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

射频识别(RFID)技术和先进的传感能力的集成提供了建立数据丰富的制造环境的潜力，可以利用该环境通过增强的决策来提高制造系统的性能。现有的基于集中式决策的生产控制方法不适合有效利用来自车间RFID标签和其他传感器的实时海量数据。在这个项目中，我们将探索新的控制体系结构，这些体系结构可以捕获实时数据，促进智能决策，并将决策进行沟通，以便在车间及时执行。在本项目中，将设计和开发一种将柔性制造系统与RFID技术和其他传感器相结合的试验台。此外，试验台将与仿真平台集成，以便于半实物仿真。这样的试验台将允许仿真模型与实际生产设备和控制器的实时交互，以便扩大从车间到供应链级别的应用，从而可以研究现实的解决方案。本项目旨在通过利用试验台的能力实现以下目的：1)研究由车间级实时数据驱动的分散控制体系结构和决策模型，用于动态监控和分配供应链上的资源和部件。2)研究培训为本科生和研究生提供一个激励和灵活的环境，以在先进制造领域进行研究挑战，例如制造系统控制，部件、资产管理和工业控制器的实时布线。3)教育促进了学生在本科生和研究生课程中的实践体验，这些课程对德克萨斯大学圣安东尼奥分校(UTSA)的新制造和企业工程课程至关重要。这一建议的基本独特性来自三个因素：1)相对于传统的、短视的RFID实施，这一建议的基本独特性来自三个因素：1)相对于传统的、短视的RFID实施；2)可扩展的建模方法：硬件在环中模拟；3)车间与供应链的集成。该项目显著提高了美国制造业的竞争力，其目标从分布式、以网络为中心的系统的角度与国防部和陆军研究办公室的愿景非常吻合。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集成在一起，并开发涉及RFID数据和其他制造数据的有效混合的决策方案，以进行有效和及时的决策。此外，该项目包括与车间级操作集成的供应链级业务流程，以便不仅可以调查传感器数据(RFID和其他传感技术)对车间级的影响，还可以调查供应链级的影响。此外，该项目对UTSA在制造和企业工程领域推出新的制造计划以及建立先进制造和精益系统中心(CAMLS)的使命做出了重要贡献。

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).