Search Results (112)

The concept of a digital twin has become a key driver of industrial transformation, enabling a seamless connection between physical systems and their virtual counterparts. The growing need for adaptability has accelerated the use of advanced technologies and tools to maintain competitiveness. In this context, the article introduces the concept of a hierarchical digital twin and illustrates its operation through a practical example. Production resource structures and timing data were generated in the KbRS (Knowledge-based Rescheduling System), which will serve as the Level II digital twin in this article. The acquired data is transferred via Excel to the FlexSim simulation environment, which represents the Level I digital twin responsible for modeling the flow of production processes. Because a digital twin must accurately reflect a specific production system, the study begins by formulating a general mathematical model. Algorithms for product ordering and for constructing the digital twin of the production processes were developed. Furthermore, three implementation scenarios for the hierarchical digital twin were proposed using the KbRS and FlexSim tools. The implementation of the hierarchical digital twin concept facilitated the development of the more comprehensive virtual model. At the same time, the integration of data between the two software environments enabled the generation of more detailed and precise results. Traditionally, a digital twin created solely within a single simulation platform is unable to represent all the structural components of a production system—an issue addressed by the hierarchical approach presented in this study. Full article

Metaheuristics are a fundament pillar of Industry 4.0, as they allow for complex optimization problems to be solved by finding good solutions in a reasonable amount of computational time. One category of important problems in modern industry is that of binary problems, where decision variables can take values of zero or one. In this work, we propose a binary version of the Pufferfish optimization algorithm (BPOA), which was originally created to solve continuous problems. The binary mapping follows a two-step technique, first transforming using transfer functions and then discretizing using binarization rules. We study representative pairings of transfer functions and binarization rules, comparing our algorithm with Particle Swarm Optimization, Secretary Bird Optimization Algorithm, and Arithmetic Optimization Algorithm with identical computational budgets. To validate its correct functioning, we solved binary problems present in industry, such as the Set Covering Problem together with its Unicost variant, as well as the Knapsack Problem. The results we achieved with regard to these problems were promising and statistically validated. The tests performed on the executions indicate that many pair differences are not statistically significant when both methods are already close to the optimal level, and significance arises precisely where the descriptive gaps widen, underscoring that transfer–rule pairing is the main performance factor. BPOA is a competitive and flexible framework whose effectiveness is mainly governed by the discretization design. Full article

Polyetheretherketone (PEEK) is a high-performance engineering plastic widely used in aerospace, automotive, and other industries due to its heat resistance and mechanical strength. However, its high friction coefficient and low thermal conductivity limit its use in heavy-load environments. Existing studies have extensively explored the individual effects of thermal processing or irradiation on PEEK. However, the synergistic mechanism between the initial microstructure formed by mold temperature and subsequent irradiation modification remains unclear. This paper investigates the coupled effects of injection molding temperature and electron beam irradiation on the tribology of carbon fiber-reinforced PEEK composites, with the aim of identifying process conditions that improve friction and wear performance under high load by controlling the crystal morphology and cross-linking network. Carbon fiber (CF) particles were mixed with PEEK particles at a 1:2 mass ratio, and specimens were prepared at injection molding temperatures of 150 °C, 175 °C, and 200 °C. Some specimens were irradiated with an electron beam dose of 200 kGy. The friction coefficient, wear rate, surface shape, and crystallinity of the material were obtained using friction and wear tests, white-light topography, SEM, and XRD. The results show that the injection molding temperature of the material influences the friction performance. Optimal performance is obtained at 175 °C with a friction coefficient of 0.12 and wear rate of 9.722 × 10⁻⁶ mm³/(N·m). After irradiation modification, the friction coefficient decreases to 0.10. This improvement is due to the moderate melt fluidity, adequate fiber infiltration, and dense crystallization at this temperature. In addition, cross-linking of chains occurs, and surface transfer films are created at this temperature. However, irradiation leads to a slight increase in wear rate to 1.013 × 10⁻⁵ mm³/(N·m), suggesting that chain segment fracture and embrittlement effects are enhanced at this dose. At 150 °C, there is weak interfacial bonding and microcrack development. At 200 °C, excessive thermal motion reduces crystallinity and adds residual stress, increasing wear sensitivity. Overall, while irradiation reduces the friction coefficient, the wear rate is affected by the initial microstructure at molding. At non-optimal temperatures, embrittlement tends to dominate the wear mode. This study uncovers the synergistic and competitive dynamics between the injection molding process and irradiation modification, offering an operational framework and a mechanistic foundation for applying CF/PEEK under heavy-load conditions. The present approach can be extended in future work to other reinforcement systems or variable-dose irradiation schemes to further optimize overall tribological performance. Full article

Hexavalent chromium (Cr(VI)) is a highly toxic and carcinogenic pollutant commonly found in industrial wastewater. To address the challenge of sulfate inhibition on biological methods for treating chromium-containing wastewater, this study investigated the enhancement effect and mechanism of anthraquinone-2,6-disulfonate (AQDS) on the anaerobic bio-reduction of Cr(VI). At an AQDS dosage of 30 mg/L, Cr(VI) reduction efficiency increased by 7.8-fold compared to the group with only sulfate. AQDS demonstrated remarkable performance of Cr(VI) bio-reduction by reducing intracellular Cr(VI) penetration, lowering reactive oxygen species (ROS) levels, and maintaining optimal NADH/NAD⁺ ratios. Importantly, AQDS restores Cr(VI) reduction efficiency by directing electron flow toward Cr(VI) reduction through enhanced extracellular electron transfer, thereby mitigating the competitive inhibitory effect of sulfate. It concluded that AQDS effectively enhances Cr(VI) bio-reduction, offering a promising strategy for the environmental remediation of Cr(VI)-contaminated wastewater under sulfate-rich conditions. Full article

Food loss and food waste (FLFW) constitute a major global challenge with profound economic, environmental, and social consequences. This study examines how businesses in Greece’s food service and retail sectors perceive and manage food waste, integrating the triple bottom line framework—economic, environmental, and social sustainability—as the guiding analytical lens. The research aims to: (1) analyze perceptions, practices, and barriers to food waste reduction among businesses; (2) explore the relationship between awareness, business policies, technological adoption, and consumer-oriented strategies; and (3) situate the Greek experience within broader European and international contexts to identify transferable lessons for policy and business innovation. Drawing on a structured survey of 250 industry representatives and comparative international evidence, the study finds that although awareness of food waste is widespread, it remains weakly connected to structured policies, technology adoption, or operational practices. Businesses recognize economic opportunities in waste reduction—such as supply chain optimization and near-expiry discounting—but these remain underexploited due to a lack of strong regulatory and financial incentives. The findings highlight that addressing food waste is not only an environmental and ethical necessity but also a strategic opportunity to enhance economic resilience, competitiveness, and sustainability within the agri-food sector. Full article

The authors of this paper highlight the creation of an experimental system for the implementation and testing of active low-voltage electronic power filters of the parallel type, with applicability in a wide range of electrical parameters. In this paper, the authors present the results obtained on an experimental test bench for power quality purposes. The experimental test bench is one of the results of a technology transfer project. One of the specific objectives of the project was to carry out industrial research and experimental development activities in order to develop a competitive, technical and economic solution for an intelligent power system, Active Power Filter (APF). Thus, this paper presents the experimental test bench for the design, implementation and testing of algorithms for current harmonics mitigation. The conceptual theoretical frame bases of both direct and indirect control have been presented by the authors. As a case study, both the simulation and experimental results of the indirect control strategy implemented on the test bench are provided. The indirect control method is chosen due to simplicity, no complex calculus requirements, and the use of a minimum number of transducers. By features comparison with modern control strategies, this study underlines the supremacy of the indirect control in active harmonics control. Full article

Microbial electrosynthesis (MES) has emerged as a promising bio-electrochemical technology for sustainable CO₂ conversion into valuable organic compounds since it uses living electroactive microbes to directly convert CO₂ into value-added products. This review synthesizes advancements in MES from 2010 to 2025, focusing on the electrode materials, microbial communities, reactor engineering, performance trends, techno-economic evaluations, and future challenges, especially on the results reported between 2020 and 2025, thus highlighting that MES technology is now a technology to be reckoned with in the spectrum of biofuel technology production. While the current productivity and scalability of microbial electrochemical systems (MESs) remain limited compared to conventional CO₂ conversion technologies, MES offers distinct advantages, including process simplicity, as it operates under ambient conditions without the need for high pressures or temperatures; modularity, allowing reactors to be stacked or scaled incrementally to match varying throughput requirements; and seamless integration with circular economy strategies, enabling the direct valorization of waste streams, wastewater, or renewable electricity into valuable multi-carbon products. These features position MES as a promising platform for sustainable and adaptable CO₂ utilization, particularly in decentralized or resource-constrained settings. Recent innovations in electrode materials, such as conductive polymers and metal–organic frameworks, have enhanced electron transfer efficiency and microbial attachment, leading to improved MES performance. The development of diverse microbial consortia has expanded the range of products achievable through MES, with studies highlighting the importance of microbial interactions and metabolic pathways in product formation. Advancements in reactor design, including continuous-flow systems and membrane-less configurations, have addressed scalability issues, enhancing mass transfer and system stability. Performance metrics, such as the current densities and product yields, have improved due to exceptionally high product selectivity and surface-area-normalized production compared to abiotic systems, demonstrating the potential of MES for industrial applications. Techno-economic analyses indicate that while MES offers promising economic prospects, challenges related to cost-effective electrode materials and system integration remain. Future research should focus on optimizing microbial communities, developing advanced electrode materials, and designing scalable reactors to overcome the existing limitations. Addressing these challenges will be crucial for the commercialization of MES as a viable technology for sustainable chemical production. Microbial electrosynthesis (MES) offers a novel route to biofuels by directly converting CO₂ and renewable electricity into energy carriers, bypassing the costly biomass feedstocks required in conventional pathways. With advances in electrode materials, reactor engineering, and microbial performance, MES could achieve cost-competitive, carbon-neutral fuels, positioning it as a critical complement to future biofuel technologies. Full article

This article presents a deep reinforcement learning (DRL) approach for adaptive robotic grasping in dynamic environments. We developed UR5GraspingEnv, a PyBullet-based simulation environment integrated with OpenAI Gym, to train a UR5 robotic arm with a Robotiq 2F-85 gripper. Soft Actor-Critic (SAC) and Proximal Policy Optimization (PPO) were implemented to learn robust grasping policies for randomly positioned objects. A tailored reward function, combining distance penalties, grasp, and pose rewards, optimizes grasping and post-grasping tasks, enhanced by domain randomization. SAC achieves an 87% grasp success rate and 75% post-grasp success, outperforming PPO 82% and 68%, with stable convergence over 100,000 timesteps. The system addresses post-grasping manipulation and sim-to-real transfer challenges, advancing industrial and assistive applications. Results demonstrate the feasibility of learning stable and goal-driven policies for single-arm robotic manipulation using minimal supervision. Both PPO and SAC yield competitive performance, with SAC exhibiting superior adaptability in cluttered or edge cases. These findings suggest that DRL, when carefully designed and monitored, can support scalable learning in manipulation tasks. Full article

Products with complex structures are structurally intricate and involve multiple professional fields and engineering construction elements, making it difficult for a single contractor to independently develop and manufacture such complex structural products. Therefore, during the research, development, and production of complex products, collaboration between manufacturers and suppliers is essential to ensure the smooth completion of projects. In this process, a complex supply chain network is often formed to achieve collaborative cooperation among all project participants. Within such a complex supply chain network, issues such as delayed delivery, poor product quality, or low resource utilization by any participant may trigger the bullwhip effect. This, in turn, can negatively impact the delivery cycle, product cost, and quality of the entire complex product, causing it to lose favorable competitive positions such as quality advantages and delivery advantages in fierce market competition. Therefore, this paper firstly explores the mechanism of complex product manufacturing and the supply network of complex product manufacturing, in order to grasp the inherent structure of complex product manufacturing with a focus on identifying symmetrical properties among supply chain nodes. Secondly, a complex product supply chain network model is constructed with the Graphical Evaluation and Review Technique (GERT), incorporating symmetry constraints to reflect balanced resource allocation and mutual dependencies among symmetrical nodes. Then, from the perspective of supply chain, we focus on identifying the shortcomings of supply chain suppliers and optimizing the management cost of the whole supply chain in order to improve the quality of complex products, delivery level, and cost saving level. This study constructs a Restricted Grey GERT (RG-GERT) network model with constrained outputs, integrates moment-generating functions and Mason’s Formula to derive transfer functions, and employs a hybrid algorithm (genetic algorithm combined with non-linear programming) to solve the multi-objective optimization problem (MOOP) for joint optimization of delivery time, quality, and cost. Empirical analysis is conducted using simulated data from Y Company’s aerospace equipment supply chain, covering interval parameters such as delivery time [5–30 days], cost [40,000–640,000 CNY], and quality [0.85–1.0], validated with industry-specific constraints. Empirical analysis using Y Company’s aerospace supply chain data shows that the model achieves a maximum customer satisfaction of 0.96, with resource utilization efficiency of inefficient suppliers improved by 15–20% (p < 0.05) after secondary optimization. Key contributions include (1) integrating symmetry analysis to simplify network modeling; (2) extending GERT with grey parameters for non-probabilistic uncertainty; (3) developing a two-stage optimization framework linking customer satisfaction and resource efficiency. Full article

The practical application of powdered photocatalysts is significantly hindered by challenges in recyclability and structural instability. This work proposes a sustainable immobilization strategy by integrating BiVO₄ nanoparticles into a sodium alginate (SA) aerogel scaffold through a facile freeze-drying approach. The abundant hydroxyl/carboxyl groups of SA enable uniform dispersion of BiVO₄ within the porous network, while the aerogel architecture enhances light-harvesting efficiency and mass transfer kinetics. Innovatively, peroxymonosulfate (PMS) was introduced to synergistically couple photocatalysis with sulfate radical-based advanced oxidation processes (SR-AOPs), where the photogenerated electrons from BiVO₄ effectively activate PMS to yield high-activity ·SO₄⁻ radicals. The optimized BiVO₄/SA aerogel achieves nearly complete removal of Rhodamine B within 2 h under visible light, which is competitive to pure BiVO₄ powders. In addition, the mechanically robust aerogel exhibits exceptional reusability, retaining ~90% efficiency after five cycles without structural collapse. This work provides a paradigm for designing recyclable photocatalyst carriers with dual oxidation pathways, demonstrating significant potential for industrial wastewater treatment. Full article

With the large-scale power batteries approaching their retirement phase, efforts are being made to advance the recycling and cascade utilization of power batteries for electric vehicles (EVs). This paper constructs a closed-loop supply chain (CLSC) of power batteries led by the battery manufacturer (BM) and composed of the electric vehicle manufacturer (EVM) and third-party recycler (TPR). The study investigates the optimal pricing strategies of this CLSC with the consideration of recycling competition under the government’s reward–penalty mechanism. This paper establishes five recycling modes, namely independent recycling and cooperative recycling, under dual-channel recycling, and further discusses the effects of the government reward–penalty mechanism and recycling competition on the recycling rate, profits, and recycling pricing of the CLSC in each recycling mode. The following conclusions are found: (1) An increase in the reward–penalty intensity will increase the recycling rate, sales price of EVs, wholesale price, transfer price, recycling price, and the profit of each recycler in the CLSC. (2) An increase in the recycling competition will result in the reduction of the profit of each enterprise, and will also lead to the reduction of the recycling rate. (3) Cooperation between enterprises can inhibit the recycling volume of other enterprises to a certain extent. The cooperation between the EVM and BM can increase the recycling volume and the sales volume of EVs. (4) The leadership of the BM in the supply chain is embodied in the recycling and profit. For other members of the supply chain, it is very important to strive for cooperation with the leaders in the supply chain. These research conclusions can provide theoretical support for optimizing the power battery recycling system, formulating relevant policies, and improving the efficiency of resource recycling, thereby promoting the sustainable development of the new energy industry. Full article

The coordinated development of tourism and industrialization is essential for achieving sustainable and inclusive growth in the tourism sector, as well as for ensuring long-term regional economic sustainability. This study is motivated by the observation that land is a key factor influencing the coordination between tourism and industrialization, yet the specific role of land use remains underexplored. Therefore, the objective of this paper is to investigate the nonlinear relationship and underlying mechanisms through which tourism development impacts industrialization, with a particular focus on land transfers. To achieve this, the study employs an empirical approach using multi-source data—including data on China’s A-level scenic areas and land transfers—combined with an econometric method. The results indicate a U-shaped relationship between both the quantity and quality of tourism resources and the growth of industrial enterprises, as well as an inverted U-shaped relationship between the concentration of tourism resources and industrial development. The research finds that tourism development influences industrialization through two primary land-related mechanisms: the factor competition effect and the resource conservation effect. This study also investigates the potential for synergistic development between the tourism and industrial sectors, providing valuable insights for the sustainable economic advancement of land-based tourism and industrialization. Full article

Insider threats pose significant challenges to organizations, seriously endangering information security and privacy protection. These threats arise when employees with legitimate access to systems and databases misuse their privileges. Such individuals may alter, delete, or insert data into datasets, sell customer or client email addresses, leak strategic company plans, or transfer industrial and intellectual property information. These actions can severely damage a company’s reputation, result in revenue losses and loss of competitive advantage, and, in extreme cases, lead to bankruptcy. This study presents a novel solution that examines how organizational factors such as job satisfaction and security, organizational support, attachment, commitment, involvement in information security, and organizational norms influence employees’ attitudes and intentions, thereby mitigating insider threats. A key strength of this research is its integration of two foundational theories: the Social Bond Theory (SBT) and the Theory of Planned Behavior (TPB). The results reveal that job satisfaction and security, affective and normative commitment, information security training, and personal norms all contribute to reducing insider threats. Furthermore, the findings indicate that employees’ attitudes, perceived behavioral control, and subjective norms significantly influence their intentions to mitigate insider threats. However, organizational support and continuance commitment were not found to have a significant impact. Full article

Green innovation has emerged as a key catalyst for the sustainable growth of logistics enterprises. Green innovation not only helps logistics enterprises reduce operating costs but also enhances their competitiveness and promotes the entire industry’s transformation towards environmental protection and efficiency. However, logistics enterprises encounter technical bottlenecks, capital shortages, and insufficient talent and infrastructure when implementing green innovation. Collaboration between universities and industries serves as a crucial method for logistics companies to access external resources and plays a significant role in promoting technological progress, knowledge transfer, and innovation capability enhancement of enterprises. This research, grounded in the theories of social capital and dynamic capabilities, explores the mechanism from the perspective of resources and capabilities, and examines how university–industry collaboration affects green innovation. This research employs a hierarchical regression model to evaluate the proposed hypotheses. The research results show that university–industry collaboration has a positive impact on social capital, slack resources, and dynamic capabilities, and social capital, slack resources, and dynamic capabilities positively influence green innovation. The research results have certain reference value for logistics enterprises to promote green innovation. Full article

This study investigates the transfer of rural land contracting rights in Shandong Province, China, employing a mixed methods approach that integrates qualitative policy analysis and quantitative multiple linear regression models based on panel data from 16 prefecture-level cities (collected in 2010–2022). The findings demonstrate that land transfer optimizes resource allocation, enhances agricultural output efficiency, and serves as a critical mechanism for advancing agricultural modernization and rural revitalization. Key drivers, such as agricultural modernization and industrial development, significantly promote land transfer, particularly in coastal areas, while challenges like non-standardized contracts and inadequate farmer protections persist. The study proposes targeted strategies, including strengthening agricultural modernization, enhancing farmer income through non-agricultural industries, and improving institutional frameworks to stabilize the land transfer market. Additionally, it highlights the potential role of rural social workers in addressing contentious issues such as women’s rights, displacement, and access to resources, ensuring equitable and sustainable rural development. These measures aim to accelerate agricultural modernization, promote rural economic growth, and enhance the competitiveness and social well-being of rural areas, providing a robust foundation for policy formulation. Full article