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Introduction: The aerospace industry has been significantly disrupted by recent economic downturns, underscoring the need for robust supply chain management. This is especially important given the complexity of aircraft manufacturing, the globalization of supply chains, and the requirement to meet stringent regulatory standards. While outsourcing is widely adopted to improve cost competitiveness, it also introduces risks, such as compromised product quality, inefficiency, and delays. Methods: This study explores how aerospace firms manage outsourcing relationships using control mechanisms. Data were gathered through seven semi-structured interviews with supply chain managers from contracting and supplier firms focusing on both formal and informal controls in supplier selection and relationship management. Results: Supplier selection is primarily guided by trust, past performance, and delivery reliability. Firms employ formal controls, such as KPIs and certifications, alongside informal practices, including embedding internal staff within supplier operations. This dual approach ensures quality, mitigates risks, and maintains compliance with regulatory standards. Conclusions: This study concludes that combining formal and informal controls is vital for balancing outsourcing efficiency with risk mitigation, offering valuable insights into supply chain management practices in regulated industries like aerospace. Full article

The management of and reduction in ammonia nitrogen (NH₃-N) and total phosphorus (TP) in the water environment are crucial for protecting water quality amid rapid urbanization and population growth in highly industrialized regions. Specifically, in the Xiangjiang River Basin, the development of the Chang–Zhu–Tan urban agglomeration resulted in the deterioration of river water quality in the past, where ammonia nitrogen (NH₃-N) and total phosphorus (TP) were the dominant pollutants. This study aims to assess the influence of anthropogenic and climatic factors on the dynamics of nitrogen and phosphorus in an urbanized river basin in the middle Xiangjiang River Basin, China, from 2016 to 2020. This study examines NH₃-N and TP trends and their influencing factors across six tributaries, as well as how their concentrations have changed in response to urbanization and wastewater treatment management. The results reveal that average NH₃-N and TP concentrations decreased from 2016 to 2020 in the urbanized river system. NH₃-N and TP concentrations exhibited positive correlations with the proportion of cropland and negative correlations with population number, percentages of urban lands, and forests. In contrast, the influence of precipitation and streamflow on NH₃-N and TP concentrations was relatively weak. Consequently, agricultural activity was the primary contributing factor to NH₃-N and TP concentrations. Our study also suggests that the government’s newly implemented water protection regulations can effectively control pollutant levels in urbanized river basins. Full article

Model predictive control (MPC) has emerged as a very popular control technology. This paper presents and discusses the major applications and recent research advances of MPC in the field of high-power converters and industrial drives. The classic concepts and implementation principles of MPC for power electronic control are reviewed, followed by the classification and application schemes of MPC in electrical drive systems. This paper discusses typical MPC techniques. Based on the results of extensive discussions on the latest research, this paper analyzes some key application issues of MPC in industrial control solutions, including the optimization and elimination of weighting factors, improvement of steady-state performance, and robustness improvement. It also covers research trends in advanced MPC. By reviewing advanced MPC solutions, this paper contributes to enhancing the performance in applications of high-power converters and industrial drives, and providing multiple perspectives to improve control performance of MPC. The presented content aims to provide readers with a precise overview and facilitate their future research in this attractive area. Full article

Water resources are vital for humanity, but their quality has degraded in recent years due to increasing industrial activities. One significant issue is fluoride contamination, prevalent worldwide. Fluorides exist in combined states such as calcium fluoride, fluorapatite, and cryolite, originating from industrial processes like aluminum and fertilizer manufacturing. The World Health Organization warns against fluoride levels above 1.5 mg/L in drinking water due to health risks, including dental and skeletal fluorosis. Industrial activities also release fluoride-containing wastes into the environment, endangering ecosystems and human health. Overexposure to fluoride leads to disorders affecting organs including the kidneys, liver, and nervous system. Despite fluoride’s benefits in controlled doses, excessive intake causes health problems, as evidenced by rising dental fluorosis cases in Brazil. Thus, effective and affordable fluoride removal strategies are crucial. Various methods exist, including adsorption, membrane technology, ion exchange process, electrodialysis, and electrocoagulation. Regulation of fluoride levels in drinking water is imperative to safeguard public health from its detrimental long-term effects. Full article

This study investigates how organizational contingency factors, namely company size, environmental uncertainty, technological capacity, and organizational structure, affect the design and effectiveness of management control systems (MCS) in Moroccan industrial companies. Drawing on contingency theory, which emphasizes the alignment of organizational systems with contextual factors, this research applies quantitative methods to a sample of 190 industrial firms in Morocco, achieving a 76% response rate to the distributed surveys. The data are analyzed using correlation and linear regression techniques to explore these relationships. The findings reveal that larger firms, those operating in dynamic and uncertain environments, and those with advanced technological systems tend to implement more sophisticated, integrated, and participative MCS. Furthermore, flexible and decentralized organizational structures significantly enhance the adoption of adaptive control systems. These results underscore the importance of tailoring MCS to organizational characteristics and environmental conditions, particularly in emerging market contexts. This study’s novel contribution lies in its application of contingency theory to a non-Western industrial context, addressing a gap in the literature by demonstrating how specific regional factors influence MCS practices. This research offers practical insights for Moroccan industrial firms seeking to improve their operational efficiency, adaptability, and strategic decision making in volatile markets. Full article

The introduction of Self-X capabilities into industrial control offers a tremendous potential in the development of resilient, adaptive production systems that enable circular economy. The Self-X capabilities, powered by Artificial Intelligence (AI), can monitor the production performance and enable timely reactions to problems or suboptimal operation. This paper presents a concept and prototype for Self-X AI in the process industry, particularly electric steelmaking with the EAF (Electric Arc Furnace). Due to complexity, EAF operation should be optimized with computational models, but these suffer from the fluctuating composition of the input materials, i.e., steel scrap. The fluctuation can be encountered with the Self-X method that monitors the performance, detecting anomalies and suggesting the re-training and re-initialization of models. These suggestions support the Human-in-the-Loop (HITL) in managing the AI models and in operating the production processes. The included Self-X capabilities are self-detection, self-evaluation, and self-repair. The prototype proves the concept, showing how the optimizing AI pipeline receives alarms from the external AI services if the performance degrades. The results of this work are encouraging and can be generalized, especially to processes that encounter drift related to the conditions, such as input materials for circular economy. Full article

The concurrence of social robots with different functionalities and cyber-physical systems in indoor environments has recently been increasing in many fields, such as medicine, education, and industry. In such scenarios, the collaboration of such heterogeneous robots demands effective communication for task completion. The concept of the Internet of Robotic Things (IoRT) is introduced as a potential solution, leveraging technologies like Artificial Intelligence, Cloud Computing, and Mesh Networks. This paper proposes an IoRT-based middleware that allows the communication of different types of robot operating systems in dynamic environments, using a cloud-based protocol. This middleware facilitates task assignment, training, and planning for heterogeneous robots, while enabling distributed communication via WiFi. The system operates in two control modes: local and cloud-based, for flexible communication and information distribution. This work highlights the challenges of current communication methods, particularly in ensuring information reach, agility, and handling diverse robots. To demonstrate the middleware suitability and applicability, an implementation of a proof-of-concept is shown in a touristic scenario where several guide robots can collaborate by effectively sharing information gathered from their heterogeneous sensor systems, with the aid of cloud processing or even internal communication processes. Results show that the performance of the middleware allows real-time applications for heterogeneous multi-robot systems in different domains. Full article

The integration of artificial intelligence(AI) technologies into identity and access management (IAM) systems has greatly improved access control and management, offering more robust, adaptive, and intelligent solutions than traditional methods. AI-driven IAM systems enhance security, operational efficiency, and introduce new capabilities in industrial environments. In this narrative review, we present the state-of-the-art AI technologies in industrial IAM, focusing on methods such as biometric, comprising facial and voice recognition, and multifactor authentication for robust security. It addresses the challenges and solutions in implementing AI-based IAM systems in industrial settings, including security, privacy, evaluation, and continuous improvement. We present also the emerging trends and future directions, highlighting AI’s potential to transform industrial security measures. This review aims to guide researchers and practitioners in developing and implementing next-generation access control systems, proposing future research directions to address challenges and optimize AI applications in this domain. Full article

The decarbonization of energy systems is forcing the development of renewable energy generation and consumption technologies. Photovoltaic systems are being used in almost every industry, including autonomous power systems used on ships, space vehicles, or flying platforms, where the voltage supplying specific equipment can change in an overridingly controlled manner. Feeding energy from a renewable source into a power system with highly dynamic frequency changes is not possible for traditional grid converter control strategies. This is caused by the synchronization system, which is designed for a fixed value of the grid voltage frequency, and by the proportional-resonant controllers used. In this paper, it is shown that frequency tracking correction causes deviations from the unit amplitude of synchronization signals, causing errors in the reference signals responsible for the active and reactive components of the converter current. To solve this problem, a new variable frequency adaptation system using a generalized second-order integrator was proposed. As a result, synchronization signals of unit amplitude were obtained. Due to the proposed method, the proportional-resonant controller was able to control the active and reactive components of the current even when the voltage frequency changes, adjusting the resonant frequency. Full article

The booming of the building industry has led to a sharp increase in energy consumption. The advancement of zero-energy buildings (ZEBs) is of great significance in mitigating climate change, improving energy efficiency, and thus realizing sustainable development of buildings. This paper reviews the recent progress of key technologies utilized in ZEBs, including energy-efficient measures (EEMs), renewable energy technologies (RETs), and building energy management system (BEMS), aiming to provide reference and support of the wider implementation of ZEBs. EEMs can reduce energy demand by optimizing the envelope design, phase change materials integration, efficient HVAC systems, and user behavior. The renewable energy sources discussed here are solar, biomass, wind, and geothermal energy, including distributed energy systems introduced to integrated various renewable resources and meet users’ demand. This study focuses on the application of building energy management in ZEBs, including energy use control, fault detection and diagnosis, and management optimization. The recent development of these three technologies mainly focuses on the combination with artificial intelligence (AI). In addition, this paper also emphasizes possible future research works about user behavior and zero-energy communities to improve the energy efficiency from a more complicated perspective. Full article

This study presents a methodology for the development of modern Supervisory Control and Data Acquisition (SCADA) systems aimed at improving the operation and management of concentrated solar power (CSP) plants, leveraging the tools provided by industrial digitization. This approach is exemplified by its application to the CESA-I central tower heliostat field at the Plataforma Solar de Almería (PSA), one of the oldest CSP facilities in the world. The goal was to upgrade the control and monitoring capabilities of the heliostat field by integrating modern technologies such as OPC (Open Platform Communications)) Unified Architecture (UA), a Wi-Fi mesh communication network, and a custom Python-based gateway for interfacing with legacy MODBUS systems. Performance tests demonstrated stable, scalable communication, efficient real-time control, and seamless integration of new developments (smart heliostat) into the existing infrastructure. The SCADA system also introduced a user-friendly Python-based interface developed with PySide6, significantly enhancing operational efficiency and reducing task complexity for system operators. The results show that this low-cost methodology based on open-source software provides a flexible and robust SCADA architecture, suitable for future CSP applications, with potential for further optimization through the incorporation of artificial intelligence (AI) and machine learning. Full article

The advent of dual-frequency induction heating (DFIH) technology has revolutionized modern industrial applications by providing flexible regulation of the heating process, significantly boosting heating efficiency, and optimizing energy utilization. This comprehensive review delves into the state-of-the-art research on DFIH power supplies, with a particular emphasis on their topological structures, output power control mechanisms, and resonant network configurations. The paper critically examines the challenges inherent to this technology, such as enhancing power density and ensuring system stability. It also highlights recent innovations in multi-inverter bridge topologies, resonant circuit optimization, and the implementation of intelligent control algorithms. Case studies are employed to illustrate the practical applications of DFIH in metal processing and composite material treatment, showcasing its potential to revolutionize these industries. The review concludes by delineating future research directions, with a focus on the integration of multi-frequency technologies and the development of efficient control strategies, thereby setting the stage for the next generation of induction heating systems. Full article

Diesel engines are extensively employed in transportation, agriculture, and industry due to their high thermal efficiency and fuel economy. However, the combustion of conventional diesel fuel is accompanied by substantial emissions of pollutants, including carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NO_x), and carbon dioxide (CO₂), posing significant threats to environmental quality. Biodiesel, as a renewable and cleaner alternative fuel, can significantly reduce emissions of CO, HC, and particulate matter (PM) due to its unique molecular structure. Nonetheless, its lower calorific value and poor cold-start performance limit its application, while its high oxygen content may contribute to increased NO_x emissions. To address these limitations, researchers have proposed blending biodiesel with alcohol-based fuels such as methanol, ethanol, or butanol to create synergistic combustion systems that optimize engine performance and emission characteristics. This paper systematically reviews the effects of alcohol fuels on the performance and emission characteristics of biodiesel blends in diesel engines. Studies indicate that the addition of alcohol fuels can significantly enhance engine performance by improving fuel atomization, extending ignition delay, and increasing premixed combustion efficiency. These enhancements result in higher cylinder pressure, net heat release rate (HRR), and brake thermal efficiency (BTE), while reducing brake-specific fuel consumption (BSFC) to some extent. Moreover, most studies report that alcohol fuels help reduce CO, HC, smoke, and NO_x emissions but tend to increase CO₂ emissions. However, some findings suggest that in certain cases, the opposite results may occur. The impact of different types of alcohol fuels on performance and emissions varies significantly, requiring a comprehensive evaluation of their properties, such as latent heat, viscosity, and oxygen content. Although the appropriate addition of alcohol fuels demonstrates substantial potential for optimizing engine performance and reducing emissions, excessive blending may lead to adverse effects, necessitating careful control of the blending ratio. Future research should consider mixing two or more alcohol fuels with biodiesel to explore synergistic effects beyond the capabilities of single alcohols. Additionally, further studies should focus on optimizing fuel compositions and emission control strategies for varying operating conditions. Full article

Permanent magnet synchronous motors (PMSMs) are widely used in a variety of fields such as aviation, aerospace, marine, and industry due to their high angular position accuracy, energy conversion efficiency, and fast response. However, driving errors caused by the non-ideal characteristics of the driver negatively affect motor control accuracy. Compensating for the errors arising from the non-ideal characteristics of the driver demonstrates substantial practical value in enhancing control accuracy, improving dynamic performance, minimizing vibration and noise, optimizing energy efficiency, and bolstering system robustness. To address this, the mechanism behind these non-ideal characteristics is analyzed based on the principles of space vector pulse width modulation (SVPWM) and its circuit structure. Tests are then conducted to examine the actual driver characteristics and verify the analysis. Building on this, a real-time compensation method is proposed, physically matched to the driver. Using the volt–second equivalence principle, an input–output voltage model of the driver is derived, with model parameters estimated from test data. The driving error is then compensated with a voltage method based on the model. The results of simulations and experiments show that the proposed method effectively mitigates the influence of the driver’s non-ideal characteristics, improving the driving and speed control accuracies by 88.07% (reducing the voltage error from 0.7345 V to 0.0879 V for a drastic command voltage with a sinusoidal amplitude of 10 V and a frequency of 50 Hz) and 53.08% (reducing the speed error from 0.0130°/s to 0.0061°/s for a lower command speed with a sinusoidal amplitude of 20° and a frequency of 0.1 Hz), respectively, in terms of the root mean square errors. This method is cost-effective, practical, and significantly enhances the control performance of PMSMs. Full article

Immunization against Gonadotropin-Releasing Hormone (GnRH) has been successfully explored and developed for the parenteral inoculation of animals, aimed at controlling fertility, reducing male aggressiveness, and preventing boar taint. Although effective, these vaccines may cause adverse reactions at the injection site, including immunosuppression and inflammation, as well as the involvement of laborious and time-consuming procedures. Oral vaccines represent an advancement in antigen delivery technology in the vaccine industry. In this study, a Salmonella enterica serovar Typhimurium (S. Typhimurium) mutant lacking the pathogenicity island 2 (S. Typhimurium ΔSPI2) was used as a vehicle and mucosal adjuvant to deliver two genetic constructs in an attempt to develop an oral immunological preparation against gonadotropin hormone-releasing hormone (GnRH). S. Typhimurium ΔSPI2 was transformed to carry two plasmids containing a modified GnRH gene repeated in tandem (GnRXG/Q), one under eukaryotic expression control (pDNA::GnRXG/Q) and another under prokaryotic expression control (pJexpress::GnRXG/Q). A group of three male BALB/c mice were orally immunized and vaccination-boosted 30 days later. The oral administration of S. Typhimurium ΔSPI2 transformed with both plasmids was effective in producing antibodies against GnRXG/Q, leading to a decrease in serum testosterone levels and testicular tissue atrophy, evidenced by a reduction in the transverse tubular diameter of the seminiferous tubules and a decrease in the number of layers of the seminiferous epithelium in the testes of the inoculated mice. These results suggest that S. Typhimurium ΔSPI2 can be used as a safe and simple system to produce an oral formulation against GnRH and that Salmonella-mediated oral antigen delivery is a novel, yet effective, alternative to induce an immune response against GnRH in a murine model, warranting further research in other animal species. Full article