With the continuous advancement of science and technology, alongside the increasing significant attention within the manufacturing industry, high-performance demands are placed on advanced equipment and components because of extreme temperatures, heavy impact loads, and other challenging operating conditions. The importance of resource conservation and environmental preservation is becoming more widely recognized. This paper reviews green machining technology, driven by digital intelligence. Initially, the background of green machining powered by digital technologies is introduced, focusing on digitalization, intelligence, and sustainability as key factors for improving machining efficiency, enhancing product performance, and minimizing both energy consumption and environmental pollution. Subsequently, the paper elaborates on the current research and development in digital intelligence-driven green machining technologies, highlighting four critical areas: smart toolholders, minimal quantity lubrication (MQL), machine tool compensation, machine tool energy consumption monitoring, and intelligent carbon emission control. Lastly, the future trends and challenges in these technologies are discussed, with an outlook on the growing importance of green machining in response to technological advancements and evolving market demands.
Computer-aided engineering (CAE) is widely used in the industry as an approximate numerical analysis method for solving complex engineering and product structural mechanical performance problems. However, with the increasing complexity of structural and performance requirements, the traditional research paradigm based on experimental observations, theoretical modeling, and numerical simulations faces new scientific problems and technical challenges in analysis, design, and manufacturing. Notably, the development of CAE applications in future engineering is constrained to some extent by insufficient experimental observations, lack of theoretical modeling, limited numerical analysis, and difficulties in result validation. By replacing traditional mathematical mechanics models with data-driven models, artificial intelligence (AI) methods directly use high-dimensional, high-throughput data to establish complex relationships between variables and capture laws that are difficult to discover using traditional mechanics research methods, offering significant advantages in the analysis, prediction, and optimization of complex systems. Empowering CAE with AI to find new solutions to the difficulties encountered by traditional research methods has become a developing trend in numerical simulation research. This study reviews the methods and applications of combining AI with CAE and discusses current research deficiencies as well as future research trends.
Nano-lubricant minimum quantity lubrication (NMQL) is an eco-friendly precision technology used for grinding challenging aerospace materials. However, its film-forming ability and anti-friction performance in high-speed and high-pressure grinding zones cannot satisfy the processing requirements. To address this limitation, a novel method using magnetic traction nano-lubricant was investigated. By applying an external magnetic field, a gradient magnetic field is formed on the surface of the grinding wheel to absorb the magnetic lubricant and improve the infiltration performance. A permanent magnet was used to magnetize the grinding wheel matrix, thereby directing the magnetic flux lines and guiding the distribution of the magnetic field through the grinding wheel. Hence, the magnetic field distribution was numerically simulated by adjusting the distribution, geometric position, and parameters of the permanent magnet. In type I (wherein there is repulsion between the N-S poles on the left and right), a uniform and strong magnetic field can be generated when L=6–16 mm, β=0°–30°, and H is suitably increased. This set up can achieve a maximum magnetic field intensity of 1.1×105 A/m. Furthermore, the impact of the geometrical parameters (L, H, and β) of the magnetic-assisted device on the grindability of Ti-6Al-4V was examined using an orthogonal experiment. The optimum parameters for the permanent magnet arrangement and the geometric position were L=12 mm, H=10 mm, and β=0°, thereby resulting in a smoother workpiece with fewer defects.
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.
Over the past decades,the substantial carbon emissions resulting from energy-intensive manufacturing processes,which heavily rely on non-renewable resources,have increasingly attracted significant academic and industrial attention.In response,sustainable and green manufactur-ing technologies have gained prominence in the machining industry,primarily driven by international strategies target-ing"peak carbon dioxide emissions".
Cutting chatter is a major factor that limits machining efficiency and can negatively impact the quality of a cutting surface. Chatter suppression is crucial for improving machining efficiency and maximizing business benefits. However, most chatter suppression techniques are difficult to use on a massive scale in actual production because of their high cost and limited applicability. In the investigation of chatter suppression, particularly in recent years, unique and effective suppression methods have been developed that must be summarized and arranged, and their advantages and disadvantages must be evaluated in depth. Therefore, this paper summarizes and systematically discusses recent research advancements in chatter suppression methods. Furthermore, future research directions for chatter suppression technologies are predicted.
Wire arc additive manufacturing (WAAM) is an economical and efficient technology for manufacturing large metal parts with complex physical states that are difficult to observe in situ. However, in-depth systematic research on the fluid flow state and droplet transition behavior in WAAM under complex paths is lacking. Firstly, the free surface of the molten pool was tracked using the volume-of-fluid (VOF) method. Subsequently, by integrating matrix transformation methods, the dual ellipsoidal heat source was varied over time, and its dynamic effects on the molten pool were studied. Finally, the shapes and sizes of the deposited bead and weld pool were determined. The results showed that the droplets brought heat and kinetic energy to the molten pool and that the kinetic energy of the molten pool was more easily dissipated on complex paths than on straight paths. The impact of droplets on the molten pool, creating a negative pressure, is one of the reasons for the precipitation of gas and the eventual formation of a unique bubble distribution. The primary reason for the tilt of the molten pool in the moving direction was the influence of the liquid tension and arc pressure. The simulated profiles of the deposited bead and droplet transfer are validated using experimental cross-sectional and high-speed camera images. The consistency between the simulation results and the experimental outcomes was good, aiding the precise control of specific requirements in future production.
Instantaneous material removal volume (IMRV) is a key parameter for predicting the cutting power, cutting force, and machining process. This paper presents a novel approach, known as the point cloud contour-filling method, for calculating the IMRV for each cutting tool edge at any instantaneous moment. Firstly, the kinematics during milling operations are analyzed to capture the exact motion trajectory envelope point cloud of the cutting tool edge. Secondly, the Z-map algorithm and Boolean operations are utilized to calculate the point cloud of the intersection between the workpiece and tool-edge trajectory envelope within unit time steps Δt (known as the IMRV point cloud). Finally, the 3D alpha method and Delaunay triangulation are employed to calculate the shape and volume of the IMRV. The proposed model considers the real tool-edge trajectory and tool installation errors, and introduces the variable of tool-workpiece engagement time t for the first time. The model is verified using milling tests. The proposed method provides a visualization of instantaneous complex engagement between the tool and workpiece during the milling process and can be further used for simulating milling forces and cutting power.
High-shear and low-pressure grinding with a body-armor-like grinding wheel is a novel grinding method with great potential for ultraprecision machining of difficult-to-cut materials. However, the material removal rate model for the new grinding process is still lacking. In this study, elastohydrodynamic pressure distribution at the working interface between a body-armor-like grinding wheel and the workpiece was revealed. The microcontact state of the single abrasive grain in the interface was uncovered. The formulas of the forces acting on the rubbing, plowing, and cutting abrasive grain were analyzed. Based on the force model of the single abrasive grain and the Gaussian distribution of the grain protrusion heights, the actual grinding depth of the cut model and specific removal rate model were proposed for the novel high-shear and low-pressure grinding process. The influence of the grinding wheel and processing parameters on the material removal rate was investigated. It was found that the actual cut grinding depth decreased with the increase of the workpiece feed rate while the material removal rate remained almost constant. By comparing with experimental and theoretical results, it was shown that the model could accurately predict the actual grinding depth of cut and specific removal rate under different processing parameters, with a minimum prediction error of 1.5%. The maximum actual grinding depth of cut (i.e., 0.60 μm), was obtained for Inconel 718 workpiece. The findings of this study provide theoretical guidance for the practical application of high-shear and low-pressure grinding.
This investigation examines the impact of diverse interatomic potentials on the molecular dynamics simulation results of deformation and microstructural evolution during nanomachining. The results revealed that the application of the Stillinger-Weber (SW) potential led to the occurrence of significant stacking faults and dislocations. Conversely, the Tersoff potential prevented the initiation of dislocations during the loading segment. The Tersoff potential adept representation of the high-pressure phase transformation of monocrystalline silicon throughout the nanoindentation more accurately predicted mechanical parameters when compared with experimental data. Analytical bond-order potential (ABOP) accurately delineated the deformation mechanisms, including dislocation nucleation and amorphization, during nanoscratching. In contrast, the SW potential tended to underestimate the generation of high-pressure phases, with dislocation nucleation predicted by the SW potential dominating the plastic deformation of monocrystalline Si, contradicting the experimental observations. Consequently, this study concludes that the Tersoff potential and ABOP are the preferred choices for investigating the behavior of monocrystalline Si under nanomachining conditions.
This paper studies the impact of green fiscal rules-designed to protect climate-related spending-on debt dynamics.Simulations of green rules that exempt green spending from the rule limits for an emerging market economy illustrate that they can lead to unsustainable debt dynamics when the net zero emissions goal is pursued mostly using spending-based instruments(e.g.,investment and subsidies).Or the rule would need to implicitly assume a large fiscal adjustment in the non-green budget,which would undermine its credibility.It will be needed to build broad public consensus for a more comprehensive fiscal strategy that tackles the difficult policy tradeoffs that will be required and takes into account long-term effects.A more appropriate mix of climate policies,including actively employing carbon pricing,should be pursued within the overall setting of fiscal and debt objectives.Developing"green"medium-term fiscal frameworks would help to integrate climate change considerations into fiscal policy design in a more comprehensive manner.
High-quality development in the manufacturing industry is often accompanied by high energy consumption. The accurate prediction of the energy consumption of computer numerical control (CNC) machine tools, which plays a vital role in manufacturing, is of great importance in energy conservation. However, the existing research ignores the impact of multi-factor energy losses on the performance of machine tool energy consumption prediction models. The existing models must be selected and verified several times to determine the appropriate hyperparameters. Therefore, in this study, a machine tool energy consumption prediction method based on a mechanism and data-driven model that considers multi-factor energy losses and hyperparameter dynamic self-optimization is proposed to improve the accuracy and reduce the difficulty of hyperparameter tuning. The proposed multi-factor energy-loss prediction model is based on the theoretical prediction model of machine-tool cutting energy consumption. After creating the model, a hyperparameter search space embedding a tree-structured Parzen estimator (TPE) was designed based on Hyperopt to dynamically self-optimize the hyperparameters in the deep neural network (DNN) model. Finally, two sets of experiments were designed for verification and comparison with the theoretical and data models. The results showed that the energy consumption prediction performances of the proposed hybrid model in the two sets of experiments were 99% and 97%.
Silicon carbide fiber-reinforced silicon carbide composites are preferred materials for hot-end structural parts of aero-engines. However, their anisotropy, heterogeneity, and ultra-high hardness make them difficult to machine. In this paper, 2.5-dimensional braided SiCf/SiC composites were processed using a nanosecond pulsed laser. The temperature field distribution at the laser ablated spot is analyzed through finite element modeling (FEM), and the ablation behavior of the two main components, SiC fiber and SiC matrix, is explored. A plasma plume forms when the pulse energy is sufficiently high, which increases with growing energy. The varied ablation behavior of the components is investigated, including the removal rate, ablative morphology, and phase transition. The ablation thresholds of SiC matrix and SiC fiber are found to be 2.538 J/cm2 and 3.262 J/cm2, respectively.
To enhance the performance of aero-engines, honeycomb seals are commonly used between the stator and rotor to reduce leakage and improve mechanical efficiency. Because of the thin-walled and densely distributed honeycomb holes, machining defects are prone to occur during manufacturing. Electrochemical grinding (ECG) can minimize machining deformation because it is a hybrid process involving electrochemical dissolution and mechanical grinding. However, electrolysis will generate excessive corrosion on the honeycomb surface, which affects the sealing capability and operational performance. In this study, an ECG method using an electrolyte of 10% (mass fraction) NaCl is proposed to machine the inner cylindrical surface of the honeycomb seal, and an eco-friendly inhibitor, sodium dodecylbenzene sulfonate (SDBS), is introduced to the electrolyte to inhibit corrosion of the honeycomb structure. A theoretical relationship between the voltage and feed rate during ECG is proposed, and the excessive corrosion of the honeycomb single-foiled segment is used as a measurement of the impact of electrolysis. The corrosion inhibition efficiency of SDBS on the honeycomb material in 10% (mass fraction) NaCl solution is evaluated through electrochemical tests, and the suitable feed rate and optimal concentration of SDBS are determined through ECG experiments. Additionally, the corrosion inhibition effect of SDBS is validated through four groups of comparative experiments. The results indicate that the inhibition efficiency of SDBS increases with increasing concentration, reaching the maximum of 73.44%. The optimal SDBS mass fraction is determined to be 0.06%. The comparative experiments show that excessive corrosion is reduced by more than 40%. This establishes ECG as an effective and environmentally friendly processing method for honeycomb seals by incorporating SDBS into a 10% (mass fraction) NaCl solution.
Micro-milling has been extensively employed in different fields such as aerospace,energy,automobiles,and healthcare because of its efficiency,flexibility,and versa-tility in materials and structures.Recently,nanofluid mini-mum quantity lubrication(NMQL)has been proposed as a green and economical cooling and lubrication method to assist the micro-milling process;however,its effect is limited because high-speed rotating tools disturb the surrounding air and impede the entrance of the nanofluid.Cold plasma can effectively enhance the wettability of lubricating droplets on the workpiece surface and promote the plastic fracture of materials.Therefore,the multifield coupling of cold plasma and NMQL may provide new insights to overcome this bot-tleneck.In this study,experiments on cold plasma+NMQL multifield coupling-assisted micro-milling of a7075-T6 alu-minum alloy were conducted to analyze the three-dimen-sional(3D)surface roughness(Sa),surface micromorphol-ogy,burrs of the workpiece,and milling force at different micro-milling depths.The results indicated that,under cold plasma+NMQL,the workpiece surface micromorphology was smooth with fewer burrs.In comparison with dry,N2,cold plasma,and NMQL,the Sa values at different cutting depths(5,10,15,20 and 30 μm)were relatively smaller under cold plasma+NMQL with 0.035,0.036,0.041,0.043 and 0.046 μm,which were respectively reduced by 38.9％,45.7％,45.9％,47％and 48.9％when compared to the dry.The effect of cold plasma+NMQL multifield coupling-assisted micro-milling on enhancing the workpiece surface quality was analyzed using mechanical analysis of tensile experiments,surface wettability,and X-ray photoelectron spectroscopy(XPS).
Owing to the hard brittle phase organization in their matrixes,brittle materials are prone to the forma-tion of pits and cracks on machined surfaces under extreme grinding conditions,which severely affect the overall per-formance and service behavior of machined parts.Based on the electroplastic effect of pulsed currents during material deformation,this study investigates electroplastic-assisted grinding with different electrical parameters(current,fre-quency,and duty cycle).The results demonstrate that com-pared to conventional grinding,the pulsed current can signif-icantly decrease the surface roughness(Sa)of the workpiece and reduce surface pits and crack defects.The higher the pulsed current,the more pronounced the improvement in the surface quality of the workpiece.Compared to traditional grinding,when the pulsed current is 1 000 A,Sa decreases by 46.4％,and surface pit and crack defects are eliminated.Under the same pulse-current amplitude and frequency conditions,the surface quality continues to improve as the duty cycle increases.When the duty cycle is 75％,Sa reaches a minimum of 0.749 μm.However,the surface quality is insensitive to the pulsed-current frequency.By investigating the influence of pulsed electrical parameters on the surface quality of brittle material under grinding conditions,this study provides a theoretical basis and technical support for improving the machining quality of hard,brittle materials.
Ti2AlNb intermetallic alloys, which belong to the titanium aluminum (TiAl) family, are currently being extensively researched and promoted in the aerospace industry because of their exceptional properties, including low density, high-temperature strength, and excellent oxidation resistance. However, the excellent fracture toughness of the material leads to the formation of surface defects during machining, thereby affecting the quality of the machined surface. In this study, Ti2AlNb intermetallic alloys were subjected to side-milling trials to investigate the influence of tool coating and tool wear on both the machined surface quality and chip morphology. Specifically, the tool life, machined surface roughness, surface morphology, surface defects, and chip morphology were investigated in detail. The results indicated that the tool coating provided a protective effect, resulting in a threefold increase in the service life of the coated end mill compared to that of the uncoated one. A coated end mill yields a superior machined surface topography, as evidenced by reduced roughness and a more consistent morphology. Tool wear has a significant effect on the morphology of machined surfaces. The occurrence of material debris and feed marks became increasingly severe as the tool wore off. The chip morphology was not significantly affected by the tool coating. However, tool wear results in severe tearing along the chip edge, obvious plastic flow on the non-free surface, and a distinct lamellar structure on the free surface.
Currently quality information management of the ready-mixed concrete (RMC) is manually operated, facing risks like poor traceability, information tampering, and fragmentation in the RMC supply chain. To this end, this study proposes a Blockchain-IPFS (interplanetary file system)-enabled information management platform for improving transparency, traceability, and effectiveness of RMC quality management. Specifically, through a semi-structured interview investigating the potential benefits and applications of Blockchain, a transformative Blockchain-based management mode for RMC quality management is constructed. Based on that, a novel Blockchain-based architecture is further proposed by integrating with IPFS and cloud service for addressing its data storage limitation. Furthermore, the information flows and smart contracts representing physical and cyber interactions among multiple supply chain stakeholders are illustrated in detail. Finally, a real-world case study is presented to verify the feasibility of the proposed model. A prototype system is established with solutions for client-cloud collaboration, multi-source data fusion, and enterprise privacy protection, detailing the practical application of proposed model in actual projects. The evaluation results indicate that the proposed model can improve the quality management of RMC supply chain from three aspects: transparency, traceability, and information sharing. This paper contributes to the body of knowledge by offering a novel architecture leveraging both Blockchain and IPFS in storing small-sized and large-sized information. Meanwhile, this research moves beyond conceptual framework and implements the theoretical benefits of Blockchain into engineering practice. Technical components in this paper can be adapted for multiple applications in the construction industry, providing valuable references for future search efforts.
This paper offers a comprehensive analysis of the implications for financial stability of a central bank issuing a digital currency to the public at large.We start with a systematic analysis of balance sheet changes that arise from the new liability for the central bank and the banking system,and examine how they depend on preconditions,central bank choices,and banking system responses.Based on this,we discuss the range of implications for financial stability that may arise in steady state,in the context of adoption,and in crisis times.Threats to financial intermediation in steady state arise mainly in situations where the central bank balance sheet expands,and triggers adjustment mechanisms that lead to more costly or less stable funding of the banking system,while in crisis times run risk may increase.Our analysis of policy choices to control these effects considers macroprudential policy,and an expansion of central bank lending to commercial banks,but finds that a main contribution needs to come from a design of the CBDC that encourages its use as a means of payment rather than a store of value.
High-speed grinding(HSG)is an advanced tech-nology for precision machining of difficult-to-cut materi-als in aerospace and other fields,which could solve surface burns,defects and improve surface integrity by increasing the linear speed of the grinding wheel.The advantages of HSG have been preliminarily confirmed and the equipment has been built for experimental research,which can achieve a high grinding speed of more than 300 m/s.However,it is not yet widely used in manufacturing due to the insuf-ficient understanding on material removal mechanism and characteristics of HSG machine tool.To fill this gap,this paper provides a comprehensive overview of HSG technolo-gies.A new direction for adding auxiliary process in HSG is proposed.Firstly,the combined influence law of strain hardening,strain rate intensification,and thermal soften-ing effects on material removal mechanism was revealed,and models of material removal strain rate,grinding force and grinding temperature were summarized.Secondly,the constitutive models under high strain rate boundaries were summarized by considering various properties of material and grinding parameters.Thirdly,the change law of material removal mechanism of HSG was revealed when the ther-modynamic boundary conditions changed,by introducing lubrication conditions such as minimum quantity lubrica-tion(MQL),nano-lubricant minimum quantity lubrication(NMQL)and cryogenic air(CA).Finally,the mechanical and dynamic characteristics of the key components of HSG machine tool were summarized,including main body,grind-ing wheel,spindle and dynamic balance system.Based on the content summarized in this paper,the prospect of HSG is put forward.This study establishes a solid foundation for future developments in the field and points to promising directions for further exploration.
