A Survey on RFID in Industry 4.0

As a consequence of swiftly growing populations in the urban areas, larger quantities of solid waste also form rapidly. Since urban local bodies are found to be unable to manage this perilous situation effectively, there is a high probability of risks relative to the environment and public health. A sudden change is indispensable in the existing systems that are developed for the collection, transportation, and disposal of solid waste, which are entangled in turmoil. However, Smart sensors and wireless technology enable cyber-physical systems to automate solid waste management, which will revolutionize the industry. This work presents a comprehensive study on the evolution of automation approaches in solid waste management systems. This study is enhanced by dissecting the available literature in solid waste management with Radio Frequency Identification (RFID), Wireless Sensor Networks (WSN), and Internet of Things (IoT)-based approaches and analyzing each category with a typical architecture, respectively. In addition, various communication technologies adopted in the aforementioned categories are critically analyzed to identify the best choice for the deployment of trash bins. From the survey, it is inferred that IoT-based systems are superior to other design approaches, and LoRaWAN is identified as the preferred communication protocol for the automation of solid waste handling systems in urban areas. Furthermore, the critical open research issues on state-of-the-art solid waste handling systems are identified and future directions to address the same topic are suggested.

Section: Rfid Based Solid Waste Management Systemsmentioning

confidence: 99%

Sensor-Based Solid Waste Handling Systems: A Survey

Vishnu

Ramson

Rukmini

et al. 2022

“…When considering that Industry 4.0 is first and foremost understood as a technological advancement of organizational workings [ 3 , 5 ], in research, scientists have directly proposed that the use of certain contemporary management tools can serve as a precursor for the implementation of Industry 4.0, for instance, RFID [ 34 , 76 ], rapid prototyping [ 77 ], etc. More traditional management tools have also been put forward as being beneficial to use in the environment of Industry 4.0 [ 20 , 78 ], for instance, customer segmentation [ 60 ], mission and vison statements [ 20 ], etc.…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

“…In recent years, it has improved and it is very compatible with the industrial internet of things and CPS, which means that it is one of the systems enabling real-time communication between the machines [ 34 ]. RFID complements and reflects the main principles of Industry 4.0 by using information technology to comprehensively track products and materials, and provides a valuable database for Industry 4.0 operations in organizations [ 76 ].…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

Speeding Up the Implementation of Industry 4.0 with Management Tools: Empirical Investigations in Manufacturing Organizations

Črešnar

Potočan

Nedelko

2020

The main purpose of this study is to examine how the use of management tools supports the readiness of manufacturing organizations for the implementation of Industry 4.0. The originality of the research is reflected in the exploration of the relationship between the use of the selected well-known management tools and their readiness for the implementation of Industry 4.0, which was assessed using a combination of two models—one developed by the National Academy of Science and Engineering (Acatech) and the other by the University of Warwick. The relationship was assessed by applying structural equation modeling techniques to a data set of 323 responses from employees in manufacturing organizations. The results show that the use of six sigma, total quality management, radio frequency identification, a balanced scorecard, rapid prototyping, customer segmentation, mission and vision statements, and digital transformation is positively associated with Industry 4.0 readiness. Inversely, outsourcing and strategic planning are negatively associated with Industry 4.0 readiness, while lean manufacturing, which is often emphasized as the cornerstone of Industry 4.0 implementation, is not associated with Industry 4.0 readiness in our study. These findings can help organizations to understand how to consider and measure readiness for the implementation of Industry 4.0 more comprehensively and present guidelines on how the use of management tools in manufacturing organizations can foster their implementation of Industry 4.0 principles.

“…In the last few years, few technologies associated with Industry 4.0 are implemented due to the incipient state of research [ 11 ]. Nonetheless, there are widely used technologies in the field of manufacturing (e.g., Radio Frequency Identification (RFID) [ 12 ], robots) that increase the quality and reduce the cost of products [ 13 ]. However, the lack of connectivity between machines and management services implies a reduction in the added-value of products [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Digital Twin for Automatic Transportation in Industry 4.0

Martínez-Gutiérrez

Díez-González

Ferrero-Guillén

et al. 2021

Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper.