As a natural consequence of Industry 4.0 demands related to industrial processes control digitization, the smart manufacturing (SM) concept was enriched by integrating advanced technologies of digital information processing. This paper presents an original solution for improving the most representative instance of SM, namely, supply chain management (SCM), by using the most recent approach in hierarchical networked control systems (HNCS), that is Edge Computing. The paper presents both the software and hardware architecture of an Edge Gateway device which offers, on one hand, dual communication both on vertical (between the network layers from the local, inferior, represented by IIoT, to the central, superior, represented by the Cloud) and on horizontal (between similar devices located on the same Edge level) and, on the other hand, can locally process data to take fast decisions which facilitate real-time process control. The validity of the proposed solution is supported by a case study performed on a flexible assembly/disassembly line (laboratory model).

This research paper presents a case study on the application of Metal Oxide Semiconductor (MOX)-based VOC/TVOC sensors for indoor air quality (IAQ) monitoring. This study focuses on the ease of use and the practical benefits of these sensors, drawing insights from measurements conducted in a university laboratory setting. The investigation showcases the straightforward integration of MOX-based sensors into existing IAQ monitoring systems, highlighting their user-friendly features and the ability to provide precise and real-time information on volatile organic compound concentrations. Emphasizing ease of installation, minimal maintenance, and immediate data accessibility, this paper demonstrates the practicality of incorporating MOX-based sensors for efficient IAQ management. The findings contribute to the broader understanding of MOX sensor capabilities, providing valuable insights for those seeking straightforward and effective solutions for indoor air quality monitoring. This case study outlines the feasibility and benefits of utilizing MOX-based sensors in various environments, offering a promising avenue for the widespread adoption of user-friendly technologies in IAQ management.

This paper presents a method for functionally extending an IoT indoor air quality monitoring network by adding a cloud-level fire detection logic component. The proposed method does not aim to replace traditional fire detection systems at this stage of research, but to propose a solution for the development of fire detection capabilities and to improve the support provided to firefighting teams by providing a geospatial representation of the building in which a fire occurs. The proposed solution is based on a series of laboratory tests that demonstrated that air quality sensors can successfully detect the effects caused by an ignition event of common materials and can differentiate fire events from other events that can generate false-positive alarms by classic detection systems. The research involved five laboratory combustion tests based on the measurement of temperature, humidity, PM2.5 particle concentration, volatile organic compound index, and nitrogen oxide index. Following the tests, a warning mechanism and geospatial representation were designed using a system with ten IoT sensors to monitor the indoor air quality in a building on our university’s campus.

Antifragility was introduced as a term no later than 10 years ago. As presented by Taleb, antifragility means that a system becomes more resilient and more robust with every harmful and/or stressful action it is confronted with. This paper is based on a study which aimed to use the concept of antifragility during the design stage of a self-improving system. This way, it is expected to obtain a fast adaptive system capable of functioning at optimal parameters even when it works under adverse conditions or faces unforeseen changes in the environment. Assuming that an antifragile system not only maintains its robust behavior when faced with stressful and harmful events but even benefits from them to optimize its performance, the paper offers a detailed description of the features that must be ensured when designing a self-improving antifragile manufacturing system. By ensuring the property of antifragility, complex manufacturing systems are much safer to exploit under uncertain conditions, which brings major benefits to the process management. Starting from consecrated solutions such as preventive maintenance (PvM) and predictive maintenance (PdM) and using techniques of artificial intelligence, we present the concept of antifragile maintenance (AfM).

With the rapid increase of image sensors resolution, some pressure moved on compression algorithms again. Fractal compression is known to provide good performance in terms of compression ratio. But more than ever, the focus is on execution time of these algorithms. Large and fast access memories are hard to provide and very expensive. Therefore, a fast compression algorithm can reduce the expensive memory dimension if the execution time can handle real-time requirements. Graphics Processing Units (GPUs) could provide support for such goal. This article presents some discussion and an example of how fractal compression algorithms can benefit from GPU support.