Inventory management is central to efficient management systems for increased productivity and tracking of resources. Industry 4.0 (I4.0) revolutionises the manufacturing sector by integrating advanced digital technologies like the Internet of Things (IoT), leading to smart factories with enhanced efficiency and flexibility. Inventory management compliments this transformation, particularly if it includes tracking technology and Visual Management Systems (VMS), which convert tracking data into actionable insights, optimising processes and reducing waste. This paper presents a novel application of Radio Frequency Identification (RFID) tracking technology in conjunction with a Business Intelligence (BI) VMS for tracking inventory trolleys within a large-scale aerospace manufacturing environment. An RFID-VMS system including passive RFID cards, a USB hub for remote connection and a Power BI VMS were implemented providing intuitive key performance indicator (KPI) visuals, mobile accessibility and increased production line efficiency by 45%. Missed takt times decreased by 52.2% and line stops decreased by 75% indicating substantial improvements in maintaining the production schedule and reducing interruptions. The prototype implementation cost $600 covering RFID hardware, software, and infrastructure updates. Scaling to a full production line would require an estimated investment of $36,000 with a projected annual waste cost reduction of approximately $2.45 million. The number of blue cards increased by 7.9% reflecting an increase in throughput and production efficiency. As a result, the system supports sustainability by reducing operational waste and optimising inventory management, aligning with UN Sustainable Development Goals (9: Industry, Innovation, and Infrastructure and 12: Responsible Consumption and Production) and promoting economic growth. This simple, yet effective system framework could be applied to a number of sectors where materials must be tracked and recorded into and out of different locations at different intervals.

Traceability and visibility of outbound logistics are crucial for companies aiming to enhance customer satisfaction and ensure product quality and reliability. The Internet of Things (IoT) offers promising solutions by enabling real-time tracking and intelligent decision-making in supply chains. However, processing and interpreting heterogeneous IoT data (sensors, actuators) remain challenging, as timely and accurate information dissemination is required. In this paper, we propose EDSOA-OLP-IoT; novel semantic middleware architecture based on the OLP-IoT ontology and designed to optimize outbound logistics operations. Our approach integrates a service-oriented event-driven architecture with a Publish-Subscribe communication model, complex event processing (CEP), and ontology-based reasoning. Unlike traditional IoT frameworks, our system enhances anomaly detection, improves decision-making accuracy, and optimizes resource management by leveraging semantic reasoning. Through experimental simulations, we demonstrate that EDSOA-OLP-IoT effectively reduces response time to critical events and enhances supply chain efficiency. To validate our approach, we conducted simulations based on real-world-inspired scenarios, including temperature monitoring in refrigerated trucks and warehouses. These scenarios showcase the system’s ability to detect anomalies and trigger appropriate responses, highlighting the potential of semantic reasoning and event-driven architectures for real-time logistics optimization.

The relative position and metal characteristics of electrical equipment in the substation will affect the communication performance of the RFID (Radio Frequency Identification) information acquisition system. Given its environment similar to the tunnel and the multi-metal medium characteristics, a n acquisition system for the state information of electrical equipment in the substation based on the radio frequency identification sensor is proposed, and a channel model of the information acquisition system is established. Also, the factors influencing the performance of the acquisition system for the state information of electrical equipment in the substation are analyzed. The experimental results show that the communication error rate of the radio frequency identification sensor can be reduced by 1∼3 orders of magnitude when the distance between the radio frequency identification sensor and the conventional sensor is less than 80 m. When the communication distance is within 25∼80 m, the vertical arrangement method of radio frequency identification sensors can reduce the bit error rate by 20% ∼40% compared with the horizontal arrangement.

As retailers move from pilot studies to rolling out RFID implementations across their stores, they need to adapt their current processes to the capabilities of this new technology. The main objective of this study is to explore areas in retail operations other than the supply chain that can be adap ted to the capabilities of enhanced visibility by RFID. We develop a system dynamics simulation model for retailers’ floor operations that is based on a Delphi study. Our model explores changes in merchandising processes that improve store operations. More specifically, our simulation model demonstrates how lower inventory holdings and reduced shelf space can result in more variety and assortment of products in stores.

OBJECTIVE: The objective of the paper is twofold: on the one hand, to design a testing protocol to measure performances of RFID devices. The protocol matches operational conditions in supply chain processes and is particularly tailored to the apparel industry. On the other one, the paper strives at benchmarking performances of inlays, fixed and handheld RFID readers, and printers when deployed in the apparel logistics and retail processes. DESIGN, METHODOLOGY, APPROACH: We developed a testing protocol that makes it possible to assess performances of RFID devices in simulated supply chain processes. The testing protocol has been designed by a panel of academicians, whose research activities are focused on RFID applications and logistics, and retail executives from the apparel industry. We applied the testing protocol to 7 inlays and hard tags, 3 fixed readers, 4 mobile handhelds, and 1 printer, all operating according to EPC class 1 gen 2 protocols and ETSI regulations. We measured and compared read rates, accuracies, and read times. FINDINGS: By simulating a real-world environment, test results give a direct insight of performances to be expected from different RFID devices. Therefore practitioners can find answers to how a specific piece of hardware — such as an inlay, reader or printer — performs, or which hardware would be the best choice for a company's specific application, such as logistics, inventory checking or store security. At the same time, researchers focused on the business value of RFID applications can validate RFID-reengineered business processes.

Although the benefits of Radio Frequency Identification Technologies (RFID) are quite well known, they are still scarce applications to agriculture and food supply chains. The aim of this study was to determine the extent to which the adoption of RFID can improve supply chain performance in agri-food supply chains. The methodology was a case study of a fruit cooperative using semi-structured interviews and other sources of evidence in order to examine the supply chain performance before and after the RFID implementation. Benefits from the RFID implementation were classified into two broad categories: strategic and operation ones. Strategic benefits included: reduction of the warehouse costs; reduction of total lead time from production to sales; improvement of customer relationship management; improved recall management. Operational benefits included: Better handling of unforeseen events; reducing lead times in warehousing and inventory; improved quality control.

This paper presents the results of the economical evaluation of the possibility of RFID technology adoption in an European company involved in the manufacturing of the fuselage of a new long-range, mid-size, wide-body jet airliner made of carbon fibre reinforced polymer. The peculiar constraints to the management of some of the raw materials - Time And Temperature Sensitive (TATS) materials - has pushed the Company to consider RFID tags introduction despite the fact that the material supplier did not provide any support. Thus, the most important impulse to the introduction of the RFID system in the Company has been given by the problems encountered in the management of TATS materials. However, further analyses are presented on the opportunity for the Company of extending RFID application to non- TATS materials. In this sense, several scenarios are presented, evaluating investment in hardware and tags costs with respect to advantages in terms of time savings in material handling processes or costs saving in terms of inventory misalignment reductions. In most scenarios, RFID introduction resulted to be profitable.

Radio Frequency Identification (RFID) is a key enabling technology for the Internet of Things. Like other information systems, RFID systems evolve to meet new requirements. The behavior (e.g. tag-reading performance) of RFID systems is closely coupled with software, hardware and its deployment environment. An RFID system needs to be rigorously tested before its deployment and re-tested each time when there are changes in software, hardware or environment. The cost of testing an RFID system can be significantly lowered by substituting its hardware and deployment environment with a simulator. However, radio waves can be affected by many environmental factors such as multi-path effects, backing materials and electro-magnetic noises. The effect of these factors on radio waves cannot be precisely modeled algorithmically. In this paper, we propose an effective technique to construct a mixed-reality simulator for RFID system testing using iterated learning based on a Support vector Machine (SVM). We applied our simulator to a real-life RFID object tracking system, which keeps track of the stock items entering or leaving a warehouse. Evaluation results show that our mixed-reality simulator can achieve 90% prediction accuracy with 90% reduction in both the time and storage space as compared with performing the tests using real hardware and environment. © 2011 - IOS Press and the authors. All rights reserved.

New technologies such as radio frequency identification (RFID) to better track cargo shipments are responsible for maintaining improved control and tracking along the supply chain. Among various modes of transportation used within the supply chain, a