Search

This article aims to examine and understand the current scope of Prescriptive Maintenance integrated with the human-centric characteristics of Industry 5.0. Therefore, the main research question is the following: "In the view of the managers of the companies visited, located in the Southeast Region of Brazil, what are the main technical and administrative difficulties that companies encounter in successfully implementing proactive combinations on the factory floor, such as Prescriptive Maintenance integrated with the characteristics of Industry 5.0"?. The evolution of industrial processes in recent decades and the advent of Industry 4.0 integrated with human-centered characteristics have placed maintenance as one of the protagonists of industrial processes. In a scenario where automation and humans are gaining more and more space, the future of industries lies in Prescriptive Maintenance. To achieve the objective of the article, professional experiences from participation in congresses, seminars and technical visits to several factories located in the Southeast Region of Brazil are used. In data collection, we explored documentary observation and bibliographic research in the Science Direct and Web of Science databases. The study focuses on research areas related to maintenance integration, Industry 4.0 (Techno centric) and human-centric characteristics (Industry 5.0). The article brought important conclusions, as it addresses the impact and trends on the factory floor so that managers can develop competitiveness and productivity. The article highlights the role of maintenance methods in improving factory floor performance, emphasizing human knowledge and Prescriptive Maintenance practices to ensure operations within World Class standards. [ABSTRACT FROM AUTHOR]

This paper aims to demonstrate the necessity of simulation-based multibody dynamic modeling for determining the driving stability of logistics transport robots, including those with complex-shaped tires and suspension structures. Specifically, we generate a 3D dynamic model of a mobile robot using RecurDyn software and propose a new lumped parameter tire model for the lug-type tire to calculate contact forces between the tire and ground. The tire model is validated through tire compression tests, resulting in good agreement between the model and test results. We perform various driving simulations using the dynamic model, and calculate roll and pitch stability based on the dynamic behavior and tire forces of the robot. We present stability indicators for different driving conditions as a 3D map, providing criteria for stable driving. The proposed models and methods have the potential to improve the performance and stability of multi-terrain mobile robots in various industries. [ABSTRACT FROM AUTHOR]

Featured Application: The reduction and prevention of multiple cracks and leakage of water due to factory floor sinking. In this study, in order to protect the concrete layer from slab sinking cracks in the factory floor layer, four types of reinforcing materials with a notable waterproof performance are fixed at the bottom. Furthermore, short fibers mixed with concrete in order to evaluate the load transfer mechanism and residual stress retention ability are used. The change in flexural strength due to the waterproof reinforcement varied from about 10 to 48% depending on the type of reinforcing material, and the flexural strength of the specimen reinforced with Typar and Preprufe was demonstrated to be the best. Additionally, the increase in flexural strength due to the combination of the SF20 + Typar and MF2.8 + Preprufe specimens was remarkable. After the concrete matrix cracking, the toughness resulting from the fiber pull-out resistance and the increase in the reaction force of the waterproof reinforcement showed a marked improvement in all the test specimens. The test specimen reinforced with Typar demonstrated the best crack resistance regardless of the fiber type. The crack transfer mechanism in the concrete floor can be summarized in that the fiber pull-out resistance and the reaction force of the waterproof reinforcement immediately after cracking causes a reduction of the crack length (l) from the rapid load transfer, and as a result, the fiber bridging zone (lf) is widely protected. Therefore, it is determined that the residual stress rises, maintains, and slows, as the resistance of the fiber bridging in the cracked section and the effect of the waterproofing reinforcement layer is combined. [ABSTRACT FROM AUTHOR]

In this study, in order to protect the concrete layer from slab sinking cracks in the factory floor layer, four types of reinforcing materials with a notable waterproof performance are fixed at the bottom. Furthermore, short fibers mixed with concrete in order to evaluate the load transfer mechanism and residual stress retention ability are used. The change in flexural strength due to the waterproof reinforcement varied from about 10 to 48% depending on the type of reinforcing material, and the flexural strength of the specimen reinforced with Typar and Preprufe was demonstrated to be the best. Additionally, the increase in flexural strength due to the combination of the SF20 + Typar and MF2.8 + Preprufe specimens was remarkable. After the concrete matrix cracking, the toughness resulting from the fiber pull-out resistance and the increase in the reaction force of the waterproof reinforcement showed a marked improvement in all the test specimens. The test specimen reinforced with Typar demonstrated the best crack resistance regardless of the fiber type. The crack transfer mechanism in the concrete floor can be summarized in that the fiber pull-out resistance and the reaction force of the waterproof reinforcement immediately after cracking causes a reduction of the crack length (l) from the rapid load transfer, and as a result, the fiber bridging zone (lf) is widely protected. Therefore, it is determined that the residual stress rises, maintains, and slows, as the resistance of the fiber bridging in the cracked section and the effect of the waterproofing reinforcement layer is combined.

The Internet of Things (IoT) is the global network of interrelated physical devices such as sensors, actuators, smart applications, objects, computing devices, mechanical machines, and people that are becoming an essential part of the internet. In an industrial environment, these devices are the source of data which provide abundant information in manufacturing processes. Nevertheless, the massive, heterogeneous, and time-sensitive nature of the data brings substantial challenges to the real-time collection, processing, and decision making. Therefore, this paper presents a framework of an IoT-based Industrial Data Management System (IDMS) which can manage the huge industrial data, support online monitoring, and control smart manufacturing. The framework contains five basic layers such as physical, network, middleware, database, and application layers to provide a service-oriented architecture for the end users. Experimental results from a smart factory case study demonstrate that the framework can manage the regular data and urgent events generated from various factory devices in the distributed industrial environment through state-of-the-art communication protocols. The collected data is converted into useful information which improves productivity and the prognosis of production lines.

A key characteristic for industrial production in the Industry 4.0 paradigm is the connection of physical items like sensors, devices and enterprise assets, connected both to each other and to the Internet. In this Internet of Things environment, things will sense more data, become context-aware and provide added-value information to assist people take more relevant and valuable decisions. Context-aware information distribution may offer substantial value to manufacturing. It provides taskrelevant information or services to users in a manufacturing shop-floor improving decision making through context-driven recommendations. This paper presents a context-aware information distribution system to support users in an industrial environment. The system aims at utilising data collected from sensors located at a shop-floor in order to increase the visibility of shop-floor processes by providing the right information, to the right people, at the right time. The system's architecture and key elements have been developed for a pilot implementation in the white goods industry and are presented in this study. [ABSTRACT FROM AUTHOR]