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", and 3) 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).
