计和开发一个将RFID技术和其他传感器集成到柔性制造系统中的试验台。 此外，试验台将与仿真平台集成，以便于硬件在环仿真。 该试验台将允许模拟模型与实际生产设备和控制器进行实时交互，以便扩大从车间到供应链级别的应用范围，从而可以研究现实的解决方案。该项目旨在通过利用试验台的功能实现以下目标：1）研究由车间级真实的驱动的分散控制体系结构和决策模型。时间数据，用于动态监控和分配整个供应链的资源和零件。2）研究培训为本科生和研究生提供了一个激励和灵活的环境，以承担先进制造领域的研究挑战，如制造系统控制，零件的实时路由、资产管理和工业控制器。 3)教育促进学生在本科和研究生课程的实践经验，这是至关重要的新的制造业和企业工程课程在德克萨斯大学圣安东尼奥（UTSA）。该提案的基本独特性源于三个因素：1）与传统的、短视的RFID实现相反的整体方法，2）可缩放的建模方法“硬件在环仿真”，（3）车间与供应链的整合。该项目对美国制造业的竞争力做出了重大贡献，其目标与愿景非常吻合国防部和陆军研究办公室的分布式，网络中心系统的立场。 有效和及时的决策是维持制造业竞争力的最重要因素。 该项目旨在将RFID技术与一套工业级控制器相结合，并开发决策方案，该方案涉及RFID数据和其他制造数据的有效混合，以实现有效和及时的决策。 此外，该项目还将供应链层面的业务流程与车间层面的运营相结合，以便不仅可以调查传感器数据（RFID和其他传感技术）对车间的影响，还可以调查供应链层面的影响。 此外，该项目是对UTSA的使命的重要贡献，该使命是在制造和企业工程领域推出新的制造项目，并建立先进制造和精益系统中心（CAMLS）。