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Thin-walled micro-holes are frequently used in aerospace components to achieve specific functions, such as heat dissipation and filtration. However, traditional manufacturing technologies face difficulties in achieving precision machining of these holes due to deformation caused by cutting force or heat. Laser machining is a highly flexible and efficient advanced processing technology that aims to achieve precise machining of thin-walled holes. However, it is important to note that the thermal energy generated by the laser can cause deformation of the thin walls. To address these issues, this paper proposes a process that combines laser and backside electrochemical composite machining. The model for laser electrochemical composite processing after through-hole formation suggests that the laser's temperature rise effect on the electrolyte can significantly enhance the efficiency of electrochemical processing. Furthermore, the laser exerts a micro-zone stirring effect on the electrolyte in the processed micro-zone, which promotes the liquid-phase mass transfer process during the electrochemical reaction. Furthermore, a one-way experiment was conducted to investigate the effects of the main laser parameters on the processing results. The results indicated that higher laser power, as well as lower laser frequency and scanning speed, significantly reduced the edge damage and pore taper of the processed micro-holes. The language used is clear, concise, and objective, adhering to a formal register and avoiding biased or ornamental language. Technical terms are consistently used and explained when first introduced. The text is grammatically correct and free from spelling and punctuation errors. Furthermore, this process has significantly reduced the oxygen content and surface roughness of the sidewalls of the micro-holes. [ABSTRACT FROM AUTHOR]

In this paper, an experimental investigation of the machinability of Titanium grade 23 has been carried out using hybrid micro-textures on the cutting tool. The different types of micro-textures have been fabricated on the rake surface as well as on the flank surface of the cutting tool. The performance of textured tools with the presence of a chip breaker has been investigated. The selected patterns were vertical grooved rake face (VT-R), diagonal grooved rake face (DT-R), vertical grooved flank face (VT-F) and hybrid textured tools namely, vertical rake and flank (V+V), diagonal rake and vertical flank (D+V). A comparative study has been carried out to acknowledge the performance of textured tools while dry turning Titanium Grade 23 alloy. The machinability has been made to acknowledge the performance of textured tools with the variation of machining time in case of dry turning operation. The machinability criteria are investigated based on cutting forces, cutting temperature and tool wear mechanisms involved while machining. The performance of the cutting tool with DT-R and VT-F micro-texture is observed to be better in comparison to others. Innovative applications of micro-textured tools are for dry green machining without any environmental hazards and proper chip-flow control. [ABSTRACT FROM AUTHOR]

Cutting force analysis in milling processes is essential for precision metal cutting as it contributes to understanding tool wear, optimising machining performance, and ensuring overall process stability. Numerous research papers have been published to describe modelling techniques that provide high-fidelity predictions, with recent developments highlighting the benefits of combining different methods. However, these approaches are relatively limited in their ability to predict over the wide frequency range needed to describe the tooth passing frequency (TPF) and its harmonics under varying working conditions or stages of cutter-workpiece engagement (CWE). This paper studies the prediction performance of different modelling techniques when considering wide-band noise under varying working conditions. The methods evaluated are the explicitly defined but difficult-to-parameterise Finite Element Method (FEM), Semi-Analytical Solutions (SAS), and Long Short-Term Memory (LSTM) networks, which are black-box deep learning methods incorporating time-based information. Since white-box models are still more readily adopted by industry, the paper also introduces a new post-processing model to improve the prediction accuracy of FEM and SAS based upon the Fourier Series of the TPF (FS-TPF). Over the observable range of 0 to 1500 Hz, the cutting force predictability was assessed in both the time and frequency domains using similarity of frequency distribution, Shannon entropy, and Kullback–Leibler (KL) divergence. Verification and analysis indicate that the cutting force predictability with FEM at "partial engagement" was the lowest, due to its lack of ability to describe TPF harmonics. In contrast, the LSTM model showed the best prediction performance across all tested working conditions. The new FS-TPF significantly increased FEM's prediction accuracy by approximately 50% and improved SAS's performance by 20%. Finally, a Deep Neural Network (DNN) is compared to the LSTM, suggesting that both methods are suitable for force prediction without encountering significant accuracy issues across the different stages of CWE. It was found that the key to increasing cutting force predictability to be generally applicable to all milling conditions is the capability to describe TPF harmonics across the different CWE stages in milling processes. The FS-TPF compensation can dramatically enhance the cutting force prediction accuracy of FEM and SAS, while the applied DL-LSTM and DNN models have successfully demonstrated their wide adaptability without requiring additional post-processing. [ABSTRACT FROM AUTHOR]

Deep learning methods have shown significant potential in tool wear lifecycle analysis. However, there are fewer open source datasets due to the high cost of data collection and equipment time investment. Existing datasets often fail to capture cutting force changes directly. This paper introduces QIT-CEMC, a comprehensive dataset for the full lifecycle of titanium (Ti6Al4V) tool wear. QIT-CEMC utilizes complex circumferential milling paths and employs a rotary dynamometer to directly measure cutting force and torque, alongside multidimensional data from initial wear to severe wear. The dataset consists of 68 different samples with approximately 5 million rows each, includes vibration, sound, cutting force and torque. Detailed wear pictures and measurement values are also provided. It is a valuable resource for time series prediction, anomaly detection, and tool wear studies. We believe QIT-CEMC will be a crucial resource for smart manufacturing research. [ABSTRACT FROM AUTHOR]

Cooling lubricants (CL) are used in various machining processes. In addition to heat dissipation, influencing the tribological system is a key function. In particular, the thermomechanical load on the cutting wedge is influenced by a change in friction in the secondary shear zone. In addition to tribological effects, the mechanical forces of the fluid jet have a significant effect on chip formation, particularly when a high-pressure supply of CL is used. However, investigating the mechanical effect of CL on chip formation is challenging due to poor accessibility of the chip formation zone. Using a planing test rig and a high-speed camera, it is possible to show that the mechanical force of the CL supply reduces the chip curvature radius and influences deformation of the chip during machining. In particular the force of the CL-jet force in cutting normal direction has a significant effect on reducing the chip curvature radius. [ABSTRACT FROM AUTHOR]

As an efficient, green and energy-saving technique, microwave has shown great development prospects for assisting mechanical rock breaking due to its ability to reduce rock strength and even damage rock. To address the problems of low excavation efficiency and severe tool wear during hard rock excavation, high-power microwave was applied to assist the pick breaking the rock in this study. In addition, the heating, fracturing, and the cutting effect of the rock under different microwave parameters were analyzed. The conclusions were as follows: firstly, the rock temperature is positively correlated with microwave power, irradiation time, water content and the number of cycles. The surface temperature of the rock was categorized into a high-temperature zone, sub-high-temperature zone and low temperature zone after microwave irradiation. Secondly, rocks exhibited macroscopic cracks, causing rock blocks to peel off, resulting in fracture zones after microwave irradiation. These were correlated with the temperature zones on the rock surface. Finally, the auxiliary mechanical cutting effect of microwave was analyzed and evaluated. The average cutting force (Fmean) and the maximum cutting force (Fmax) of the rock decreased after microwave irradiation. Moreover, the length, width, and depth of the cutting groove also confirmed the great effect of microwave-assisted mechanical rock breaking. This study provides valuable insights for the practical application of microwave-assisted mechanical rock breaking in the field. Highlights: Increasing the moisture content can improve the microwave absorption capacity of sandstone. Microwave thermal effects cause macro cracks and even cause local spalling in sandstone. The rock-breaking effect of microwave-assisted conical pick is evaluated from the cutting force, energy, and cutting damage characteristics. Cutting characteristics of sandstone are quantified by 3D topography scan before and after microwave irradiation. [ABSTRACT FROM AUTHOR]

The performance of a novel hard solid lubricant coating, CrAlNAg, in the face milling operation of AISI 1045 medium carbon steel under the modes of roughing and finishing was investigated. Dry machining was carried out using CrAlN coated inserts with varying silver (Ag) contents ranging from 0 to 16 at.%. The objective was to evaluate the performance of the developed coatings under different machining conditions, which could potentially result in (a) a high material removal rate (rough machining) and (b) high surface finish and dimensional accuracy (finish machining). An in-depth analysis of the cutting forces in face milling was performed to assess the impact of the coatings under these machining conditions. During machining, the force components in the X, Y, and Z directions were measured using a cutting force dynamometer attached to the workpiece. The components of these forces concerning the tool edge were calculated using geometrical characteristics and mathematical formulations, enabling the identification of the true cutting forces and the most sensitive force components relative to the cutting parameters. Apart from cutting forces, chip temperature, tool wear, surface roughness, and chip characteristics were evaluated for different coating compositions under both machining conditions. Owing to superior coating-substrate adhesion and tribological characteristics, the CrAlNAg9 coating with around 8.6 at.% of Ag was found to significantly reduce dominant forces and chip temperature under both machining conditions. Furthermore, the same coating exhibited remarkable resistance to flank wear compared to other compositions of CrAlNAg coatings. [ABSTRACT FROM AUTHOR]

In the aerospace industry, high-precision components like impellers and blisks present considerable challenges in machining due to their intricate geometries and the need for reliable performance. Blades, often classified as thin-walled parts with complex, free-form surfaces, are crucial in ensuring the efficiency and safety of aircraft engines. Their geometries and materials require strict control over cutting parameters, such as tool path and orientation, to avoid deformation and maintain surface integrity. This study investigates the impact of tilt angle variation during ball end milling of Ti6Al4V thin-walled parts. Four different tilt angles (15°, 30°, 45°, and 60°) were analysed to evaluate their effect on dimensional accuracy and surface roughness. The results show that tilt angle significantly influences surface quality and dimensional precision. A tilt angle of 30° achieved the best balance between surface finish and dimensional tolerances, with flatness values ranging from 0.038 mm at 30° to 0.101 mm at 60°, representing a 152.5% increase in flatness. The findings provide practical guidelines for optimizing ball end milling of thin-walled components, emphasizing the importance of tool orientation in reducing deformation and enhancing surface quality. [ABSTRACT FROM AUTHOR]

Inconel 718 alloy is characterised by high strength and corrosion resistance and remains stable at high temperatures, so it is widely used in the energy and aerospace industries. However, machining this material is difficult due to its high strength, hardness, and high specific force coefficient exceeding 3000 MPa. Turning of the Inconel 718 alloy can be carried out with negative and positive inserts. Therefore, the impacts of the insert geometry on the turning process of Inconel 718, cutting force components, and surface roughness were studied. Three positive and three negative insert geometries were tested. It was shown that the key influence on the active components of the cutting force is the effective rake angle. The surface roughness, on the other hand, depends mainly on the cutting-edge radius. It has been shown that the negative insert geometry with γ = 6° and rn=22 μm provides a 30% lower cutting force than the positive inserts and the same surface roughness. The developed models of the cutting force components proved that when cutting with positive inserts, a higher specific cutting force occurs for the Inconel 718 alloy than for the negative insert. It was shown that technological parameters had a very similar effect on the cutting force components and surface roughness parameters regardless of the blade geometry. It was proven that the use of positive inserts makes sense only for depths of cut no greater than the size of the corner radius. [ABSTRACT FROM AUTHOR]

Micro-milling technology is widely employed in manufacturing micro-precision parts due to its flexible processing and high accuracy. Compared to the macro-milling process, micro-milling has a smaller machining size, which leads to tool wear, tool runout, and other factors being more sensitive to the impact of machining quality. This work proposes a reliability evaluation framework for machining systems based on the micro-milling mechanical model and its surrogate method. Establish a cutting force model under shear and plow conditions with periodic variations in instantaneous uncut thickness. Subsequently, the probability distribution of the cutting parameters is obtained based on Bayesian updates. An improved buffer failure probability method is proposed to quickly get the micro-milling system failure probability. Developing new ensemble and adaptive sampling methods and introducing stochastic configuration network (SCN), an adaptive stochastic configuration network ensemble (ASCNE) model is established to alleviate the time-consuming problem of repeated calculations of mechanical models in reliability analysis. Experimental results indicate that the mechanical model can achieve good predictive performance, and the constructed ASCNE model can achieve high-precision surrogate effects. Additionally, the reliability analysis results of the system can guide tool replacement during the machining process, ensuring safe and efficient execution of the micro-milling. [ABSTRACT FROM AUTHOR]

Accurate prediction of cutting forces is critical in milling operations, with implications for cost reduction and improved manufacturing efficiency. While traditional mechanistic models provide high accuracy, their reliance on extensive milling data for force coefficient fitting poses challenges. The eXtreme Gradient Boosting algorithm offers a potential solution with reduced data requirements, yet the optimal utilization of eXtreme Gradient Boosting remains unexplored. This study investigates its effectiveness in predicting cutting forces during down-milling of Al2024. A novel framework is proposed optimizing its precision, efficiency, and user-friendliness. The model training incorporates the mechanistic force model in both time and frequency domains as new features. Through rigorous experimentation, various aspects of the eXtreme Gradient Boosting configuration are explored, including identifying the optimal number of periods for the training dataset, determining the best normalization and scaling technique, and assessing the hyperparameters' impact on model performance in terms of accuracy and computational time. The results show the remarkable effectiveness of the eXtreme Gradient Boosting model with an average normalized root mean square error of 14.7%, surpassing the 21.9% obtained by the mechanistic force model. Additionally, the machine learning model could capture the runout effect. These findings enable optimized milling operations regarding cost, accuracy and computation time. [ABSTRACT FROM AUTHOR]

With intelligent manufacturing development, applying adaptive control technology in the machining process is an effective way to increase productivity and quality. However, adaptive control alone cannot control cutting forces effectively when cutting conditions have excessive change. In this study, a digital twin of the milling process is introduced to cutting force adaptive control for system robustness and efficiency. The cutting force is indirectly measured based on the feed drive current using a Kalman filter, and unknown parameters in the estimation model are identified. A virtual machining system model is established based on online data communication and geometric operation. In addition, the machining state is predicted and introduced into the adaptive control algorithm based on the integrated digital twin for cutting force constraint control. Finally, rough milling of an S-shape specimen is carried out as the cutting experiment to verify the credibility and efficiency of the digital twin-driven cutting force adaptive control. [ABSTRACT FROM AUTHOR]

To improve the productivity of the machining process, it is crucial to minimize non-productive time during the manufacturing process. For instance, a significant amount of time is often spent troubleshooting issues on-site when machining failures occur, which reduces overall productivity as the machine remains idle during this period. Recently, using virtual environments constructed in computer systems to predict and resolve such problems has become increasingly popular. This approach, often referred to as a "digital twin," can be highly effective in addressing issues. However, accurately predicting physical phenomena in a virtual environment can be challenging, requiring considerable effort to ensure the virtual model correctly represents real-world behavior. This study presents a technique for simulating coupled vibrations between machine tool dynamics and cutting forces using MATLAB/Simulink, a widely used commercial software. Machine tool dynamics are modeled with the "Simscape Multibody" function, which allows the construction of a multi-body dynamics model by defining mass, inertia, and constraint conditions. Cutting forces and machined surface geometry are calculated through Boolean operations between two geometric shapes represented by polygonal models. Self-excited chatter vibrations are simulated as an example of coupled vibrations, and actual cutting tests are conducted to validate the accuracy of the simulated results. A stability lobe diagram of the chatter vibrations is also generated based on measured and simulated frequency responses. The results demonstrate that the constructed model can accurately predict machining stability and cutting forces. [ABSTRACT FROM AUTHOR]

Ultrasonic vibration has a certain effect on the crack propagation tendency during sapphire grinding, but the mechanism of the effect on the crack propagation tendency has not yet been elucidated. In this study, tangential ultrasonic vibratory scratching and normal scratching sapphire processes were simulated using the discrete element method, and the expansion tendency of sub-surface cracks in the scratching sapphire process was analyzed in terms of cutting forces and stresses. The results of the study show that the crack depth decreases with increasing scratch speed and increases with increasing scratch depth; The greater the variation in cutting force, the greater the number of cracks formed and the crack propagation is mainly distributed near the maximum residual tensile stress; The introduction of tangential ultrasonic vibration induces a decrease in residual tensile stresses and an increase in residual compressive stresses, thus inhibiting subsurface crack propagation; The suppression of subsurface cracks becomes more pronounced as the amplitude increases. Finally, tangential ultrasonic vibratory scratching and normal scratching sapphire experiments were comparatively studied and the experimental results were in agreement with the simulation results. This study provides some theoretical guidance for the suppression of subsurface cracks in sapphire materials during the grinding process. [ABSTRACT FROM AUTHOR]

Super-duplex stainless steel (SDSS) 2507 is well known for its complex microstructure and alloying components, which contribute to its exceptional mechanical qualities and resistance to corrosion. Nevertheless, these features provide considerable difficulties during machining. In order to address these challenges and advance sustainability, this work presents a novel machining technique that combines minimal quantity lubrication (MQL) with surface-textured tools. Two different kinds of texture tools were examined: one with linear grooves and the other with a hybrid texture that combined both circular pits and holes. A CNC center lathe machine operating under MQL conditions was used for the experiments. It had two distinct cooling conditions, different tool textures, and cutting parameters like depth of cut, feed rate, and speed. Cutting speed, followed by feed rate, was the most important factor affecting cutting force and tool flank wear, according to analysis of variance (ANOVA). Comparing the hybrid-textured tool under MQL to dry machining conditions, the cutting force was reduced by 40%. A cutting speed of 40m/min, feed rate of 0.1mm/rev, and depth of cut of 0.4mm were found to be the optimal machining parameters employing MQL and hybrid-textured tools for minimizing cutting force and tool wear, the optimal values are 119.57N and 113.875μm respectively. These findings provide notable enhancements in machinability and sustainability for SDSS 2507, demonstrating the efficiency and usefulness of the suggested approach in MQL machining. [ABSTRACT FROM AUTHOR]

The study consists of two stages: machinability tests and metallographic examinations. In the first stage of the study, response surface methodology (RSM) optimization was performed for the main‐cutting‐force (Fc) and average surface roughness (Ra) values obtained as a result of turning tests. In the second stage, the wear performance of cutting tool tips with and without deep cryogenic treatment was explained with the support of SEM images, EDX, XRD, and microhardness analyses. As a result of ANOVA analysis, it was found that the most effective parameter on Fc was the feed rate, with 78.89%. As a result of RSM‐optimization, the lowest Fc value was found to be 339.99 N. The most effective parameter on Ra was found to be the feed rate at 69.38%. In terms of tool life, 15% and 11% improvements were achieved in uncoated and coated carbide cutting tools, respectively. As a result of Rieltveld's analysis, it was determined that cryogenic treatment increased the carbide percentages in the tools. As a result of microhardness measurements, it was observed that the hardness of uncoated and coated carbide tools increased by 4.6% and 5.15%, respectively, after cryogenic treatment. [ABSTRACT FROM AUTHOR]

This study delves into investigating tool wear in drill thread mill (DTM), a specialized threading process known for its adaptability and lack of need for a pilot hole. While previous research extensively addresses tool wear in turning and milling processes, studies focusing on thread-making processes, especially DTM, are relatively scarce. To address this gap, our research aims to comprehensively explore wear morphologies, mechanisms, and their impacts on dimensional integrity and cutting parameters of DTM tools. We employ optical microscopy to elucidate wear progression and mechanisms and assess the effects of tool wear on dimensional accuracy of threaded holes and cutting parameters like cutting forces and vibration. Our findings reveal that the flank side experiences more significant wear compared to the rake side, with thread upper and thread lower cutters being the most heavily worn. We observe adhesion, coating delamination, built-up edges, and chipping in the wear mechanisms. Notably, wear predominantly affects lateral cutting forces, whereas thrust forces are less impacted. Although vibratory analysis can indicate wear progression, its efficacy is inferior to that of cutting force analysis. Moreover, wear significantly affects thread dimensional quality, particularly the effective diameter, necessitating compensation after the 130th hole. [ABSTRACT FROM AUTHOR]

During the process of five-axis free-form milling, tool orientation and surface curvature of the workpiece have significant effects on tool wear. Five-axis milling experiments are carried out on 17-4PH stainless steel using a carbide ball end mill. The influence of tool orientation on the amount of wear, cutting force, and chip morphology of the ball end cutter was investigated. The results show that tool wear is slighter at a tool inclination angle of approximately 15°, reducing tool wear by up to 29.55% compared with other angles. The inclination angle also has great effects on the milling force and torque signals, a suitable tool inclination angle makes the milling force and torque signals smooth, and the standard deviation is only 0.94 N and 0.017 N·m, respectively. In addition, the chips can reflect the stability of the machining process to some extent. On this basis, different workpiece surfaces were selected to investigate the effect of workpiece surface characteristics on tool wear. The results show that more severe tool wear and higher milling force signals on curved surfaces occurred with smaller radii of curvature. An appropriate tool orientation in relation to the curvature of the workpiece surface can significantly reduce tool wear; concave surfaces are suitable for machining with small angle of inclination, e.g., 5° ~ 10°, whereas convex surfaces are suitable for machining with larger angle of inclination, e.g., 20° ~ 25°. [ABSTRACT FROM AUTHOR]

Cutting force is a vital indicator for assessing the performance of machining operations; therefore, developing a reliable predictive model is mandatory for process monitoring, optimization, and control. The mechanistic force model is preferred among approaches presented in the literature due to computational efficiency and effectiveness. The prediction abilities of the model largely depend on the empirical relationship between uncut chip geometry and lumped empirical constants determined using machining experiments involving cutting force measurements. The experimental data usually contains noise and outliers that must be removed before determining empirical constants. Data mining techniques are potential tools for removing noisy and outlier-ridden experimental data. This work develops a two-stage hybrid approach combining a clustering technique and machine learning model for data mining and determining precise empirical constants. The comparative evaluation of three unsupervised clustering techniques, namely hierarchical density-based spatial clustering of applications with noise (HDBSCAN), one-class support vector machine (SVM), and elliptic envelope, is performed in removing outliers. The machine learning-based ADAMW algorithm is implemented to fit the relationship and determine empirical constants from cleansed experimental data. It has been shown that HDBSCAN combined with the ADAMW algorithm can effectively remove outliers, enhance the goodness of fit, and achieve better performance. The prediction abilities of the proposed approach are corroborated by performing machining experiments over varying cutting conditions. It is concluded that the hybrid approach can address challenges associated with noisy and outlier-ridden experimental data, thereby enhancing the fidelity of the mechanistic force model. [ABSTRACT FROM AUTHOR]

Aiming at the machining difficulty of high-volume fraction SiCp/Al composites, the cutting mechanism and damage behavior of SiCp/Al composites with volume fraction of 65% during the milling process using PCD tools were studied in this paper. The complex deformation phenomena among SiC particles, Al matrix, and particle–matrix in the tool-particle contact area during cutting were analyzed. A two-dimensional finite element model of a cut SiC/Al composite was built, cohesive zone model (CZM) was adopted, and relevant experiments were conducted to validate its accuracy and the effectiveness of the model. The SiCp/Al composite containing 65% silicon carbide particles (SiCp) was cut using polycrystalline diamond tools. Then, the effects of processing parameters (tool rake angle γ 0 , corner radius r , milling depth a p , milling speed v ) and the tool-particle interaction on material properties were analyzed using a single-factor variable method. Both simulation and experiments revealed the failure modes of SiC particles and the Al matrix as well as the correlations with the cutting force, cutting temperature, cutting stress, and surface morphology. The results theoretically underlie the appropriate selection of tool geometrical parameters and the improved processability of SiCp/Al PCD tools. [ABSTRACT FROM AUTHOR]

The current research work aims at investigating the influence on dimple type textures of varying dimensions on different machining characteristics of Ti6Al4V, with particular emphasis on cutting forces, tool wear and surface roughness under dry environment. The texture on the WC turning inserts is developed using laser surface texturing technique carried out in a femtosecond laser system. The diameter of texture is varied in the range of 140–400 µm with the corresponding dimple depth in the range of 50–100 µm. In order to understand the effect of textures under different conditions of machining, cutting speeds of 60, 90 and 120 m/min, feeds of 0.1 and 0.25 mm/rev and depth of cuts of 1 and 1.5 mm are utilized in the present study. Textured tools T2 and T3 exhibit reasonably good resistance to edge chipping particularly under the condition of high feed and high depth of cut and are recommended to employ under high feed and depth of cut keeping the cutting speed at low to moderate values. However, the results also indicate that the textured tools with larger diameter (T1, T4 and T5) are more effective in bringing down cutting forces, coefficient of friction and surface roughness particularly at cutting speed of 60 m/min during dry machining of Ti6Al4V. The maximum reduction of 4.30% in main cutting force, 3.96% in coefficient of friction with the textured tool T4, whereas reduction of 60% in surface roughness with the textured tool T1 are recorded. Moreover, texture with higher pitch and lower area ratio is more suited under the condition of higher cutting speed (120 m/min), while the texture with higher area ratio results in lower adhesion of work material during machining under the lower cutting speed of 60 m/min. [ABSTRACT FROM AUTHOR]

Minimum quantity lubrication (MQL) is an effective method for addressing technical challenges associated with high cutting loads during machining. Although much research has explored the ability of MQL to reduce cutting forces, intuitive analyses of its developmental trends, leading researchers, and research hotspots remain limited. To address this, a bibliometric analysis was conducted on studies related to MQL and its role in cutting force reduction. Data from the Web of Science Core Collection database, covering the period from January 1, 2008, to December 31, 2023, were analyzed. Bibliometric tools such as VOSviewer, Scimago Graphica, and Bibliometrix were used to visually assess publication trends, source journals, countries, institutions, authors, references, and keywords. The results show that India leads in publication output with 231 papers, while Li CH from China is the most cited author, with 3200 citations. A detailed clustering analysis of keywords and their representative research areas was performed, summarizing the current findings on the effects of processing parameters on cutting forces. The study also analyzed the optimization of machining parameters to minimize cutting forces, identifying relatively optimal conditions. Finally, challenges and potential solutions were discussed, providing theoretical and technical guidance for the industrial application of MQL. [ABSTRACT FROM AUTHOR]

Minimum quantity lubrication (MQL) is an environment-friendly alternative to traditional flood cooling techniques and has great potential to be successful in micro-machining. The current research work aims toinvestigate the influence of MQL flow rates (6, 50, and 100 ml/h) and cutting parameters such as spindle speed and feed on various micro-drilling characteristics of Ti-6Al-4 V. Thrust force, specific cutting energy, and hole surface roughness were found to be lower under the MQL flow rate of 6 ml/h as compared to higher flow rates. An increase in the MQL flow rate from 6 to 100 ml/h at a spindle speed of 30,000 rpm resulted in a maximum of 40% increase in the thrust force. The surface roughness and oversize error increased by a maximum of up to 162 and 66%, respectively, under a similar change in the MQL parameters. The flow rate of 100 ml/h exhibited inferior micro-drilling characteristics primarily owing to its inability to effectively penetrate the narrow machining zone. Material adhesion under the MQL environment increased with an increase in cutting velocity due to the rise in the cutting temperature. The phenomenon of the "size effect" was evident under the lowest feed of 1 µm/rev owing to the regime of rubbing and ploughing. Elevation of feed effectively promoted shear deformation in micro-drilling. Overall, the present study highlighted the superiority of the lowest flow rate of 6 ml/h owing to effective atomization during micro-machining under the MQL environment. [ABSTRACT FROM AUTHOR]

Nowadays, sustainable Minimum Quantity Lubrication (MQL) technology has significantly enhanced machinability, surface quality, and productivity comparing to dry machining. Furthermore, it is considered as a key factor that respects the ecological trends in machining and also contributes in reducing the consumption of cutting fluid and machining costs. The present paper brings a comparative research between sustainable dry machining and sustainable MQL machining while turning AISI 52100 steel with CVD coated (GC-2015) metal carbide inserts. First, parametric tests were carried out to evaluate the impact of machining parameters (CS, f, and Doc) on performance factors in terms of tool wear, cutting force, surface roughness, energy consumption, and cutting temperature. Then, a Taguchi L9 (3^3) experimental design was implemented in order to carry out a statistical analysis based on ANOVA and performance modelling (Ra, Fz, Pc, Kc, and MRR) by applying the (RSM) method. Finally, a comparative multi-criteria optimization was performed using the DF method and four other MCDM methods (GRA, EAMR, FUCA, and EDAS) combined with Taguchi's signal-to-noise-ratio (S/N). The results confirmed the effectiveness of MQL technique in enhancing machining performance over dry machining. Furthermore, the EAMR, EDAS, and GRA methods identified the same optimal combination (CS = 300 m/min, Doc = 0.45 mm, and f = 0.08 mm/rev), yielding the best results for (Ra, Kc, and MRR). The FUCA method promotes improvement of energy efficiency during machining by achieving minimal values for (Pc and Fz). Finally, the DF method stands out for its ability to produce balanced results across all performances. [ABSTRACT FROM AUTHOR]

The aviation industry is still looking for effective manufacturing methods. Currently, the challenge is still the machining of shapes in thin-walled materials. This work focuses on the analysis of the influence of these parameters on deformations during the drilling process of holes in the adapters of aircraft engine body accessories. The drilling process was carried out in the thin-walled superalloy Inconel 718, which is classified as a difficult-to-machine material. During the analyses, experimental studies based on the Response Surface Method (RSM) and finite element method (FEM) calculations were carried out simultaneously. The aim of this work was to analyze the developed mathematical models describing nonlinear relationships between cutting parameters, cutting forces, and deformations of the aircraft engine body characterized by a complex, thin-walled geometric structure. By using the proposed solutions, it is possible to achieve integration between the techniques of conducting research, performing calculations using FEM, and designing the machining. The advantage of this comprehensive approach used in our work is the development of mathematical models that strongly fit the results of the research. The results of analyses and calculations presented in the article and the research methodology used can be applied to industrial conditions. [ABSTRACT FROM AUTHOR]

The machining of shape memory alloys, such as NiTi, presents challenges due to their specific physical, chemical, and mechanical properties. This study investigated the effect of the helix angle of milling tools—both uncoated and coated—on the cutting forces and the surface roughness of the milling process for a NiTi alloy. Experiments were conducted using the tools with and without coatings at various helix angles (20°, 30°, and 40°) and under different machining conditions. Optimization of the process was employed the Taguchi method to identify the best combination of the corresponding parameters. The results of the cutting force and the surface roughness measurements were analyzed and discussed in the context of optimizing the cutting conditions to achieve the desired outcomes. The results show that the lowest surface roughness values (Sa = 0.301 μm and Sz = 3.41 μm) were achieved with the coated tool at a helix angle of 30°, a feed per tooth of 0.02 mm, and a cutting speed of 45 m/min, while the lowest cutting force (F = 143.6 N) was observed with the coated tool at a cutting speed of 55 m/min, helix angle of 40°, and feed per tooth of 0.02 mm. This research provides valuable insights for industrial applications requiring the precise machining of NiTi in terms of the cutting forces and the surface quality. The findings reveal that the presence of the coating, along with an increase in the helix angle, significantly reduces the cutting forces, positively influencing the quality of the machined surface. [ABSTRACT FROM AUTHOR]

The use of the minimum quantity lubrication (MQL) method during machining leads to the reduced consumption of cooling and lubricating liquids, thus contributing to sustainable machining. To improve the properties of liquids used under MQL conditions, they are enriched with various types of micro- and nanoparticles. The purpose of this study was to investigate the effect of the addition of graphite micropowder (GMP) on tool life, cutting force components, and selected surface roughness parameters during the finish turning of the Ti-6Al-4V titanium alloy under MQL conditions. The addition of 0.6 wt% of GMP to the base liquid in machining under MQL conditions leads to an extension of tool life by 7% and 96% compared to machining with a liquid without the addition of GMP and dry machining, respectively. Mathematical models of the cutting force components and surface roughness parameters were developed, taking into account the change in cutting speed and feed. It was found that the use of a liquid with the addition of GMP extends the range of cutting parameters for which the shape of chips obtained is acceptable in terms of work safety. The novelty of this study lies in the use of a cutting fluid composed of bis(2-ethylhexyl) adipate and diester, enriched with graphite micropowder, which has not been extensively investigated for machining titanium alloys under MQL conditions. [ABSTRACT FROM AUTHOR]