Logistics 4.0 Technologies Driven Approaches for Warehouse Operations: A Framework of Resource Management System
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The last several years have seen the evolution of warehouse from stockpiling of inventory to high-velocity operations, allowing facilities to handle as many goods as they typically deal with, but at lower costs. Warehouses as an essential component of the supply chain infrastructure are increasingly not regarded as cost centers any more, but rather as strategic facilities to provide competitive advantages. With the growing demand for reduced labor costs, better quality control, greater order customization, shorter lead times and higher production output, adaptable advanced technologies are needed to achieve these goals. Advances in information and digital technologies can help pave the way for the evolving warehouse, enabling intelligent systems to adapt to their environment and address challenges more efficiently. Technologies such as RFID, low-cost sensors, artificial intelligence, computer vision, autonomous vehicles, Internet of Things (IoT), and high-performance computing—all inherent in Logistics 4.0—are being leveraged to create a more adaptable facility. Meanwhile, they are also enabling new types of smart automation that can help transform warehouse operations. This thesis presents a framework of warehouse resource management system based on Logistics 4.0–driven technologies to enable a more flexible, adaptive, and productive warehouse. The framework consists of three tiers. In the first tier, RFID devices are deployed to capture the warehouse resource data. All the received data is stored in the centralized database. In the second tier, the locations of warehouse resources such as SKUs and forklifts are computed based on the collected data. The third tier is data management which contains two modules, namely route optimization module and motion detection module. The route optimization module is to formulate the shortest route for order picking operations, thus reducing the total traveling time. In doing this, the objectives of maximizing the productivity and enhancing the efficiency of the warehouse operations can be achieved. The motion detection module is responsible for distinguishing the RFID tags which are detected accidentally by the RFID reader but not the ones of interest. Machine learning algorithms are applied to identify such RFID readings.