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In Ti-6Al-4V titanium alloy micro-machining, since the uncut chip thickness (UCT) is comparable to the radius of the tool cutting edge, there exists a minimum uncut chip thickness (MUCT), and when the UCT is smaller than the MUCT, the plowing effect dominates the cutting process, which seriously affects the machined surface quality and tool life. Therefore, the reliable prediction of the MUCT is of great significance. This paper used Deform to establish an orthogonal cutting simulation model, studied the effect of the dead metal zone (DMZ) on the micro-cutting material flow, determined the DMZ range, and proposed a new method for determining the MUCT based on the DMZ. Cutting experiments were conducted to verify the accuracy of the simulation model firstly by cutting force, and then confirming the accuracy of the DMZ-based MUCT determination method through chip analysis and surface quality analysis. Finally, the effects of different cutting conditions on DMZ and MUCT were further investigated using the proposed DMZ-based MUCT determination method. The results show that the MUCT of Ti-6Al-4V titanium alloy is 4.833 μm for a tool cutting edge radius of 40 μm and a cutting speed of 10 m/min. The DMZ boundary can be used as the boundary of micro-cutting plastic deformation, and the ratio of MUCT to cutting edge radius, hp/rn will gradually decrease with the increase in the tool cutting edge radius and the cutting speed. [ABSTRACT FROM AUTHOR]

Cauliflower is an important winter crop grown in India, its curds are rich in nutritional profile, containing valuable minerals and vitamins. However, cauliflower harvesting is mainly accomplished by hands, which is time-consuming and requires a high labour force. On the other hand, most developed cauliflower harvesters are once over or single pass type, which harvests all plants irrespective of their maturity. So, the selective harvester could improve the cauliflower curds yield, and then decrease the labour requirement. To improve the cutting performance of the selective cauliflower harvester, the working parameters of the chainsaw cutting mechanism need to be considered and optimized. This research investigates the impact of cutting height, feed (push) force, and cutting speed on the efficiency of the cutter during harvest. The Taguchi approach, together with grey relational analysis (GRA), was employed to identify the most favorable combination of operational parameters. In addition, the variance analysis was conducted to statistically examine the impact of multiple parameters. The findings indicated that the feed force was the major parameter that influenced the cutting force, splitting failure levels, and cutting time. The most effective parameter combination consisted of a cutting height of 15 mm, a feed force of 10 N, and a cutting speed of 5 m/s. The grey relational grade of the ideal parameter combination has shown a 0.322 increase in comparison to the grade achieved with the initially selected parameter combination. This setting was further incorporated in the developed selective cauliflower harvester to improve the performance of its cutting mechanism. [ABSTRACT FROM AUTHOR]

High‐speed dry milling (HSDM) technology is one of the most attractive solutions for improving the cutting performance of difficult‐to‐machine materials. However, the study of HSDM performance for 30CrMnSiNi2A steel has not been reported. In this article, HSDM for 30CrMnSiNi2A steel is investigated using TiN‐coated and AlTiN‐coated tools, focusing on cutting force, vibration, surface roughness, residual stress, and tool wear. The effects of cutting parameters on cutting force and vibration are remarkably similar. At a spindle speed of 7500 r min−1, both cutting force and vibration are minimized. TiN‐coated and AlTiN‐coated tools exhibit distinct performance differences. But, HSDM of 30CrMnSiNi2A steel using TiN‐coated and AlTiN‐coated tools can achieve low surface roughness. The depth of cut significantly affects surface roughness, which is lowest at the depth of cut (0.8 mm). Most of the workpiece surface shows residual compressive stress. The main wear mechanisms for both coated tools are abrasive wear, adhesive wear, and oxidative wear. Furthermore, the AlTiN‐coated tool is more wear resistant on the flank face compared to the TiN‐coated tool. Chipping due to crater wear is the leading cause of tool failure for the AlTiN‐coated tool. Upon various comparisons, the AlTiN‐coated tool is more suitable for HSDM of 30CrMnSiNi2A steel. [ABSTRACT FROM AUTHOR]

This paper integrates an in-process monitoring of tool wear with quality control of roughness and roundness of machined parts in CNC turning, which are the critical parameters. The Daubechies wavelet transform has been applied to decompose the dynamic cutting forces in order to classify the signals of the tool wear, the average surface roughness, the surface roughness, and the roundness. The decomposed cutting forces are normalized to predict those parameters regardless of cutting conditions by taking the ratio of decomposed cutting forces. Firstly, the ratio of average variance of decomposed feed force to that of decomposed main force is proposed to estimate the tool wear. Secondly, the areas of those decomposed feed force and decomposed main force have been proposed and taken into the ratio to forecast the average surface roughness and the surface roughness concurrently. Lastly, the roundness error is calculated simultaneously by utilizing the ratio of average variance of decomposed radial force to that of decomposed feed force. The exponential function is adopted to represent the relations of the tool wear, the average surface roughness, the surface roughness, the roundness, and all proposed ratios of decomposed cutting forces, respectively. The new cutting tests are conducted to verify all obtained models. The experimentally obtained results showed that the tool wear declines as the ratio of average variance of decomposed feed force to that of decomposed main force increases. The average surface roughness and the surface roughness tend to decrease while the ratio of decomposed feed force to decomposed main force progresses. On the other hand, the roundness error becomes larger when the ratio of average variance of decomposed radial force to that of decomposed feed force escalates. It is concluded that the tool wear, the average surface roughness, the surface roughness, and the roundness can be monitored and controlled at the same time during the in-process CNC turning, which has never been done and developed before. The highest benefit of the proposed system can enhance the quality of machined parts and lead to higher productivity. [ABSTRACT FROM AUTHOR]

Aramid fiber–reinforced polymer composite (AFRPC) is popular in aerospace and defense industries owing to its superior thermal and mechanical properties. However, its intricate hexagonal cellular structure and the material's heterogeneous, soft, and brittle characteristics lead to significant surface defects, such as burr formation, wall tearing, roughness, dimensional inaccuracies, and uncut fibers during traditional machining. Such poor machining quality issues notably affect the operational lifespan and functional performance of its sandwich structural components. To address these issues, the rotary ultrasonic assisted machining (RUSAM) process has been introduced. To thoroughly investigate the RUSAM of AFRPC using various cutting tools, a 3D finite element model was developed and validated. This paper mainly investigates the effect of various machining parameters such as vibration amplitude (VA), cutting width (CW), feed rate (FR), and spindle speed (SS) on the cutting force, surface morphology, burr formation, and burr height during RUSAM of AFRPC structure by plane and toothed disc cutters. The burr height was found to decrease with the increase of spindle speed (60.82% and 71.00%) and vibration amplitude (78.15% and 82.32%), whereas increase with cutting width ( 149.81 % and 321.16%) and feed rate (156.53% and 314.83%) during RUSAM by plane and toothed disc cutters, respectively. The pattern of variation of burr height with machining parameters was found similar to that of the cutting force. Significance analysis based on 4 levels, 4 factors orthogonal L 16 ( 4 4 ) experiments revealed the cutting width to be the most influential parameter on the burr height and cutting force followed by the spindle speed, feed rate, and vibration amplitude during RUSAM of the AFRPC core by the disc cutters. Up to 62.54 % reduction in burr height was realized by rotary ultrasonic assisted machining compared to the conventional machining. Under specified operating conditions, the disc cutter generates a higher but less number of burr as compared to the toothed disc cutter without any tearing defects. 3–10% and 5–20% burrs were observed during rotary ultrasonic assisted machining compared to 20–50% and 40–70% burrs during conventional machining of AFRPC structure by plane and toothed disc cutters, respectively. This experimental research will be extremely useful to comprehend the burr formation mechanism and optimize the machining parameters for enhanced surface morphology of AFRPC structures. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polymer Please check Affiliations if captured/presented correctly.(CFRP) composites are essential in aerospace, automotive, and civil engineering due to their strength-to-weight ratio, stiffness, thermal stability, and corrosion resistance. However, drilling CFRPs is challenging due to anisotropy, heterogeneity, and sensitivity to cutting forces, often causing delamination, burr formation, tearing surface ca[vities, and roughness. This review examines advancements in drilling techniques, analyzing their mechanisms, benefits, and limitations to improve hole quality and minimize damage. Finite element modeling (FEM) plays a crucial role in optimizing drilling by predicting thrust forces, torques, and damage, with recent advancements enhancing damage reduction. The review explores the influence of drilling parameters on thrust force, torque, temperature, and various damage types in CFRP composites. This review proposes strategies to optimize these parameters, including tool geometries, deburring techniques, pilot holes, and variable feed rates, while emphasizing sustainability for environmental and efficiency benefits. It analyzes research shortcomings, outlines future directions, and focuses on sustainable methods like cryogenic cooling, MQL, and compressed air cooling to reduce energy use, tool wear, and emissions. Future research should reveal the mapping mechanism between these parameters and CFRP hole-making quality, proposing an optimized, sustainable drilling strategy to reduce defects and improve hole quality. [ABSTRACT FROM AUTHOR]

Small-scale rock cutting tests serve as a simple approach to evaluate the performance of tunnel boring machines (TBMs), but the feasibility of this method requires further investigation. Herein, a small-scale rotary cutting machine is developed to conduct rock cutting tests, and the cutting performance is investigated. The results indicate that similar cutting performance can be achieved through both small-scale and full-scale tests. The critical penetration depth for effective rock cutting by the cutter is 0.5 mm, below which the cutter grinds against the rock. The optimal ratio of cutting spacing to penetration depth obtained in small-scale tests is 4.47. A result within the empirical range can be achieved by multiplying the optimal small-scale cutting parameters with the scale coefficient, demonstrating the feasibility of using small-scale tests to guide the design of cutter heads. Based on the test result, the scale prediction model is constructed to predict the full-scale cutting force. The predictive capability of the proposed model and CSM model is validated using 72 sets of full-scale test data involving the same types of rock, and the predictions of the proposed model are closer to the test data. [ABSTRACT FROM AUTHOR]

Multi-tooth milling cutters have the advantages of minimal surface damages and low cutting forces and are widely used in composite materials milling such as carbon fiber and wood. Cortical bone is a composite biomaterial similar to carbon fiber and wood; however, the cutting performance of multi-tooth milling cutters on bone cutting is unclear. Here, this paper proposes a multi-tooth milling cutter longitudinal torsional ultrasonic vibration assisted milling (LTVUM) method for cortical bone low damage cutting. The cutting performance of sinusoidal and corn edge cutters for cortical bone LTVUM was studied, and its material removal mechanisms were also established. The results indicated that the multi-tooth milling cutter has a smaller average cutting force, and suppressing the chip burrs and tearing damages. Compared to straight edge cutter, the resultant cutting forces of sinusoidal and corn edge cutters are decreased by 52.58%–61.01% and 45.60%−65.96%. The reason is that the secondary cutting edge of multi-tooth cutter can participate in cutting, reducing the tool squeeze interference. This work provides experimental guidance for the application of multi-tooth milling cutters LTVUM in bone cutting. [ABSTRACT FROM AUTHOR]

The single-phase titanium ß-alloy Ti10V2Fe3Al (Ti-1023) has been widely used in the aerospace industry due to its unique mechanical properties, which include high fatigue strength and fracture toughness, as well as high corrosion resistance. On the other hand, these unique properties significantly hinder the cutting processes of this material, especially those characterized by a closed machining process area, such as drilling. This paper is devoted to the study of the short hole drilling process of the above-mentioned titanium alloy using direct measurements and numerical modeling. Measurements of the cutting force components in the drilling process and determination of the resultant cutting force and total cutting power were performed. The macro- and microstructure of chips generated during drilling were analyzed, and the dependence of the chip compression ratio and the distance between neighboring segments of serrated chips on cutting speed and drill feed was determined. Experimental studies were supplemented by determining the temperature on the lateral clearance face of the drill's outer cutting insert in dependence on the cutting modes. For the modeling of the drilling process using the finite element model, the parameters of the triad of component submodels of the numerical model were determined: the machined material model, the model of contact interaction between the tool and the machined material, and the fracture model of the machined material. The determination of these parameters was performed through the DOE sensitivity analysis. The target values for performing this analysis were the total cutting power and the distance between neighboring chip segments. The maximum deviation between the simulated and experimentally determined values of the resulting cutting force is no more than 25%. At the same time, the maximum deviation between the measured values of the temperature on the lateral clearance face of the drill's outer cutting insert and the corresponding simulated values is 26.1%. [ABSTRACT FROM AUTHOR]

Plunge milling, as a recognized high-efficiency metal cutting process, is an ideal choice for roughing machining of deep groove and cavity parts. However, due to the severe cutting load of plunge milling, especially the problem of plunge milling collision, and the lack of cavity plunge milling process, its engineering application has always been unsatisfactory. In this paper, starting from the cutter design, the inward-inclined structure of cutting edge is proposed, which can effectively avoid the sharp increase in cutting load caused by plunge milling collision, and realize in situ cutter retraction. At the same time, the dislocation chip-separation structure of cutting edge is also proposed, which can effectively reduce the plastic deformation of cutting layer, and the maximum cutting force is reduced by about 55%. Based on the design of the above high-performance plunging cutter, considering the constraints of material residue and isolated corner, the plunging milling process strategies for open cavity, semi-closed cavity and closed cavity are planned. Finally, the influence law of machining parameters on cutting force is explored. The setup series of verification experiments show that the inward-inclined structure and dislocation chip-separation structure of plunge milling cutter are reasonable, and the process strategies and machining parameters of cavity plunge milling are feasible. Compared with the traditional layer milling, the machining efficiency is increased by about 3.3 times. [ABSTRACT FROM AUTHOR]

Advances in Additive Manufacturing (AM) technologies have made it possible to reduce the design and prototyping costs to a minimum especially for a low-productivity material like titanium. Titanium alloys are commonly and widely used alloys in the aerospace and biomedical sector due to their advantageous material properties. This paper is an evaluation study of factors affecting the productivity characteristics of Laser Engineered Net Shaping (LENS) titanium alloy (Ti-6Al-4 V) using face milling. Some of the productivity challenges associated with titanium such as rapid tool wear, poor surface finish, and high-power consumption are explored in this paper. All materials processed using AM face the same critical problem that the manufactured part requires a post machining since AM produces relatively poor surface finish. Machining trials are conducted using the combinations of machining parameters such as spindle speed of 800 and 1600 rev/min; feed rate of 50 and 100 mm/min; and a constant depth of cut of 1 mm, respectively. Titanium being a poor thermal conductivity material, the effect of coolant was investigated using wet/dry machining. Data related to the productivity factors and material behavior under a milling trial was recorded and analyzed. The obtained data from the trials include productivity factors such as Metal Removal Rate (MRR), power consumed, and the surface finish for each plate/trial. The power consumed in dry milling was observed to be lower than that in wet milling which is contrary to the observations from conventional wet milling. The paper concludes the trends observed for LENS titanium are opposed to the trends in conventional machining such as increasing cutting speed will result in lower cutting force and power consumed. [ABSTRACT FROM AUTHOR]

B4C particle-reinforced Al matrix composite (B4Cp/Al) has excellent properties and is expected to become the mainstream of composites in the future. Due to the complex meso-structure of B4Cp/Al, this increases the difficulty of material precision machining. In addition, the current research on the PRMMCs generally focuses on SiCp/Al and the effects of machining parameters on cutting force and temperature, while the research on the effects of tool geometry parameters on material cutting is relatively rare. Therefore, the cutting mechanism of B4Cp/Al is studied by finite element simulation. Firstly, based on the meso-structure of B4Cp/Al, a three-dimensional (3D) model of the material is established. Then the mechanism of surface formation of B4Cp/Al was studied by combining cutting simulation and turning experiment. Use the simulation to study the effect of tool rake angle on material cutting surface quality. It was found that the removal mode of B4C particles, the residual stress in Al matrix after cutting, and the plastic deformation would be affected by the tool rake angle, thus affecting the cutting surface quality. After a comprehensive comparison, it is found that when the rake angle is − 5°, the cutting quality is the best. [ABSTRACT FROM AUTHOR]

During high-efficiency milling, the mechanical status of the tool system, consisting of the tool and tool holder, is constantly changing due to the high-speed cyclic cutting load and the self-excited vibration of the cutting force. The dynamic mechanical status has a significant impact on the relative position between the tool and workpiece, which directly affects the machining error. Clarification of the dynamics of the tool system subjected to high-speed cutting loads plays a key role for better understanding the energy transfer and offset distribution of the tool system. This paper presented a dynamic model of the tool system in high-efficiency milling process. The hierarchical structure and response characteristics of the energy consumption of milling tool system's interface were researched, the transmission path and distribution of the energy consumption were investigated, and a method for identifying the factors affecting the dynamic energy consumption of milling tool system's interface was proposed. The changing law in relative position of the tool system under the effect of high-speed cutting load was unveiled. Milling machining experiments were conducted to verify the accuracy of the proposed models. [ABSTRACT FROM AUTHOR]

Helical milling is widely used in aerospace as a key processing technology for Carbon fiber reinforced polymer (CFRP). However, the eccentric machining characteristics lead to an unusually complex pattern of cutting force and residual stress distribution on the work-piece during helical milling processing. Based on the Hashin failure criterion, a 3D FEM model of CFRP helical milling was built for analyzing the changing law of cutting force, then the three factors and three levels orthogonal tests were used to investigate the influence of machining parameters on the axial force, radial force, and minimum principal residual stress, finally, the multi-objective optimization based on grey correlation analysis was realized. The results showed that the errors of axial force and radial force obtained by simulation and experiment were 10.68% and 12.26%, respectively. The axial force and radial force were negatively correlated to the spindle speed, positively correlated to the axial cutting depth, and uncorrelated to the feed per tooth. The minimum principal residual stress was negatively correlated to the spindle speed, positively correlated to the feed per tooth, and uncorrelated to the axial cutting depth. The degree of influence on optimization of machining parameters was: spindle speed > axial cutting depth > feed per tooth. The corresponding average grey correlation degree differences were 0.280981, 0.216859, and 0.013422, respectively. The maximum value of grey correlation degree in the orthogonal test was 0.874372, and the corresponding optimal parameters combination was the spindle speed 8000 r/min, feed per tooth 0.03 mm/z, and axial cutting depth 0.2 mm/r. [ABSTRACT FROM AUTHOR]

Investigation into the post-processing machinability of Ti6Al4V alloy is increasingly crucial in the manufacturing industry, particularly in the machining of additively manufactured (AM) Ti6Al4V alloy to ensure effective machining parameters. This review article summarizes various AM techniques and machining processes for Ti6Al4V alloy. It focuses on powder-based fusion AM techniques such as electron beam melting (EBM), selected laser melting (SLM), and direct metal deposition (DMD). The review addresses key aspects of machining Ti6Al4V alloy, including machining parameters, residual stress effects, hardness, microstructural changes, and surface defects introduced during the additive manufacturing (AM) process. Additionally, it covers the qualification process for machined components and the optimization of cutting parameters. It also examines the application of finite element analysis (FEA) in post-processing methods for Ti6Al4V alloy. The review reveals a scarcity of articles addressing the significance of post-processing methods and the qualification process for machined parts of Ti6Al4V alloy fabricated using such AM techniques. Consequently, this article focuses on the AM-based techniques for Ti6Al4V alloy parts to evaluate and understand the performance of the Johnson–Cook (J–C) model in predicting flow stress and cutting forces during machining of the alloy. [ABSTRACT FROM AUTHOR]

The forage crop Caragana korshinskii Kom. is of high quality, and the biomechanical properties of its plant system are of great significance for the development of harvesting equipment and the comprehensive utilisation of crop resources. However, the extant research on the biomechanical properties of Caragana korshinskii Kom. is inadequate to enhance and refine the theoretical techniques for mechanised harvesting. In this study, we established a discrete element model of CKS based on the Hertz-Mindlin bonding contact model. By combining physical experiments and numerical simulations, we calibrated and validated the intrinsic and contact parameters. The Plackett-Burman design test was employed to identify the significant factors influencing bending force, and the optimal parameter combination for these factors was determined through response surface analysis. When the shear stiffness per unit area was 3.56×109 Pa, the bonded disk scale was 0.93 mm, the normal stiffness per unit area was 9.68×109 Pa, the normal strength was 5.62×107 Pa, the shear strength was 4.27×107 Pa, the discrete element numerical simulation results for three-point bending, radial compression, axial tension, and shear fracture exhibited a maximum failure force error of 3.32%, 4.37%, 4.87% and 3.74% in comparison to the physical experiments. In the cutting experiments, a smaller radial angle between the tool edge and the stem resulted in less damage to the cutting section, which was beneficial for the smoothness of the stubble after harvesting and the subsequent growth of the stem. The discrepancy in cutting force between the physical and numerical simulations was 3.89%, and the F - x (force versus displacement) trend was consistent. The multi-angle experimental validation demonstrated that the discrete element model of CKS is an accurate representation of the real biomechanical properties of CKS. The findings offer valuable insights into the mechanisms underlying crop-machine interactions. [ABSTRACT FROM AUTHOR]

As oil production increasingly transitions from shallow to deep formation, the need for efficient PDC cutters to drill through deep hard rock becomes paramount. Currently, there is a lack of effective methods for optimizing cutter shapes and their cutting parameters. This study addresses this gap by developing a rock-breaking mechanism model for PDC cutters and proposing a Stability Index (SI) based on cutting force variations during the cutting process. Using the FDEM method, we simulated the rock-breaking processes of planar, stinger, and machete cutters under various cutting depths and angles. SI and Mechanical Specific Energy (MSE) were employed as evaluation metrics to analyze the rock-breaking characteristics and determine the optimal cutting parameters for each cutter type. The results indicate that at shallow cutting depths, cutting force changes are minimal, predominantly causing plastic damage to the rock, resulting in lower stress and reduced wear on the PDC cutters. Conversely, at greater cutting depths, significant fluctuations in cutting force occur, leading to brittle failure and the generation of large cuttings. This sudden increase in cutting force can accelerate rock breaking but also increases the risk of cutter wear. Our findings suggest that the planar cutter offers stable performance with high cutting force requirements, optimal at a cutting depth of 1.5 mm and an angle of less than 20°. The stinger cutter, requiring lower cutting forces, performs best at a cutting depth of 2 mm and an angle of 20°. The machete cutter exhibits characteristics similar to the stinger cutter at shallow depths and the planar cutter at deeper depths, making it suitable for drilling at a depth of 2 mm and an angle of less than 10°. By balancing SI and MSE, this study provides a comprehensive approach to optimizing PDC cutter performance, enhancing drilling efficiency while minimizing cutter wear. [ABSTRACT FROM AUTHOR]

Application of tool-based micromachining in soft polymer has been limited due to high adhesion and low elastic modulus of this material at room temperature. This study aims to evaluate the machinability of a typical viscoelastic soft polymer and understand the effect of material and process parameters on machining performances. In this study, a micro-milling process using cryogenic-assisted cooling is proposed and the importance of temperature control toward glass transition zone was particularly addressed. To identify insight of machinability in micro domain, this article also determines minimum uncut chip thickness (MUCT) and size effects by considering the variations of cutting force and surface integrity with the ratio of h/re (uncut chip thickness (h) to cutting edge radius (re)). The experimental results reveal that consideration of size effect during micromilling of soft viscoelastic polymer helps in reduction of machined surface roughness (Sa) value. Based on the cutting force pattern, it is evaluated that higher machining stability can be achieved during cryogenic machining by reduction of specific cutting force value. Moreover, temperature range around glass transition zone yields more promising experimental outcomes, outperforming other cooling zones. [ABSTRACT FROM AUTHOR]

This paper focuses primarily on the wear behavior observed in AISI4340 steel when machining with a multi-layered coated carbide tool. Numerical and experimental examination is processed out to predict the wear performance of AISI 4340 steel along with its cutting force and temperature. In this process, four layers of different coated material are bonded together to form a multi-layered coated carbide tool. The coated thickness is assessed with the assistance of a Scanning Electron Microscope (SEM). Experimental analysis takes place with a heavy duty lathe machine equipped with an infrared thermometer and force dynamometer. Simulation is performed using DEFORM-2D software to simulate cutting forces and interface temperature, and the output results obtained have been compared with the experimental work. With the help of the SEM image, maximum crater wear depth is evaluated and analyzed. Feed plays a crucial role in increasing the chip interface temperature and cutting force. For varied feed rates, the cutting tool edge radius, depth of cut, and cutting speed are taken as the input parameters. The proposed 2D finite element model provides effective parameter values for reducing wear. Results measured indicate that the output parameter values of interface temperature and cutting force obtained from simulation and experimental investigation match each other with high accuracy. Simulation results for temperature distribution around the tool tip show that a maximum temperature of 654 °C is formed at the feed rate of 0.4 mm/rev, leading to high heat flux. For the feed rate of 0.3 and 0.2 mm/rev, there is not much deviation in heat flux around the tool tip. The maximum temperature around the tool tip is near 527 °C for both 0.3 and 0.2 mm/rev. Simulation results show that the lowest tool wear of 0.001 23 mm was obtained for a feed rate of 0.2 mm/rev, followed by 0.004 25 (0.1 mm/rev), 0.005 09 mm (0.4 mm/rev), and 0.007 14 mm/rev. [ABSTRACT FROM AUTHOR]

In this study, the effects of reinforcement ratio, drill bit material, and drilling process parameters on the cutting forces generated during the drilling of glass sphere‐reinforced polypropylene composites were investigated experimentally. Test specimens were produced by conventional injection‐moulding of glass sphere reinforced polypropylene composite materials at 5 %, 10 % and 20 % wt. ratios. High speed steel, titanium‐coated high‐speed steel, and carbide drill bits with 4 mm diameter were preferred for drilling. In addition, the drilling process was carried out on a 3‐axis computer numeric control milling machine. Three different feed rates of 0.05 mm/rev, 0.10 mm/rev, and 0.15 mm/rev and cutting speeds of 12 m⋅min−1, 16 m⋅min−1, and 20 m⋅min−1 were determined for the drilling process. In addition, Taguchi experimental optimization method, analysis of variance and scanning electron microscopy were used to investigate the morphology of the drilled surface and the wear mechanisms occurring on the drill bit due to the drilling process. The test findings showed that the maximum torque value was 54.64 N⋅mm and the maximum thrust force was 100.43 N. The optimum test parameter for cutting forces was observed as C1D3FR1CS3. Drill parameter had an effect of 40.96 % on thrust force and 36.11 % on torque. [ABSTRACT FROM AUTHOR]

Rohu fish (Labeo rohita) fillets were coated with 2.5% to 25% soy protein isolate (SPI) to evaluate their ability to reduce fat uptake. The coating pickup of fish fillets increased with increasing coating concentration. Fillets coated with 15% SPI showed the highest coating pickup value of 18.29% and reduced fat uptake by 57.78%. As revealed by lowered carbonyl and sulfhydryl contents, SPI coating protected proteins from oxidation during deep-frying. Increasing coating concentration decreased the hardness, chewiness, and cutting force of coated fish fillets. Therefore, the aforesaid coatings could be recommended for making low-fat fried fish fillets with 15% SPI. [ABSTRACT FROM AUTHOR]

Micro-milling technology is widely used in the manufacturing of micro three-dimensional complex parts in aerospace, mechanical equipment, biomedical devices, electronic components, and other fields due to its advantages of high machining accuracy, small size, and complex surface. Consequently, understanding its machining process is essential. This study proposes a time-varying dynamic micro-milling process model with the effects of tool runout, tool wear, and cutting status and explores the stable cutting domain of real-time machining. Considering the time-varying characteristics of the cutting process, combined with measured data and particle filtering method, the cutting force coefficients and tool wear parameters in the dynamic model at different times are identified. The dynamic equation of micro-milling is derived using a discrete method, and the stability of the cutting process is evaluated. Multiple cutting experiments are conducted on the Al6061, and the test data are compared with simulated values. The comparison results show that the accuracy of the proposed model in predicting the cutting state can reach 100%, and the average error of cutting force prediction is 7.72%. The research results can provide theoretical guidance for the safety evaluation of micro-milling and the selection of machining conditions. [ABSTRACT FROM AUTHOR]

The surface geometry of polycrystalline diamond compact (PDC) cutters has a considerable influence on their rock-cutting mechanism. In the study reported here, to study the mechanism for rock crushing by saddle PDC cutters, two-dimensional and three-dimensional finite-element models of such cutters cutting granite were established. The two-dimensional simulation results were used to analyze the crack generation and expansion forms when a saddle PDC cutter cuts rock, and the results show that it mainly crushes the rock via joint tensile and shear action. Next, the wear resistance and cutting performance of saddle PDC cutters were analyzed by simulation and experiment, and both were better than those of conventional PDC cutters. The residual stresses on the surface of a notch cut by a saddle PDC cutter were extracted from the 3D model, and it is concluded that they are mainly compressive stresses. Cutting models for mixed arrangements of saddle and conventional PDC cutters were established, and analyses were conducted of how the cutting-depth difference between the front and rear cutters in the same-track cutting scheme and the spacing of the front cutters in the different-track cutting scheme affect the cutting force of the rear cutters, the mechanical specific energy, and the cutting stability. The results show that for the same-track cutting scheme, the optimum cutting depth difference between the front and rear cutters is 0.1–0.2 mm, and for the different-track cutting scheme, the optimum spacing between the front cutters is 17 mm. Finally, the characteristics of the cutting damage areas of different types of PDC cutters are discussed. The present results help in revealing the rock-breaking mechanism of saddle PDC cutters and provide theoretical support for designing hybrid PDC bits. Highlights: The generation and propagation modes of rock cracks during the cutting of rock by saddle PDC cutters are revealed and compared with those of conventional PDC cutters. By extracting and comparing the residual stresses on their cut surfaces, the impacts of saddle and conventional PDC cutters on the surrounding rock are analyzed. The wear resistance, cutting stability, and other factors of saddle and conventional PDC cutters are investigated, and the results show that saddle PDC cutters have superior performance. The optimal parameters for a mixed cutter arrangement of saddle and conventional PDC cutters are determined via simulation, and the geometric influence coefficient n is defined. [ABSTRACT FROM AUTHOR]

CFRP/Ti6Al4V stacks are widely employed in aerospace, automotive and marine applications owing to their superior properties. However, machining these stacked structures pose challenges due to the intrinsic difference in the mechanical properties of CFRP and Ti6Al4V. Such difference can induce distinct failure mechanisms and chip formation processes compared to those observed in individual materials. This paper presents an explicit finite element (FE) modeling to predict the cutting forces and analyze the induced damage during the orthogonal cutting process. The proposed FE model is validated using available experimental data for separate CFRP and Ti6Al4V conditions before being applied to simulate the cutting behavior of CFRP/Ti6Al4V stacks. The effects of fiber angles, cutting sequences and cutting parameters on the cutting performance and damage mechanism of CFRP/Ti6Al4V stacks are investigated in detail. This work provides insights into the cutting behavior of CFRP/Ti6Al4V stacks and facilitates the optimization of machining process for such composite system. [ABSTRACT FROM AUTHOR]

Severe tool wear significantly impacts both the tool life and machined surface quality when machining difficult-to-cut materials. Sufficient cooling and lubrication capacity provided by cutting fluid can effectively mitigate tool wear, whereas conventional flood cooling methods consume excessive amounts of cutting fluid, raising serious environmental concerns. The atomization mode of cutting fluid is accompanied by a minimum quantity of cutting fluid, and it has demonstrated exceptional cooling and lubrication performance for machining difficult-to-cut materials. In this work, various sustainable cooling conditions were employed, including dry cutting, high-pressure air cooling (HPAC), air atomization of cutting fluid (AACF), and ultrasonic atomization of cutting fluid (UACF). A series of experiments were implemented to investigate the tool wear behavior during the milling process of ultra-high-strength steel under different cooling conditions. The effects of tool wear evolution on the milling force, surface quality, and chip morphology were thoroughly analyzed. Results showed that micro-chipping, macro-chipping, and breakage were the primary wear evolution forms of the tool in HPAC condition, while the tools experienced abrasion, chipping, and breakage in the dry, AACF, and UACF processes. The occurrence of severe tool wear, leading to poor surface quality and chip tearing, was observed as the maximum flank wear width VBmax exceeded 0.2 mm. Compared to other cooling conditions, the UACF process exhibited the lowest tool wear and resultant milling force, as well as the best surface quality, attributed to the exceptional cooling and lubrication performance of droplets generated through ultrasonic atomization. [ABSTRACT FROM AUTHOR]

Predicting cutting forces in hard turning optimizes toolpaths, improving machining efficiency and precision, minimizing tool wear, and enhancing manufacturing processes. This study assesses the potential of ensemble machine learning models for predicting machining force components during the hard turning of AISI 52100 bearing steel. Firstly, it conducts a comprehensive evaluation of Random Forest, Gradient Boosting, XGBoost, and CatBoost machine learning models using experimental data collected during AISI 52100 bearing steel turning with a CBN cutting tool. Cubic Spline-based data augmentation is employed to enrich the data, further enhancing prediction quality. A comparative analysis of the considered models on both original and augmented datasets reveals significant performance improvements associated with the utilization of augmented data. Moreover, this study utilizes SHAP (SHapley Additive exPlanations) to elucidate model predictions, providing insights into the contribution of each feature. Results indicate that ensemble learning methods, particularly CatBoost and XGBoost, demonstrate satisfactory predictive results with an averaged R2 of 0.96 and 0.945, respectively. Ensemble models like CatBoost and XGBoost, coupled with data augmentation, prove effective in predicting cutting forces during hard turning, emphasizing the potential for enhanced machining optimization. [ABSTRACT FROM AUTHOR]

Silicon carbide particle-reinforced aluminum matrix composites (SiCp/Al) have been widely used in many areas due to their good physical and mechanical properties. However, because the material contains SiC particles with high hardness, processing is difficult and the processing quality of milling is poor. Ultrasonic vibration-assisted longitudinal torsion milling (LTUVAM) has great advantages in cutting difficult materials because it can effectively reduce the cutting force and cutting heat and improve the surface quality of the workpiece. Therefore, the kinematic analysis of LTUVAM is carried out, the material removal mechanism of 60% SiCp/Al is studied by the method of simulation and experiment, and the effects of machining parameters on the cutting force, cutting heat, and surface quality of the material were analyzed and using the traditional milling (CM) compared. The simulation and experimental results show that LTUVAM can improve the particle crushing rate, effectively reduce the cutting force and cutting heat under the relevant parameters, and improve the surface quality. [ABSTRACT FROM AUTHOR]

Micro milling is a state-of-the-art micro manufacturing method employed, for instance, in the context of prototyping applications. Due to the high specific cutting forces and small tool diameters inherent to micro milling, tool wear represents a significant challenge for the fabrication of large, high-quality structures. In conventional cutting applications, ceramic tool substrates have been demonstrated to exhibit greater wear resistance than cemented carbides. In the case of micro milling of polymethylmethacrylate (PMMA), all-ceramic micro end mills made from zirconia (Y-TZP) have been observed to exhibit less tool wear than common cemented carbide micro end mills. In previous experiments, these tools exhibited a feed per tooth-dependent wear behavior, regardless of the spindle speed employed. The objective of this study was to investigate the wear behavior of the all-ceramic micro end mills at higher feeds per tooth (up to 7.5 µm) and spindle speeds (up to 110,000 rpm) in PMMA. The objective was to fully characterize the interactions between the all-ceramic micro end mills and the milling parameters for this thermoplastic workpiece material. The wear at the cutting edge was quantified by analyzing the topography with an atomic force microscope, and the results were correlated with the cutting forces and process outcomes. The results were found to be highly sensitive to the spindle speed used, with higher speeds leading to higher temperatures in the cutting zone and thus softening of the PMMA material. In general, micro milling parameters of 110,000 rpm and a feed per tooth of 5 µm resulted in significantly reduced tool wear with no adverse effect on surface quality when micro milling PMMA with all-ceramic micro end mills. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polymers (CFRPs) are widely used in biomedical, optical and tissue engineering applications. Nevertheless, machining these materials significantly differs from other materials and faces special challenges. In recent years, ultrasonic drilling as a new technique was introduced in the field of composites' machining. This study evaluates the effects of nano-graphene incorporation and machining parameters including feed rate, tool type in both conventional and ultrasonic vibration assisted drilling. Besides, statistical analysis is conducted in order to identify contribution of the parameters. The results suggest that feed rate is the most influential factor on cutting force and hole quality including delamination and hole roundness. In addition, in order to acquire the best optimal process parameters, desirability method was established. That was indicated the best hole quality is achieved in CFRP samples at the least feed rate by the HSS-8% cobalt tool (M42 tool) and in presence of the ultrasonic vibration. [ABSTRACT FROM AUTHOR]

The novelty of this study is to develop the oscillation, amplitude and periodical behavior of thermal and concentration boundary layers of transient Darcian nanofluid flow over stationary circular cylinder. For the improvement of cutting forces, lubrication and cooling in machining operations, workpiece cutting temperature and tool durability, the nanofluids have significant role with the effects of thermophoretic nanoparticles and rate of reactions. The aim of current work is to deduce the oscillations, amplitude, and frequency analysis of mass and heat transmission of Darcian nanoparticles motion around porous stretchable cylinder with thermal radiation and heat generation effects. For physical and thermo parameters, the governing mathematical equations are transformed into convenient equations. The smooth and similar programing algorithm is developed in FORTRAN language (Lahey‐95) by using primitive and oscillatory stokes transformations. The primitive steady and oscillating model is solved numerically by using Gaussian elimination and implicit finite difference techniques. The steady outcomes of velocity, temperature, and concentration distributions are plotted for various physical parameters within defined boundary values. The range of parameters such as 0.01≤ξ1≤2.0$0.01 \le {\xi }_1 \le 2.0$, 0.01≤ξ1≤3.0$0.01 \le {\xi }_1 \le 3.0$, 1.0≤Rd≤25.0$1.0 \le {R}_d \le 25.0$, 0.1≤Fr≤2.0$0.1 \le {F}_r \le 2.0$, 0.1≤NT≤1.0$0.1 \le {N}_T \le 1.0$, and 0.1≤γ≤1.5$0.1 \le \gamma \le 1.5$ is used. The steady results are again used to display the oscillatory skin friction, oscillating heating rate, and oscillating mass transport around α=π/3$\alpha = \pi /3$ and α=π$\alpha = \pi $ positions of stretching porous cylinder. The increasing amplitude of velocity and temperature slip distribution grows well as diffusion‐convection parameter and thermal radiation increases at both angles. The slip temperature and slip concentration grows significantly as convective parameter increases. The impact of thermophoresis and rate of reactions enhances the oscillations and amplitudes of mass and heat transmission around stretchable cylinder as porous effect decreases. It is very important in nanofluid lubrications, drilling, rotating, milling, and cutting tools machines. [ABSTRACT FROM AUTHOR]

Saw rotational speed critically influences cutting force and surface quality yet is often destabilized by variable cutting resistance. The sensorless detection method for calculating rotational speed based on current ripple can prevent the contact of wood chips and dust with Hall sensors. This paper introduces a speed control system for brushed DC motors that capitalizes on the linear relationship between current ripple frequency and rotational speed. The system achieves speed regulation through indirect speed measurement and PID control. It utilizes an H-bridge circuit controlled by the EG2014S driver chip to regulate the motor direction and braking. Current ripple detection is accomplished through a 0.02 Ω sampling resistor and AMC1200SDUBR signal amplifier, followed by a wavelet transform and Savitzky–Golay filtering for refined signal extraction. Experimental results indicate that the system maintains stable speeds across the 2000–6000 RPM range, with a maximum error of 2.32% at 6000 RPM. The improved ripple detection algorithm effectively preserves critical signals while reducing noise. This enables the motor to quickly regain speed when resistance is encountered, ensuring a smooth cutting surface. Compared to traditional Hall sensor systems, this sensorless design enhances adaptability in agricultural applications. [ABSTRACT FROM AUTHOR]

The article presents the research on turning the titanium alloy Ti6Al4V with uncoated carbide blades and physically coated with PVD and chemically CVD. By examining the processed surfaces using the contact method, it was found that the chemically applied coating allows one to obtain the best 3D roughness. Using finishing cutting parameters and CVD-coated blades, it is possible to obtain a surface with a roughness of Sq at the level of 0.7 μm and Sz 2 μm. Cutting force tests have shown that applying coatings to the cutting blade increases the total cutting force by approximately 20%. Additionally, on the basis of microscopic observations, it was found that thermal and adhesive wear occurs on the surfaces of coated blades. Tool coatings have no influence on the shape of the chips produced. The grey relational analysis performed showed that the best turning results for the Ti6Al4V alloy are obtained when using an uncoated HX insert with a feed of 0.08 mm/rev and a cutting speed of 70 m/min. The results of this analysis also indicate that the tested blades, which are not recommended for the machining of superalloys, should not be used to turn the Ti6Al4V alloy. [ABSTRACT FROM AUTHOR]

Workpiece surface quality is a critical metric for assessing machining quality. However, due to the complex coupling characteristics of cutting factors, accurately predicting surface roughness remains challenging. Typically, roughness is measured post-machining using specialized instruments, which delays feedback and hampers timely problem detection, ultimately resulting in cutting resource wastage. To address this issue, this paper introduces a predictive model for workpiece surface roughness based on the finite element (FE) method and advanced image processing techniques. Initially, an orthogonal turning experiment was designed, and an FE cutting model was constructed to assess the distribution of cutting forces and temperatures under varying cutting parameters. Image processing methods (including mesh calibration, edge extraction, and contour fitting) were then applied to extract surface characteristics from the FE simulation outputs, yielding preliminary estimates of surface roughness. By employing range and regression analyses methods, this study quantitatively evaluates the interdependencies among cutting parameters, forces, temperatures, and roughness, subsequently formulating a multivariate regression model to predict surface roughness. Finally, a turning experiment under actual working conditions was conducted, confirming the model's capacity to predict the R a trend with an accuracy of 85.07%. Thus, the proposed model provides a precise predictive tool for surface roughness, offering valuable guidance for optimizing machining parameters and supporting proactive control in the turning process, ultimately enhancing machining efficiency and quality. [ABSTRACT FROM AUTHOR]

This work concerns an experimental investigation dealing with the machinability of 60CrMoV18-5 cold-work tool steel under dry CNC hard turning conditions using a CBN cutting insert. A response surface experiment based on the central composite design was set to conduct dry CNC hard-turning experiments with three different levels for cutting conditions, cutting speed Vc (m/min), feed rate f (mm/rev), and depth of cut α (mm) while selecting main cutting force and surface roughness Ra as the two machinability responses. The results were analyzed by applying analysis of variance (ANOVA). The effect of cutting conditions on main cutting force and surface roughness was studied through contour plots. Full quadratic regression models were generated to model the relationships between inputs and outputs. Finally, the NSGA-III algorithm was applied to simultaneously optimize the selected machinability parameters by providing beneficial values for determining cutting conditions. The results have shown that surface roughness is mainly affected by feed rate and cutting speed, whereas main cutting force is affected by depth of cut and feed rate. [ABSTRACT FROM AUTHOR]

To thoroughly investigate the rock-breaking characteristics of conical pick under various attack angles in linear cutting, aiming to optimize conical pick parameters, enhance rock-breaking efficiency, and reduce energy consumption. Constructing matDEM numerical model for rock breaking by conical pick, a series of linear cutting numerical simulations were designed based on varying attack angles, to obtain key parameters such as conical pick force, crack propagation patterns and cutting efficiency. The results show that the average cutting force and the normal force of the conical pick increased with the increase of the attack angle of the conical pick. The main mode of rock failure changed from tensile failure to shear failure with the increase of the attack angle. The optimal attack angle for rock fragmentation efficiency was 40° at a cutting depth of 12 mm, and it was between 55°-60° at a cutting depth of 15 mm. Different attack angles lead to distinct failure modes between the conical pick and the rock, thus affecting the energy conversion and efficiency during the rock-breaking process. The conclusions of this study can provide a reference basis for the optimization of structural parameters in conical pick design, thereby enhancing the mining efficiency of cantilever roadheaders. [ABSTRACT FROM AUTHOR]

The cutting force of pick is an important parameter to measure whether it can achieve rock breaking, which is crucial to the design and selection of tunneling machinery. Based on the rock cutting test data, the cutting force feature set including training set and test set was constructed, and the cutting force prediction ability of the conical pick with different machine learning methods was studied. Mean square error and coefficient of determination were adopted as indicators for assessing the predictive power of models. The study shows that the polynomial regression model has the best predictive effect, which outperforms the traditional computational model and it is most suitable for modelling the cutting force prediction. The linear regression model has poor performance for cutting force prediction, which are not suitable for modelling the cutting force prediction. The decision tree model has slightly worse performance relative to the polynomial model, but it also has some application prospects. This study provides a new solution for the prediction of the cutting force acting on the conical pick. [ABSTRACT FROM AUTHOR]

The cutter of the hand-held tea picker is the key cutting component in the efficient tea harvesting process. In order to solve the problems of large cutting resistance and uneven incision during tea picking, this study fully applied the bionics principle to combine the excellent cutting performance of Aeolesthes induta Newman's mandibles with the tea cutter, which extracted and fitted the tooth profile structure curve of the upper edge of the Aeolesthes induta Newman's mandibles. The trapezoidal teeth on the reciprocating cutter of ordinary hand-held tea-picking harvesters were optimized by the fitted curve, and a new tea cutter with the shape of Aeolesthes induta Newman teeth was obtained, which included four kinds of bionic tea-harvesting cutters. The multi-body system software ADAMS 2020 and finite element analysis software ANSYS 2024R1 were used to compare the kinematics, statics and explicit dynamics of cutting properties of the four bionic cutters and common cutters with ordinary trapezoidal teeth and saw teeth. The simulation results showed that the maximum equivalent elastic strain and the maximum cutting force during the cutting operation were reduced by 36.7% and 42.89%, respectively, for the cutting teeth of the bionic tea-harvesting cutter #4 compared with that of the cutter with ordinary trapezoidal teeth. The bionic tea-harvesting cutter designed in this study has better cutting performance than the cutter with traditional cutting teeth, which can effectively reduce the cutting force and improve the flatness and cutting quality of the cutting surface. [ABSTRACT FROM AUTHOR]

The energy efficiency in metal cutting is, sometimes, very low. Recent studies show that the energy consumed for detaching chips represents only about 15% of the total energy involved in material machining. The available solutions for energy optimization in cutting processes mentioned are the improvement of manufacturing equipment, the optimization of processes, and appropriate production scheduling. Already-performed research shows that to increase energy efficiency, the cutting force must be reduced, for example, by reducing the depth of the cut and by increasing the feed rate. However, this is applicable when the cutting force is quasi-constant during the process, which is not the case for gear teeth cutting when the cutting force significantly varies. The present paper proposes a new solution for energy efficiency increase in gear teeth cutting, namely, the smoothing of the cutting force variation during the machining process, by keeping the area of the detached chip section quasi-constant during the cutting process. This can be reached by replacing the constant rolling feed, currently used in gear teeth cutting, with a rolling feed that varies after an appropriate law. An algorithm dedicated to implementing this solution has been developed. It uses graphical modeling in CATIA to find the variation in the detached chip area. Original MatLab R2018a applications were developed (i) to identify the analytical form of the law that approximates this variation and (ii) to find the variation law of the feed during the rolling motion, if imposing a constant area of the detached chip. The algorithm was successfully applied in the cases of toothing with a rack tool (by slotting) and with a pinion cutter (by slotting and turning). A technical solution for method implementation in practice is also presented. [ABSTRACT FROM AUTHOR]

This study addresses the necessity for a more profound comprehension of the mechanical behavior and fracture mechanisms of tree branches during impact pruning. The methodologies of the research are to develop a failure model of impact-cutting mechanics and a tool–branch interaction model using the finite element method (FEM). The validation of the model was conducted through the measurement of cutting forces and cross-sectional morphology in the field. A comparative analysis between experimental and simulation data revealed an average relative error below 15% for cutting force and below 10% for the cross-sectional ratio, thereby confirming the accuracy of the model. The findings indicate the presence of plastic deformation within the cutting zone, with elastic deformation prevailing in the surrounding region. As the branch approaches the yield point, the phenomenon of plastic deformation intensifies, resulting in a notable increase in internal energy demands, particularly in larger branches. The optimal pruning diameter was identified as 15 mm. An increase in cutting velocity raises the peak cutting force by 460.9 N per m/s, while a 1° increase in the blade wedge angle adds 34.9 N. A reduction in normal stress by increasing the tool back angle improves energy efficiency. This study provides insights to optimize pruning practices, enhancing efficiency and precision. [ABSTRACT FROM AUTHOR]

Machining of polycarbonate workpieces with ultrasonic modification of the force is considered. Milling with different values of the mill's thermal conductivity and the cutting speed—including milling in the presence of ultrasound—is analyzed by means of numerical modeling. When the thermal conductivity increases, the temperature decrease in the mill–chip and mill–workpiece contact zones is greater when milling polycarbonate workpieces than when milling steel. The presence of ultrasound lowers the main component of the cutting force and the temperature in the mill–chip and mill–workpiece contact zones. In machining steel, the temperature in the surface layers falls significantly. In the contact zones, the temperature declines more with increase in cutting speed. [ABSTRACT FROM AUTHOR]

The article presents an application of acoustic emission (AE) signals as a diagnostic criterion of the current cutting capability of a grinding wheel under varying grinding conditions that simulate tool wear modes. The influence of cutting modes and grinding conditions on the controlled AE parameters, the components of the cutting force, and the temperature of the machined surface is established. [ABSTRACT FROM AUTHOR]

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With the continuous development of the aerospace, defense, and military industry, along with other high-end fields, the complexity of machined parts has gradually increased. Consequently, the demand for tool intelligence has also strengthened. However, traditional tools are prone to wear during cutting due to high cutting forces, high temperatures, and vibrations. Intelligent tools, in contrast to traditional ones, integrate sensors into their design, allowing for real-time monitoring of the cutting status and timely prediction of tool wear. The application of intelligent tools in machining significantly enhances machining quality, increases productivity, and reduces production costs. In this review, first, the tool wear monitoring methods were classified and discussed. Second, the intelligence and innovation of sensors in monitoring cutting force, temperature, and vibration were introduced, and the commonly used types of sensors for online monitoring of cutting force were detailed. Furthermore, different types of sensors in tool wear were discussed, and the advantages of multi-sensor monitoring were summarized. Some urgent issues and perspectives that need to be addressed were proposed, providing new ideas for the design and development of intelligent tools. [ABSTRACT FROM AUTHOR]

Knowledge of plants' mechanical properties and behavior is one of the essential factors in the design of harvesting and post-harvesting devices. In this study, horticulture, medicinal, and food plants of Aloe Vera were cut using a flat blade. Aloe Vera leaves are cut from the cross-section, and the force and energy required for cutting them were measured using Zwick /roll universal testing machine. The effect of cutting angle (0, 30, and 45 degrees), cutting speed (150, 250, 350, and 450 mm/min), and thickness of Aloe Vera leaves (1, 2, and 3 cm) on the force and energy required for cutting were investigated. To achieve this, response surface methodology was used, the results of which were compared with the artificial neural network method. The results of this study indicated that by increasing the cutting angle, cutting rate (cutting speed), and thickness of the leaves of the Aloe Vera plant, the energy required for its cutting decreased. The most optimal case for cutting the Aloe Vera plant in the case of cutting angle is 45 degrees, the cutting speed is 450 mm/min, and the thickness of Aloe Vera leaves is 3 cm, in which the required energy for cutting and cutting force is equal to 3.45 J and 4.99 N respectively. This study showed that Response Surface Methodology (RSM) is suitable for evaluating optimum conditions in Aloe Vera cutting experiments and is more accurate than the Artificial Neural Network (ANN) method.

Improving hard machining efficiency is a growing concern in industrial production, but environmentally friendly characteristics are guaranteed. Nanofluid minimum quantity lubrication (NF MQL) has emerged as a promising solution to improve cooling and lubrication performance in the cutting zone. This paper utilizes Box-Behnken experimental design to identify the influences of Al2O3/MoS2 hybrid nanofluid MQL hard turning using CBN inserts on surface roughness and cutting forces. Mathematical models were employed to predict thrust cutting force, tangential cutting force, and surface roughness in hard turning under MQL conditions using Al2O3/MoS2 hybrid nanofluid. The study results reveal that the minimum thrust force (Fy) occurs at a nanoparticle concentration of 0.5%, air pressure of 5 bar, and flow rate of 236 l/min. In comparison, the tangential force (Fz) reaches its minimum at a nanoparticle concentration of 0.8%, air pressure of 5 bar, and airflow rate of 227 l/min. The minimum surface roughness was achieved with a nanoparticle concentration of 1%, air pressure of 4.7 bars, and airflow rate of 186 l/min. Additionally, based on the multi-objective optimization, an optimal parameter set of NC=1%, p=5 bar, and Q = 210 l/min was identified to bring out the minimal values of surface roughness (Ra) of 0.218 µm, thrust force (Fy) of 115.9 N, and tangential force (Fz) of 93.3 N.

An experimental study is made to understand the deformation characteristics and failure mechanism of sands subjected to severe plastic deformation in the ploughing model setup of in-plane orthogonal cutting. The cutting experiments were performed on sands over 3 orders of strain rates. High-speed imaging and concomitant image analysis were performed using the Particle Image Velocimetry algorithm to obtain the whole field velocity measurements of the material flow. The velocity field maps of the near tool tip region demonstrate a sharp change in the motion of sand particles along with the formation of a dead zone. The effective strain rate maps show regions of intense localized plastic deformation- termed "shear bands". The inclination angle of these bands evolved periodically with time and showed a decreasing trend due to an increase in the surcharge and effective depth of cut. The morphology and overall characteristics of these mesoscale structures (shear bands) do not change significantly with strain rate. The cutting force signatures were oscillatory and suggested cyclic material softening (dilation)—hardening (compaction) ahead of the tool, which is also reflected in the periodic repositioning of shear bands. The limit equilibrium-based model was adequate to predict the tool-cutting forces well, even with the significant variation in strain rates. [ABSTRACT FROM AUTHOR]