The air conditioning manufacturing industry is characterized by discrete manufacturing features including multiple processes, a wide variety of products, small batch sizes and rapid production cycles. Traditional production lines have been rendered insufficient to meet the rapidly evolving market demands concerning flexibility, efficiency, quality and resource management. To address this challenge, an intelligent production line and operational model has been proposed and validated for air conditioning manufacturing, based on the concept of data-driven, system-integrated, and intelligently-scheduled operations. First, three core hypotheses were formulated based on theoretical considerations. An integrated technical framework was subsequently established, incorporating a cyber-physical system architecture, core assembly processes, four sub-production line systems and an intelligent maintenance platform. Key innovations were implemented in technologies including radio frequency identification traceability, artificial intelligence visual inspection, automated equipment integration, Internet of Things sensing networks, as well as an integrated air-ground coordinated transportation system. Through comparative studies with traditional air conditioner production lines, the intelligent production line was shown to significantly outperform traditional systems in production capacity: daily output increased by 57.6%, cycle time was reduced by 57.6%, workforce requirements decreased by 57.4% and unit per person per hour improved to 3.8 times the original level. Additionally, lighting energy consumption was reduced by an average of 60% and the system achieved substantial improvements in efficiency across six dimensions. The established intelligent air conditioner production line model not only effectively validated the research hypotheses and addressed critical limitations of traditional production lines but also provided theoretical support and technical pathways for the intelligent transformation of the discrete manufacturing industry, demonstrating considerable engineering application value and promotion potential.

[This retracts the article DOI: 10.1021/acsomega.3c07837.].

Driven by global sustainability, minimum quantity lubrication (MQL) has gained increasing prominence in machining due to its advantage in enhancing lubricant utilization efficiency. However, the feasibility of MQL as a sustainable lubrication alternative is currently limited by a lack of enhancement strategies. Meanwhile, though electrostatic field-enabled MQL has been extensively documented, the underlying mechanism of its impact on droplet spreading remains unclear. Previous speculative interpretations of wetting mechanisms based on machining results, as well as findings obtained under simplified conditions, are difficult to generalize to practical scenarios. This study, based on comprehensive phenomenological results, reveals the spreading mechanism of biolubricant droplets, focusing on two dominant factors i.e., corona ions and the droplet's properties. First, the spreading dynamics of dielectric biolubricant droplets under the influence of the electrostatic field were investigated and quantitatively analyzed using the spreading ratio and film retraction height. The results indicate that, compared to the non-field condition, dielectric droplets under corona ions exhibit superior spreading efficiency, primarily attributed to the electric pressure induced by ion accumulation at the film interface. Furthermore, the spreading behavior of modified biolubricant droplets with high chargeability was evaluated, showing a reduction in contact angle under the electrostatic field. The spreading mechanism of modified biolubricants shifts toward outcomes dominated by multiple electrostatic forces. Finally, the shift mechanism of the spreading modes of droplets influenced by electrostatic field was analyzed, and the wetting mechanisms of EMQL were discussed based on its practical parameters. This study provides significant insights into the spreading mechanisms of charged droplets in the machining zone, promoting the development of controllable and efficient MQL while offering new perspectives for energy fields-enabled lubrication.

To achieve extreme weight reduction in new energy vehicles, the deep integration of intelligent equipment with lightweighting strategies has catalyzed a paradigm shift. Light alloys, particularly aluminum and magnesium, have become pivotal materials. Compared to traditional high pressure die casting, integrated giga-casting demonstrates significant advancements, pushing the flow length-to-thickness ratio beyond 500 and requiring clamping forces exceeding 16,000 tons. Nevertheless, the complex physical metallurgy of large-scale structures remains insufficiently understood, which limits the formulation of process specifications and widespread industrial application. Particularly in chaotic filling environments, the intrinsic trade-offs among melt fluidity, solidification shrinkage, and mechanical integrity are difficult to control. To address these challenges, a comprehensive assessment of microstructural evolution and strengthening mechanisms under rapid solidification conditions is provided. Firstly, this paper reveals advanced strengthening mechanisms by detailing the decisive role of casting densification and nonequilibrium solute trapping in activating grain refinement, solid solution strengthening, and unique deformation twinning. Secondly, the distinctive technological evolution towards intelligent casting routes is clarified, demonstrating how thermal management and semi-solid technologies suppress internal porosity below 1.7% and elevate the ultimate tensile strength to the 250-450 MPa range. Furthermore, process optimization strategies are summarized based on material-process-intelligence synergy, including in situ sensing, millisecond-level artificial intelligence defect prediction, and digital twin frameworks. Finally, future development directions are outlined. This review aims to facilitate a deeper understanding of the underlying mechanisms, assist in formulating process specifications, and ultimately achieve a weight reduction of 15 – 20% for automotive structures.

[This retracts the article DOI: 10.1021/acsomega.3c08109.].

Ultrafine grinding (UFG) has emerged as an effective strategy for particle-scale regulation and interfacial activation, and has shown considerable engineering value in food powder processing, release of functional components, and value-added utilization of by-products. During size reduction to the micrometer scale, increases in specific surface area, elevation of surface energy, and microstructural reconstruction often occur simultaneously, thereby markedly affecting dissolution/leaching kinetics, dispersion stability, processing adaptability, and functional performance. However, the links among grinding methods, multi-scale breakage mechanisms, property evolution, and application outcomes remain insufficiently integrated because breakage kinetics, energy dissipation, multiphase flow–particle interactions, and particle agglomeration are highly coupled. In this context, this review focuses primarily on food materials, with traditional Chinese medicinal materials (TCMs) as a supplementary point of comparison, to summarize recent advances in UFG. First, based on the classification of dry and wet routes, various UFG approaches are reviewed with emphasis on their energy-transfer mechanisms, equipment characteristics, material-processing boundaries, and process differences from conventional equipment. Second, from the perspectives of micromechanics, energy consumption, and particle-size evolution, recent advances in fracture and energy theories, multiscale particle mechanics models, CFD–DEM coupling, and population balance modeling are summarized. Furthermore, the effects of UFG on powder morphology, particle-size distribution, flowability, hydration/solubility, and functional properties of food and TCMs are discussed, with particular attention to cell-wall disruption, release of bioactive constituents, structural reconstruction, and over-grinding effects. Finally, recent progress and future directions are reviewed for applications of UFG in enhanced bioactivity, synergistic modification, novel food development, value-added utilization of food by-products, and efficacy enhancement of TCM formulations. This review provides a systematic reference for mechanistic elucidation, model prediction, and engineering application of UFG in food systems.

Milling is widely used in aerospace structures, molds, automotive parts, and other mechanical parts manufacturing fields. However, milling tool wear is a serious constraint on the production quality, cost control, and productivity of parts. Traditional flood milling depends on large quantities of cutting fluid for cooling and lubrication. Although cutting fluid plays an important role in the cutting of metal materials, this large-scale use not only causes serious pollution of the environment but also poses a threat to the health of workers. As an ideal alternative to cutting fluid, eco-friendly lubricant-based Minimum Quantity Lubrication (MQL) is attracting attention for its clean and sustainable properties. However, when it comes to efficiently milling difficult-to-machine materials, MQL technology still faces technical challenges in terms of mechanical and thermal damage, making it difficult to meet stringent surface integrity requirements. To improve the performance of MQL, enhanced MQL technologies including Nano-lubricant Minimum Quantity Lubrication (NMQL), Cold Plasma (CP) enhanced Minimum Quantity Lubrication (CPMQL), Ultrasonic Vibration (UV) enhanced Minimum Quantity Lubrication (UVMQL), and Cryogenic Minimum Quantity Lubrication (CMQL) have been applied to milling processes. This paper reviews the recent research advances in enhanced MQL technologies and elucidates the key scientific issues. First, the tribological and heat transfer mechanisms of the milling area in MQL-assisted milling are summarized, and the bottleneck of insufficient cooling and lubrication is analyzed. Subsequently, the mechanisms of different enhanced MQL-assisted technologies are summarized and revealed, and the Coefficient Of Friction (COF), milling force, milling temperature, and tool wear under different enhanced MQL conditions are comparatively evaluated. Finally, the research gaps and future exploration directions of enhanced MQL-assisted milling technology are envisioned. It makes it convenient for researchers to gain a deeper understanding of the mechanism, tribological behavior, and development trend of enhanced MQL technology.

Minimum quantity lubrication (MQL) machining has gained widespread attention in both academic and industrial research fields as a beneficial technology for improving machining performance and sustainability, due to its low cost and environmental protection. Nevertheless, there is still room for improvement in MQL, such as the lack of research and analysis on the development history of MQL, key authors, and research hotspots. This may be one of the reasons limiting the development of MQL. Based on this, this paper proposes a new bibliometric analysis of MQL research, with the aim of describing current research trends and visualizing the development history and emerging trends of MQL to support researchers in conducting in-depth studies. First, a bibliometric analysis was conducted on 1842 publications related to MQL in the Web of Science (WoS) Core Collection database from 2008 to 2023. Secondly, bibliometric analysis software such as VOSviewer and bibliometrix were used to visualize the annual growth of publications, distribution of research fields, regional distribution, distribution of research institutions, author distribution, highly cited articles, and keywords. The results show that from 19 publications annually in 2008 to 292 publications annually in 2023, there has been a 15-fold increase, with India (550 publications) being the country with the most publications and China (19420 citations) having the highest number of citations. Furthermore, an analysis was conducted on the research hotspot directions represented by keyword classification, summarizing the current research achievements. This paper reveals the development trend, global cooperation pattern, basic knowledge, research hotspots, and emerging frontiers of MQL.

With the continuous improvement of contemporary demands for air conditioning quality, the upgrade of air conditioning production lines is imperative. The assembly of central air conditioning outdoor units is a key link in the intelligent upgrade of the air conditioning manufacturing industry, and its level of automation and intelligence directly affects product quality and production efficiency. However, traditional production lines suffer from low levels of automation, insufficient positioning accuracy, and delayed material replenishment, which restrict the high-quality development of the industry. Therefore, based on the cyber-physical system architecture, this study systematically constructs an integrated solution for an intelligent production line. Specifically, an overall production line architecture incorporating high-precision positioning devices and flexible execution units is designed, and a flexible fixture featuring a composite positioning system and an adaptive pneumatic system is proposed, thereby achieving precise positioning and reliable clamping of workpieces during transmission and assembly. Furthermore, a real-time material replenishment system integrating automated guided vehicles, machine vision, and 5G communication is developed, enabling rapid response and accurate replenishment for material shortages through dynamic perception and intelligent scheduling. Through data comparison, this solution has increased the overall efficiency of the production line by 57%.

Electrostatic field-driven minimum quantity lubrication (EMQL) demonstrates unique advantages in enhancing lubrication and cooling performance of droplet. However, while considerable research has focused on evaluating the machining performance of EMQL, the underlying charging mechanisms and atomization dynamics of bio-based lubricants remain unclear. This study introduces a novel charging nozzle that employs both contact and corona charging mechanisms. It then investigates the charging mechanisms of biolubricants based on electric field distribution characteristics. Furthermore, the charging, atomization, and spreading performance of various biolubricants are experimentally evaluated. The results demonstrate that the combined contact-corona charging nozzle significantly enhances surface charge density in both droplets and the cutting zone, compared to conventional contact charging nozzles. Biolubricants with high electric conductivity additives show superior charging properties over pure vegetable oil. Increasing the applied voltage from 0 to 35kV leads to substantial reductions in mean droplet diameter: 28.83% for rapeseed oil, 38.94% for lecithin-oil mixture, 35.76% for WS2 nanofluids, and 38.28% for CNT nanofluids. Atomization dynamics analysis reveals that the presence of charges on droplet surfaces and the electric field at the nozzle both contribute to enhancing the atomization performance of biolubricants. However, higher conductivity accelerates interfacial charge release, which inhibits electrically driven droplet spreading. This study provides valuable insights into the EMQL mechanism through experimental and theoretical analysis, expanding the potential applications of charged biolubricants in clean manufacturing and tribology.

Multi-source errors, as critical obstacles limiting the accuracy retention and machining performance of machine tools, hold fundamental and strategic significance for achieving high-precision, high-efficiency, and high-reliability machining in modern manufacturing systems. However, these errors typically exhibit complex characteristics such as strong coupling, time-variance, and nonlinearity, which challenge traditional methods of error identification, modeling, and compensation in terms of adaptability, real-time capability, and integration. Therefore, it is imperative to establish a systematic and intelligent multi-source error control framework. Firstly, this work systematically reviews typical error sources and their evolution mechanisms, evaluates multi-scale detection technologies including laser interferometry, double ball-bar systems, multi-sensor fusion, and vision-based systems, and constructs an intelligent error identification and evaluation framework. Next, it reviews classical modeling methods such as homogeneous transformation matrices, screw theory, thermal equilibrium models, finite element analysis, and modal analysis, compares physical modeling, data-driven, and hybrid modeling strategies, and develops an integrated multi-source error modeling architecture centered on digital twin technology and artificial intelligence. Furthermore, key technologies including geometric error mapping and real-time compensation, online thermal error prediction and active temperature control, dynamic error suppression, and adaptive control are summarized. A multi-level integrated error compensation architecture is proposed by combining physical models, data models, and cyber-physical synchronization. This architecture encompasses core processes such as error traceability and decoupling, dynamic prediction, real-time compensation, and closed-loop optimization, emphasizing engineering implementation mechanisms based on cyber-physical collaboration, multi-physics coupling, and multi-scale fusion, thereby effectively enhancing accuracy stability and control robustness under complex operating conditions. Finally, frontier challenges such as constructing high-fidelity coupled models from heterogeneous multi-source data, edge–cloud collaborative control, and cross-platform interoperability are discussed. The application prospects of multi-source error evaluation are also envisioned, providing theoretical foundations and technical support for the precise management and optimization of the entire lifecycle accuracy of machine tools.

FeCoNiCrMn high-entropy alloy (HEA) is widely applied in aerospace components such as turbine blades, wing structures, and fuselage frames. High-speed grinding (HSG) is critical to achieving superior surface integrity during machining. However, its underlying removal mechanisms remain poorly understood due to limited research on surface integrity and the absence of a defined constitutive model for high-speed processes. In this study, an integrated experimental and numerical framework was developed to analyze the material removal mechanisms and surface integrity evolution of FeCoNiCrMn HEAs under HSG. First, the high-strain-rate fracture mechanism was characterized through stress-strain curves, and a Johnson-cook constitutive model was established by fitting grinding-wheel peripheral speed to the model parameters. Second, fracture criteria derived from the constitutive model were incorporated into a numerical simulation to clarify chip formation, grinding-force evolution, and material removal mechanisms at different wheel speeds. Finally, HSG experiments were performed to examine the effects of wheel speed and grinding depth on grinding forces, surface roughness, workpiece morphology, and EBSD-measured microstructural and plastic-deformation-layer variations. Results show that increasing wheel peripheral speed reduces surface roughness by 2.05 mu m, mitigates surface defects, and enhances surface integrity, although grinding forces increase correspondingly. Conversely, increasing grinding depth initially elevates and then decreases grinding forces, while surface roughness (Ra) rises by 0.50 mu m, surface defects intensify, and overall integrity declines. EBSD analysis reveals a subsurface plastic-deformation zone <= 10 mu m thick, confined by the alloy's high hardness and strength, which limit deformation during grinding. This work establishes a theoretical and experimental foundation for understanding the HSG removal mechanisms of FeCoNiCrMn HEAs and provides technical guidance for achieving high surface integrity in machining difficult-tocut high-entropy alloys.

To improve the inadequate Infiltration performance during the process of large arc length grinding, this study proposes a novel minimum quantity lubrication (MQL) grinding method based on magnetic traction nano-lubrication (MTN). By utilizing magnetic fields to enhance lubricant wettability in the grinding zone, the proposed approach improves friction-reduction and anti-wear performance in high-temperature and high-friction environments. A simulated grinding platform was established to investigate the tribological behavior of MTN through systematic friction and wear experiments. First, a novel Fe3O4/graphene magnetic nano-lubricant was synthesized, and the influence of magnetic field strength on its viscosity was investigated. Subsequently, an experimental validation study of the magnetic nanolubricant was conducted, comparing the properties of composite magnetic nanoparticles at different concentrations. Results showed that the friction coefficient curve of the hybrid nano-lubricant was significantly smoother, abrasion mark width was substantially reduced, and surface adhesion was markedly improved. Finally, an optimization study on the ratio of Fe3O4/GR was conducted to achieve optimal performance and economic efficiency. At a 2:1 Fe3O4/GR ratio, the lubricant demonstrated the lowest average friction coefficient (0.32), the smallest wear area (6146 mu m(2)), and the best surface roughness (1.64 mu m). This method offers a promising strategy and experimental basis for optimizing lubrication technology in precision machining.

The tubular gas-liquid atomizing mixer is a compact and high-efficiency gas-liquid contact device. It generates high-speed gas flow through a variable cross-section channel, atomizes liquid absorbent into micro-nano droplets to enhance gas-liquid mass transfer, and its performance directly determines the achievement of design objectives. This study proposes a tubular gas-liquid atomizing mixer with a "rhombic cone + boss" structure. Combining CFD simulation and experimental tests, it investigates the effects of gas Weber number (Weg) and liquid-gas momentum flux ratio (q) on gas-liquid atomization and mixing characteristics. The results show that the variable cross-section channel can increase gas flow velocity and induce intense turbulence inside the tube, promoting the mixing of gas-microdroplet two phases. Weg has a significant impact on droplet size and volume concentration: when Weg increases from 212.46 to 524.64, the droplet size decreases by 46.1 % and the volume concentration increases by 170 %. q affects mixing performance by changing the penetration depth of the liquid jet, with the optimal performance achieved when q=28.79, but its influence on droplet characteristics is weaker than that of Weg. The structural layout of combining variable cross-section flow channel with central bluff body can provide a solution for high-efficiency tubular gas-liquid atomizing mixers, facilitating industrial applications such as natural gas water dew point control.

The as-cast state of Al-Cu-Li alloys generally necessitates a homogenization treatment to achieve a uniform microstructure, which effectively alleviates severe elemental segregation. However, during homogenization, the specific mechanisms by which micro-alloying elements influence the homogenization kinetics and the evolution of microstructural constituents remain insufficiently understood. In the present paper, four Al-Cu-Li alloys with designed Mg/Zn contents were prepared. The microstructural characteristics and the evolution of microstructural constituents during homogenization were systematically characterized, using optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), electron probe micro-analysis (EPMA), differential scanning calorimetry (DSC), and the application of Scheil solidification modeling. The results demonstrate that Mg significantly retards the homogenization process by stabilizing high-melting-point intermetallic phases, such as Al7Cu3Mg6, and impeding solute diffusion. In contrast, Zn promotes the dissolution of non-equilibrium intermetallic phases and lowers the required homogenization temperature, primarily by facilitating the formation of low-melting-point Zn-containing phases (e.g., Al2Zn). When Mg and Zn are simultaneously added to the alloy, complex microalloyed intermetallic compounds such as Mg-32(Al, Zn)(49) are formed. That leads to a non-monotonic dependence of homogenization difficulty on the Mg/Zn ratio, characterized by an initial decrease followed by an increase. The study systematically clarifies the opposing roles and interactive effects of Mg and Zn during the homogenization of Al-Cu-Li alloys, thereby providing a theoretical foundation for optimizing alloy composition and heat treatment parameters.

In the precision cutting of difficult-to-process metals, surface thermal damage to a workpiece is a significant technical challenge. Although clean minimum quantity lubrication (MQL) technology, which replaces traditional pouring cooling, is used, inadequate heat dissipation remains an issue. Cryogenic air MQL (CAMQL), an eco-friendly technology, can enhance the heat transfer performance of the lubricating film in the cutting zone, offering excellent cooling and lubrication effects. However, the influence of jet and temperature parameters on the average particle size and distribution characteristics of atomized droplets is not well understood. This study first analyzes the evolution of lubricant physical properties and establishes a quantitative mapping relationship between cryogenic air temperature and physical parameters of lubricant. Next, the unstable fluctuation in the annular liquid film at the two-phase flow nozzle exit is observed and analyzed. A thickness model of annular liquid film is developed, revealing the effect of airflow field on the annular liquid film. Finally, a model for the average particle size of atomized droplets under CAMQL is established. Numerical analysis and validation experiments under different working conditions show that the measured values align with the theoretical values. Under an air pressure of 0.4 MPa and an air flow temperature of −50 °C, the droplet particle size is 133.5 μm, with an error of 8.2%. The effect of air pressure on particle size is greater than that of air flow temperature. Additionally, the distribution spans of droplet size under different conditions are analyzed, and the results demonstrated that low temperatures help shorten the interval between particle sizes and improve the relative uniformity of particle size distribution. This research provides a theoretical basis for the application of CAMQL technology in the cutting process.

High-temperature-resistant and chemically stable ceramic materials exhibit great adaptability across numerous industrial applications. Grinding is an essential component of the precision shaping and manufacturing processes for ceramic structural components. However, the low machining efficiency and high machining damage rate caused by hard and brittle material properties have been a challenge in both academia and industry. Grinding force is the most critical parameter reflecting the grinding system, and establishing an accurate prediction model is highly significant in reducing machining damage. However, a knowledge gap remains in the comprehensive review and evaluation of grinding force models for ceramic materials, which is undoubtedly not conducive to further theoretical advances. This review discusses the removal mechanism for polycrystalline ceramic materials. Subsequently, it comprehensively reviews and comparatively evaluates detailed grinding force modeling knowledge. Furthermore, it explores the specificities of the ultrasonic and laser energy-field-assisted grinding of ceramic materials in terms of their physical behavior and mechanical modeling. Finally, the theoretical value of grinding force modeling for predicting the damage to ceramic materials is explored. The current limitations of the grinding process, mechanical modeling of ceramic materials, corresponding potential research directions, and valuable research content are provided. The goal is to derive actionable low-damage grinding guidelines and establish a robust theoretical framework that enhances the quality of grinding processes for ceramics and other hard and brittle solids.

Electrospinning is a key technique for producing nanofibers used in bone tissue engineering. Electrospinning methods, materials, and parameters affect bone scaffold properties and efficacy. However, there is currently a lack of systematic reviews, and the influence of electrospinning forms, scaffold types, and their parameters on scaffold performance remains unclear, making it difficult for researchers to obtain effective references. Therefore, this paper reviews the applications of electrospun scaffolds in bone tissue engineering. Firstly, it summarizes various electrospun scaffold fabrication methods and their principles, including conventional, blend, melt, coaxial, emulsion, solution, free surface, and improved techniques. Based on differences in scaffold structure, this paper further classifies scaffolds into multilayer, grid, and tubular types, analyzing the advantages and limitations of electrospinning processes and scaffold types, and discussing related scaffolds. Future research should focus on material, structural, and solvent optimization to improve scaffold performance. Secondly, this paper discusses the material characterization and applications of electrospun scaffolds in bone tissue engineering, emphasizing the need for performance optimization for improving bone repair. Finally, it proposes future research directions to address current challenges. This paper aims to provide systematic guidance and technical support for the application of electrospinning technology in bone tissue engineering.