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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]

The machining of aerospace deep cavity parts was prone to issues such as chatter. Currently, discrete-edge end mills are commonly employed in milling these parts, yet the vibration reduction mechanism of the cutter and the rationality of the distribution position of the chip-split groove have not been systematically studied. Consequently, a design method of distribution position of chip-split groove of discrete-edge end mill was proposed. Initially, the correlation between the discrete parameters of discrete-edge end mills and the eigenvalue of cutting vibration was examined to elucidate how the structural characteristics of discrete-edge end mills impact vibration. Subsequently, the impact of discrete-edge end mill structure, tool-work contact system, and cutting parameters on vibration was sequentially assessed. The effect of discrete parameters on the dynamic characteristics and cutting forces of the end mill was investigated, and the vibration reduction mechanism of discrete-edge end mill was revealed. Furthermore, the distribution position of chip-split groove of the discrete-edge end mill was optimized based on the Improved Grey Wolf Algorithm (I-GWO). The optimized parameters were as follows: a width of 1 mm, a total of 4 grooves, arranged alternately with varying density. Finally, the design method of distribution position of chip-split groove of discrete edge end mill was proposed, and the effectiveness of the method was verified by experiments. This method serves as a foundational reference for the design and production of discrete-edge end mills. [ABSTRACT FROM AUTHOR]

In this manuscript, a laser ablation-assisted step milling (LAAM(S)) process was proposed, building upon the foundation of laser-ablation assisted overall milling (LAAM(O)). The model of the oxidation mechanism of SiC f /SiC composites was developed to explain the evolution of material properties with laser assistance. The results of the oxidation revealed that the material undergoes melting and evaporation, forming an ablation layer, and the thickness of the ablation layer is positively correlated with laser power. In comparison to CM and LAAM(O), LAAM(S) demonstrates notable reductions in milling forces and temperatures, with corresponding decreases in tool wear of 55 μm and 30 μm respectively. These improvements are attributed to the porous and loosely adherent ablation layer, facilitating easier removal，demonstrating the effectiveness of the developed machining method. Unlike CM and LAAM(O), LAAM(S) prevents tool edge chipping and reduces surface damages such as fiber fracture and matrix fragmentation. The machining efficiency was quantitatively evaluated. The processing time reduced by 13.65 % in LAAM(S) compared to LAAM(O) when the milling distance reached 500 mm. This indicates that LAAM(S) offers superior efficiency in long-distance processing. Therefore, LAAM(S) proves to be a feasible and effective method for improving the machinability and efficiency of SiC f /SiC composites. [ABSTRACT FROM AUTHOR]

The use of carbon fiber reinforced polymers (CFRP) is crucial in industries, such as aerospace, automotive, and marine, due to their excellent strength-to-weight ratio and corrosion resistance. However, machining CFRP is challenging due to its abrasive nature, which can cause premature tool wear. Some of the commonly used processes for machining these materials are dry milling and abrasive water jet machining (AWJM), which offer the best alternatives from an environmental point of view. This article presents an analysis of the defects and surface quality obtained in CFRP after machining by AWJM and milling. For this purpose, combinations of relevant parameters have been chosen for each process: cutting speed and tool wear in milling and traverse feed rate and hydraulic pressure in AWJM. The results obtained have been evaluated from two points of view: macroscopically, through the evaluation of delamination, and microscopically, through the study of the roughness in terms of Ra. Furthermore, a discussion on functional, environmental, economic, and social terms has been made between both processes. In summary, each machining process generates a specific type of delamination: Type II in milling and Type I in AWJM. In addition, the best Ra results are obtained for pressures of 1200 bar in AWJM. [ABSTRACT FROM AUTHOR]

Intelligent monitoring and maintenance protocols are undoubtedly crucial for improving manufacturing processes. Accordingly, machine learning techniques and predictive control models have been customized and optimized to account for the specific characteristics of the processes under investigation. In this context, the management of manufacturing processes in a “smart way” requires the development of specific models based on input-output empirical data. The aim of the proposed research was to develop an easily customizable application integrated into a milling process executed at the laboratory level. The application was designed to identify and record the operator, the order and the specific work sequences. It also supports the operator in setting processing parameters according to the type of work sequence to be performed. The application analyses specific process outputs, such as the wear growth on the inserts of the cutter in relation to the main input process parameters: depth of cut, feed rate, and spindle speed. This analysis is implemented by leveraging empirical evidence. [ABSTRACT FROM AUTHOR]

This study investigates the performance of DLC-coated 3-flute Ø 12 mm WC-Co (10%) end mills in the high-speed machining (226 m/min) of Al7075 Aluminum alloy, with high-pressure (20 bar) cooling applied in all tests focused on the cutting zone. Rolled blocks with dimensions of 150 × 350 × 150 mm were used as workpiece material. Slot milling was preferred as a test method for machining tests. Each end mill machined 757 slots with a length of 350 mm at a depth of 3 mm, and a total volume of 9150 cm3 was removed with each tool. In total, three groups of endmills were tested. A 1 is a specially designed endmill for aluminum machining and was tested in an uncoated state, while A 2 has the exact same geometry as A 1 and was coated with tetrahedral amorphous carbon (ta-C), which is a form of Diamond-Like Carbon (DLC) coating. Finally, the A 3 endmill was tested as an industrial comparative designed for aluminum machining, which was also ta-C coated. Performance tests have shown that ta-C coating significantly prevented the formation of the built-up edge. In addition, it reduced the average bending moment on the tool by 20%–25% by acting as a lubricant. It has been observed that DLC coating reduces tool wear. It was determined that flank wear was reduced by 28% and rake wear by approximately 58% in the A 2 tool compared to the uncoated tool. The DLC-coated tools also provided smaller chips and improved chip control. [ABSTRACT FROM AUTHOR]

This article focuses on research in the machining of zirconia crowns for dental implants. Its goal is to find the most suitable cutting parameters that significantly affect the final surface roughness of the crowns for dental implants. This study conducts investigations and experiments to specify the cutting parameters that achieve the optimal surface roughness of zirconia crowns for dental implants. The experiments were designed to precisely determine the cutting parameters that influence the surface roughness of zirconia crowns. The results of this study provide important insights for improving the manufacturing process of zirconia crowns with the specified most suitable cutting parameters. This research contributes to the enhancement of zirconia crown manufacturing techniques and the improvement in the quality and effectiveness of dental implants. [ABSTRACT FROM AUTHOR]

Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. While the phenomenon is well known, experimental identification of process damping model parameters can limit pre-process parameter selection that leverages the potential increases in material removal rates. This paper proposes a physics-informed Bayesian method that can identify the cutting force and process damping model coefficients from a limited set of test cuts without requiring direct measurements of cutting force or vibration. The method uses time-domain simulation to incorporate process damping and provide a basis for test selection. New strategies for efficient sampling and dimensionality reduction are applied to lower computation time and minimize the effect of model error. The proposed method is demonstrated, and the identified cutting and damping force coefficients are compared to values obtained using machining tests and least-squares fitting. [ABSTRACT FROM AUTHOR]

Milling is traditionally the most used machining method when manufacturing complex gas turbine components. In particular those made from nickel-based superalloys. However, for larger free form surfaces, grinding may be an efficient alternative that could be used throughout the complete manufacturing route, from roughing to finishing. Hence, in this work the two processing methods has been compared in regard to surface integrity and productivity. Machining tests have been performed on case plates of heat-treated Alloy 718 using best practise setting for roughing and finishing with grinding and milling. The surface integrity of the work pieces was evaluated regarding surface topography, residual stresses, and deformation. This comparison showed that the main advantage with grinding is the ability to switch between roughing and finishing by just altering the depth of cut. Further, grinding offers lower surface roughness, compressive residual stresses, and significantly lower degree of deformation. From a productivity perspective, deep grinding may offer high material removal rates and ability to machine several work pieces in the same setup. However, grinding is limited to simpler free form geometries and may result in minor surface damages and abrasive surface residue. For selection of machining strategy, advantages and drawbacks shown in this work need to be considered for the application at hand in respect to productivity, surface integrity and requirements on fatigue life. [ABSTRACT FROM AUTHOR]

With the flood cooling technique approach, it is impossible to fulfill the concerned environmental regulations and increase productivity while machining material that is infamously tough to cut. To address the conscious environmental regulation in the metal cutting industry, an effect must be made to reduce the industry process impact on environmental pollution along with manufacturing process optimization. Therefore, an eco-friendly MQL technique was investigated associated with machinability characteristics and compared results with dry condition while end milling of Inconel 825 material. The results revealed that MQL significantly reduced cutting temperature (CT) and surface roughness (Ra) to maximum levels of 70% and 43%, respectively. Further, optimum conditions were found using Taguchi method under MQL cooling. Additionally, using 3D surface plots, the interaction impact of process parameter on "Ra" has been investigated. For end milling Inconel 825 material, the MQL machining method has been proven as the most feasible alternative over dry condition. [ABSTRACT FROM AUTHOR]

Aluminum alloys used in monolithic parts for aerospace applications are subjected to distortion and residual stress (RS) generated by milling, affecting the product fatigue life. Particularly, the change in RS with depth (z) has a characteristic distribution with a maximum compressive RS at a z several tens of micrometers from the surface; however, the RS value depends on the measurement method used. In this study, the RS distribution with z from the surface after milling was measured for the AA7050-T7451 aluminum alloy by two-dimensional X-ray diffraction (2D method). The results were compared with those of four prior measurement methods, and the validity of 2D method was verified. The changes in subsurface RS with z showed similar distributions under all measurement conditions except when cos(α)-XRD was employed. The 2D method provides high repeatability. The in-plane RS distribution was also measured using 2D method to investigate the effect of milling conditions on this distribution. The RS values varied markedly depending on the measurement position, particularly at a small collimator diameter of 0.146 mm, allowing detection of localized extreme RS values. The maximum RS at z = 0 mm was − 85.6 MPa at a cutting speed of vc = 200 m/s and feed per tooth of fz = 0.05 mm, while it was − 16 MPa for vc = 450 m/s and 6.8 MPa for fz = 0.2 mm, revealing that the compressive RS changes to tensile RS as vc and fz increase.

Machining process involves numerous variables that can influence the desired outcomes, with surface roughness being a critical quality index for machined products. Surface roughness is often a technical requirement for mechanical products as it can lead to chatter and impact the functional performance of parts, especially those in contact with other materials. Therefore, predicting surface roughness is essential. This dataset comprises 7444 audio files containing acoustic signal samples recorded using a 44.1 kHz microphone during the milling of mild steel with a tungsten carbide tool on a BFW YF1 vertical milling machine. Various combinations of speed, feed and depth of cut were used, and surface roughness values measured using a Carl Zeiss E-35B profile-meter are provided for each combination. Additionally, an example workflow indicating the possible use of the data to estimate the surface roughness from the acoustic signals is presented. This dataset is the first publicly available resource for surface roughness measurement using sound signals in milling, offering significant potential for reuse in related research and applications.

The generation of mechanical characteristics in workpiece subsurface layers as a result of the cutting process has a predominant influence on the performance properties of machined parts. The effect of the end milling process on the mechanical characteristics of the machined subsurface layers was evaluated using nondestructive methods: instrumented nanoindentation and sclerometry (scratching). In this paper, the influence of one of the common processes of materials processing by cutting—the process of end tool milling—on the generation of mechanical characteristics of workpiece machined subsurface layers is studied. The effect of the end milling process on the character of mechanical property formation was evaluated through the coincidence of the cutting process energy characteristics with the mechanical characteristics of the machined subsurface layers. The total cutting power and cutting work in the tertiary cutting zone area were used as energy characteristics of the end milling process. The modes of the end milling process are considered as the main parameters affecting these energy characteristics. The mechanical characteristics of the workpiece machined subsurface layers were the microhardness of the subsurface layers and the total work of indenter penetration, determined by instrumental nanoindentation, and the maximum depth of indenter penetration, determined by sclerometry. Titanium alloy Ti10V2Fe3Al (Ti-1023) was used as the machining material. Based on the evaluation of the coincidence of the cutting process energy characteristics with the specified mechanical characteristics of the machined subsurface layers, the milling mode effect of the studied titanium alloy, in particular the cutter feed and cutting speed, on the generated mechanical characteristics was established. [ABSTRACT FROM AUTHOR]

Nanofluids are efficient heat transfer media that have been developed over the past 27 years and have been widely used in the electronic microchannel, engine, spacecraft, nuclear, and solar energy fields. With the high demand for efficient lubricants in manufacturing, the application of nanofluids in machining has become a hot topic in academia and industry. However, in the context of the huge amount of literature in the past decade, existing review cannot be used as a technical manual for industrial applications. There are many technical difficulties in establishing a mature production system, which hinder the large-scale application of nanofluids in industrial production. The physicochemical mechanism underlying the application of nanofluids in machining remains unclear. This paper is a complete review of the process, device, and mechanism, especially the unique mechanism of nanofluid minimum quantity lubrication under different processing modes. In this paper, the preparation, fluid, thermal, and tribological properties of nanofluids are reviewed. The performance of nanofluids in machining is clarified. Typically, in friction and wear tests, the coefficient of friction of jatropha oil-based alumina nanofluids is reduced by 85% compared with dry conditions. The cutting fluid based on alumina nanoparticles improves the tool life by 177–230% in hard milling. The addition of carbon nanotube nanoparticles increases the convective heat transfer coefficient of normal saline by 145.06%. Furthermore, the innovative equipment used in the supply of nanofluids is reviewed, and the atomization mechanisms under different boundary conditions are analyzed. The technical problem of parameterized controllable supply system is solved. In addition, the performance of nanofluids in turning, milling, and grinding is discussed. The mapping relationship between the nanofluid parameters and the machining performance is clarified. The flow field distribution and lubricant wetting behavior under different tool-workpiece boundaries are investigated. Finally, the application prospects of nanofluids in machining are discussed. This review includes a report on recent progress in academia and industry as well as a roadmap for future development. [ABSTRACT FROM AUTHOR]

This study investigates the impact of declination angles (at 5, 10, and 15°) on the side milling process of additively manufactured Ti6Al4V. The finite element modelling (FEM) simulations are conducted using the Abaqus software and the Johnson–Cook (J-C) model. The main focus is on characterizing the relationship between the declination angles and the cutting forces. The findings demonstrate the significant effects of the declination angle, with noticeable variations observed in the milling forces. By employing the 3D milling finite element model of Abaqus, accurate analyses and predictions of the machining process dynamics are achieved. The insights gained from this research are valuable for optimizing machining parameters and enhancing efficiency, as well as for improving the surface quality of milled additively manufactured Ti6Al4V components. [ABSTRACT FROM AUTHOR]

This article demonstrates the electro erosion milling process in Al-SiC metal matrix composites. Material Erosion Rate (MER) and Tool Erosion Rate (TER) are measured which depict the productivity aspect of the process. Depth and width of the slots, surface roughness (Ra) is used to indicate the geometrical accuracy. Maximum MER (0.1097 mm3/min) is obtained at 5A. Maximum TER (0.65 µm/min) is obtained at 2.15A. Minimum Ra (2.13 µm) is obtained at 2.15A. Maximum MER (0.1194 mm3/min) is obtained at 100µs. Lowest TER (0.73µm/min) is obtained at 10µs. Lowest Ra (7.66µm) is obtained at Ton of 100µs. Jaya algorithm is used to optimize and create Pareto front from which the results are extracted and reported. Material removal mechanism has been detailed which includes melting / evaporating of matrix material, electrochemical dislodging of SiC grains. Better surfaces have crater diameters ranging from 40–50µm and the bigger craters are in the range of 100–150µm. [ABSTRACT FROM AUTHOR]

Face milling is among the processes that can produce a high-precision surface finish. Tool condition monitoring and signal processing algorithms are under extensive research to improve production quality and productivity in machining processes. In the present research, the time–frequency analysis technique was applied to the signal obtained from a sensor integrated into the primary AC power circuitry during the milling of steel bars to evaluate its applicability in detecting the current variations associated with the cutting force. The signal acquired from the sensor was processed in the time–frequency domain using wavelet analysis, and the results were compared with the traditional time and frequency analyses. The results showed that the signal variations produced by the cutting force were well localized in the frequency spectra with both approaches. However, the wavelet processing method yielded a poorly defined cutting force signal shape due to the limited resolution inherent in the sub-bands containing the frequencies of interest. [ABSTRACT FROM AUTHOR]

Featured Application: The results of the following design investigation can be used in the field of machining, particularly when developing new types of cutting tools and tooling. This paper describes the process of the design and verification of a milling tool and tooling that may contribute to the renouncement of the flood cooling method when mineral oils and oil-in-water emulsions are used as coolants. The proposed solutions are based on the idea of coolant supply in internal channels created inside of a cutting tool. As an alternative to the aforementioned mineral oil-based coolants, liquids with higher cooling efficiency and environmental friendliness (green coolants) were considered. Given coolants' possible lack of lubricating properties and negative (corrosive, etc.) influence on a machine tool's units, tooling delivers these coolants to the cutting tool and bypasses the standard machine tool's supply system. The geometry of the milling tool (a cutting insert with an internal channel) was tested in the framework of a stress simulation. To perform it, cutting force components F z , F y , and F x were determined empirically and then applied to the simulated area of contact between the tool and the workpiece. Based on the obtained principal stress values P 1 , P 2 , and P 3 , the factor of safety was calculated with the Mohr–Coulomb, P 1   m a x , and P 3   m i n failure criteria. The proposed milling tool, equipped with a novel type of labyrinth seal with no friction between its components, was experimentally tested to confirm its ability to maintain leak-tightness at different values of spindle speed (200~2000 rpm) and coolant supply volume (1.0~10.0 L/min). Based on the results of the stress simulation and the leak-tightness experiment, conclusions were drawn about further modernization and utilization prospects of the proposed milling tool and tooling design. [ABSTRACT FROM AUTHOR]

Machining process simulation is a method to increase machining quality and efficiency. The right cutting tool geometry and parameters are chosen during the machining simulation process to create a variety of precision component shapes. A machining simulation for the production of polygonal shafts is presented in this paper. The quality of the parabolic shaft during manufacture will be directly impacted by the machining process, which is simulated using the proper tools and appropriate machining parameters. CAM ESPRIT TNG (x64) software is used in the simulation to simulate the turning and milling process. The machining process can be made more efficient because the simulation process demonstrates that every step of the process operates as intended. [ABSTRACT FROM AUTHOR]

Fused Deposition Modeling (FDM) finds extensive application across various fields due to its cost-effectiveness and user-friendly nature. However, it does come with certain limitations, including challenges in achieving high surface quality, precise dimensional tolerance, and the characteristic anisotropic mechanical properties it exhibits. The aim of this paper is to investigate the machinability of 3D-printed PETG and analyze the roughness and burr formation that occurs as a result. A Design of Experiments (DoE) was developed with three factors: rotational speed, feed rate, and depth of cut. Each factor had different levels: rotational speed at 3000, 5500, and 8000 rpm; feed rate at 400, 600, and 800 mm/min; and depth of cut at 0.2, 0.4, 0.6, and 0.8 mm. The machinability was evaluated based on two response parameters: roughness (Sa), determined on the milled surface, and burr height, measured using a profilometer on both sides of the milled surface. The findings indicate that milling parameters strongly affect roughness and burr formation. However, the optimal conditions for minimizing roughness and burr formation are not coincident. The results were also compared to the machinability of PLA machined under similar conditions. [ABSTRACT FROM AUTHOR]

Background: While near surface residual stress (NSRS) from milling is a driver for distortion in aluminum parts there are few studies that directly compare available techniques for NSRS measurement. Objective: We report application and assessment of four different techniques for evaluating residual stress versus depth in milled aluminum parts. Methods: The four techniques are: hole-drilling, slotting, cos(α) x-ray diffraction (XRD), and sin2(ψ) XRD, all including incremental material removal to produce a stress versus depth profile. The milled aluminum parts are cut from stress-relieved plate, AA7050-T7451, with a range of table and tool speeds used to mill a large flat surface in several samples. NSRS measurements are made at specified locations on each sample. Results: Resulting data show that NSRS from three techniques are in general agreement: hole-drilling, slotting, and sin2(ψ) XRD. At shallow depths (< 0.03 mm), sin2(ψ) XRD data have the best repeatability (< 15 MPa), but at larger depths (> 0.04 mm) hole-drilling and slotting have the best repeatability (< 10 MPa). NSRS data from cos(α) XRD differ from data provided by other techniques and the data are less repeatable. NSRS data for different milling parameters show that the depth of NSRS increases with feed per tooth and is unaffected by cutting speed. Conclusion: Hole-drilling, slotting, and sin2(ψ) XRD provided comparable results when assessing milling-induced near surface residual stress in aluminum. Combining a simple distortion test, comprising removal of a 1 mm thick wafer at the milled surface, with a companion stress analysis showed that NSRS data from hole-drilling are most consistent with milling-induced distortion.

The aim of this study was to increase the economic efficiency of industrial robots (IR) when subtractive machining timber beams. The most compact possible stack configuration, consisting of three different workpiece geometries, was calculated and machined. When compared to machining individual workpieces, a reduction of the process time is strived for. The workspace of the IR should be fully utilised by an optimised spatial stack configuration (number, location and spacing of workpieces). The stacks were calculated using a parameterised evolutionary solver model in Rhinoceros, Grasshopper, Galapagos and Opossum software. Machining trials were performed to obtain process time data for the IR and as a reference for a benchmark joinery machine (JM). By applying the newly introduced optimisation model, the process time per workpiece, when machining stacks instead of individual specimens, was reduced by 16%. This result was primarily achieved by shifting the share of non-machining time to machining time. When compared to individual machining with a JM, the process time of the IR is still higher. This fact can be outweighed by advantages of IRs such as cost, availability and flexibility, showing that the overall economic efficiency of IRs does in fact hold potential for prefabrication in the timber construction sector. [ABSTRACT FROM AUTHOR]

Manufacturing industries are rapidly growing with varying customer needs, and efficient quality control tools are widely used to optimize product/process performances. This paper highlights the modified quality control module to optimize the milling performances of polymer nanocomposites. The carbon fabric and reduced graphene oxide reinforced (CF/rGO) polymer composites are machined at varying process constraints. The experimentation was designed according to Taguchi's orthogonal array. The Milling performances were optimized using a multi-criterion decision-making (MCDM) tool based on a combination distance-based assessment (CODAS) optimization method. The desired value of surface roughness (Ra) and cutting force (Fc) is examined during the machining of the developed polymer. CODAS optimization module efficiently combined the various contradictory parametric outcomes into a single objective assessment value (Hi), which could not be possible by utilizing the usual conventional Taguchi method. Specifically, the optimal machining conditions were found to be rGO wt.%—1, speed—2000 rpm, feed—80 mm/min, DoC—1.5 mm. Overall, the findings demonstrate the practicality of the recommended MCDM tool, which outperformed the usual conventional Taguchi method. The optimal assessment score of CODAS was noted as 1.904, which confirms the better viability of the current MCDM approach. This study contributes to the advancement of efficient quality control tools that can be widely used to optimize product/process performances in manufacturing industries. [ABSTRACT FROM AUTHOR]

Machining process simulation is a method to increase machining quality and efficiency. The right cutting tool geometry and parameters are chosen during the machining simulation process to create a variety of precision component shapes. A machining simulation for the production of polygonal shafts is presented in this paper. The quality of the parabolic shaft during manufacture will be directly impacted by the machining process, which is simulated using the proper tools and appropriate machining parameters. CAM ESPRIT TNG (x64) software is used in the simulation to simulate the turning and milling process. The machining process can be made more efficient because the simulation process demonstrates that every step of the process operates as intended.

This paper investigates the possibility of using empirical tool life models to predict tool life in a side milling application in a medium carbon steel, C 45E. To do this, an extensive dataset containing 46 data points with different machining parameters are produced. Four different empirical models: Taylor’s equation, Colding’s equation and Extended Taylor both using depth of cut and feed as well as an Extended Taylor using equivalent chip thickness has been considered. It is found that Colding’s equation is best suited to predict the tool life for this application. Furthermore, this paper suggests a novel method to fit the experimental data to the empirical models. Based on the results from previously published papers it is shown that the proposed method performs equally or better to determine the model constants.

Monitoring the machining process is crucial for providing cost-effective, high-quality production and preventing unwanted accidents. This study aims to predict critical machining conditions related to surface roughness and tool breakage in titanium alloy slot milling. The Siemens SINUMERIK EDGE (SE) Box system collects signals from the spindle and axes of a CNC machine tool. In this study, features were extracted from signals in time, frequency, and time–frequency domains. The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. The SVM hyperparameters were optimized simultaneously with feature selection, and the model was tested with test data. The proposed model accurately predicted critical machining conditions for unbalanced datasets. The classification model indicates an average recall, precision, and accuracy of 80%, 86%, and 95%, respectively, when predicting workpiece quality and tool breakage. [ABSTRACT FROM AUTHOR]

Today, various military, aerospace, automotive, etc. industries need materials with a high strength -to -weight ratio. The use of metal -based composite materials, especially aluminum - based composites, has increased greatly. Machining is needed to achieve high dimensional accuracy in products made with aluminum -based composites. Due to the presence of reinforcing material such as silicon carbide, machining of this type of material is difficult. Therefore, it is important to study the parameters affecting the machining of aluminum -based composites. In this study, the effect of spindle speed, feed rate, depth of cut and percentage of reinforcing particles were discussed using experimental and statistical test methods. The responses of surface roughness and material removal rate were investigated. The behavior of the input parameters on the responses of the process has been carefully investigated quantitatively and qualitatively. Answers have also been optimized. According to the obtained results, the spindle speed has the greatest effect on the surface roughness. Also, feed rate 33%, spindle speed 28%, depth of cut 26% and the percentage of reinforcing particles 13% have an effect on the chipping rate. [ABSTRACT FROM AUTHOR]

AA 7075 T6 material offers important strength values and is easy to machining. In this respect, it is preferred on a wide scale in the industry. This study aimed to investigate the surface quality that occurs in the end milling of AA 7075 T6 material. For this, three different cutting speeds (40, 80, 120 m/min), three different feed rates (0.04, 0.08, 0.12 mm/rev), two different cutting depths (1 and 2 mm) were selected. The selected cutting parameters are combined with 2 and 4-flute end mills. As a result of the experiments, the average surface roughness (Ra) value was measured. The relations of Ra values with the cut parameters were determined. It was determined that Ra increased with increasing feed rate and decreased with increasing cutting speed. No significant effect of depth of cut was detected. Increasing the number of mouths increased Ra. The milling simulation was performed with the 3D cutting module in the Deform 3D software. 2 and 4 flute end mills are modeled, and the workpiece is defined to the software and the cutting parameters. Temperature, damage, stress, and cutting force outputs were estimated through simulations run at different cutting parameters. The predicted outputs and the experimental Ra outputs were interpreted. Experimental outputs were supported by successfully applying milling simulation in Deform 3D software. [ABSTRACT FROM AUTHOR]

Real-time tool condition monitoring (TCM) is becoming more and more important to meet the increased requirement of reducing downtime and ensuring the machining quality of manufacturing systems. However, it is difficult to satisfy both robustness and effectiveness of pattern recognition for a TCM system without using an unsupervised strategy. In this paper, a clustering-based TCM system is proposed that can be used for different machining conditions such as variable cutting parameters, variable cutters, and even variable cutting methods. The solution is based on a significant statistical correlation between tool wear and the distribution of cutting force features, which is revealed through the clustering results obtained from a novel clustering method based on adjacent grids searching (CAGS). This statistical correlation is converted into tool wear status by using an empirical factor that is robust for variable cutting processes. The proposed TCM system is completely unsupervised as a training-free procedure is used in the monitoring process. To verify the effectiveness of the system, a series of experiments are conducted, such as whole life-cycle wear experiment under same milling condition, tool wear experiment under variable milling conditions and tool wear experiment under same turning condition. The prediction accuracy of our system for tool wear experiment under variable milling conditions is 100%, 75% and 75%, respectively. In contrast, BP neural network, Bayesian network and SVM are used for tool wear prediction under the same conditions. Experimental results show the superiority and effectiveness of our TCM system based on cluster density of CAGS over several state-of-the-art supervised methods. [ABSTRACT FROM AUTHOR]

Traditional electrochemical discharge machining (ECDM) is a hybrid of electrical discharge machining (EDM) and electrochemical machining (ECM). Electrical discharge erosion and electrochemical dissolution occur simultaneously in low-conductivity salt solution. It is very difficult to reduce the recast layers because of the low ratio of electrochemical dissolution. A novel combined machining approach combining electrical discharge ablation machining and electrochemical machining (EDAM-ECM) is proposed and the "electrolyte-oxygen" aerosol is used as the medium in this study. First, the electrical discharge ablation machining (EDAM) process is performed with oxygen in the aerosol medium to attain a higher material removal rate (MRR). Second, the electrochemical reaction current is increased by using a droplet of the electrolyte with higher conductivity. Third, the ratio of electrochemical dissolution is increased in an aerosol medium. The mechanism of conventional ECDM milling and EDAM-ECM milling was analyzed and comparable experiments were performed. Results show that EDAM-ECM milling has advantages of higher MRR, lower relative electrode wear ratio (REWR), and higher surface quality. Under the prescribed test conditions, the MRR increased by more than five times and the REWR is reduced by 94.1% compared with ECDM milling, and the recast layer is completely removed. [ABSTRACT FROM AUTHOR]

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The innovative Green Ceramic Hybrid Machining (GCHM) process sequentially combines milling with a cutting tool (GCM, Green Ceramic Machining) and laser beam machining (GCLBM) of a ceramic material (black Y-TZP in this study) at the green stage mainly to increase productivity, avoid taper angle limitations of laser beam machining, and obtain micro-features. The study focuses on the reliability and the repeatability of the properties of sintered parts obtained by three manufacturing processes (GCM, GCLBM, GCHM) to assess the performance of hybridisation. It turns out that GCHM is a compromise of both milling and laser beam processes; it increases the repeatability of the surface quality and it slightly reduces (less than 7%) the flexural strength by comparison to milling for a similar reliability. The study also highlights that the surface quality of GCLBM processed parts relies on of the surface generated by the previous operation. Milling that surface at the previous step is therefore recommended, corresponding to the sequence adopted by GCHM. [ABSTRACT FROM AUTHOR]

Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time–frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets—Big Data—under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing. [ABSTRACT FROM AUTHOR]

The poor machinability of SiC f /SiC composites greatly limits its application and promotion. The laser-induced ablation products of SiC f /SiC composites are powdery, loose and porous. Milling of laser ablated samples demonstrated that the force and heat were almost negligible when milling ablation products. Accordingly, a laser ablation pretreatment milling (LAPM) process of SiC f /SiC composites was proposed. Under the LAPM process, after the laser ablation treatment with controllable depth, the cutting allowance could be achieved in only one pass, which greatly improved the machining efficiency compared with the conventional milling process. The material removal rate was greatly improved on the premise of ensuring the machining quality. Taking the milling of tensile specimens as an example, compared with conventional milling, the total processing time of the specimen was reduced by 31.29 % by LAPM process. Therefore, LAPM provides a potential feasible process scheme for greatly improving the machinability and machining efficiency of SiC f /SiC composites. [ABSTRACT FROM AUTHOR]

Due to Inconel 718's high mechanical properties, even at higher temperatures, tendency to work-harden, and low thermal conductivity, this alloy is considered hard to machine. The machining of this alloy causes high amounts of tool wear, leading to its premature failure. There seems to be a gap in the literature, particularly regarding milling and finishing operations applied to Inconel 718 parts. In the present study, the wear behavior of multilayered PVD HiPIMS (High-power impulse magnetron sputtering)-coated TiN/TiAlN end-mills used for finishing operations on Inconel 718 is evaluated, aiming to establish/expand the understanding of the wear behavior of coated tools when machining these alloys. Different machining parameters, such as cutting speed, cutting length, and feed per tooth, are tested, evaluating the influence of these parameters' variations on tool wear. The sustained wear was evaluated using SEM (Scanning electron microscope) analysis, characterizing the tools' wear and identifying the predominant wear mechanisms. The machined surface was also evaluated after each machining test, establishing a relationship between the tools' wear and production quality. It was noticed that the feed rate parameter exerted the most influence on the tools' production quality, while the cutting speed mostly impacted the tools' wear. The main wear mechanisms identified were abrasion, material adhesion, cratering, and adhesive wear. The findings of this study might prove useful for future research conducted on this topic, either optimization studies or studies on the simulation of the milling of Inconel alloys, such as the one presented here. [ABSTRACT FROM AUTHOR]

Composite materials such as Fiber Metal Laminates (FMLs) have attracted the interest of the aerospace and automotive industries due to their high strength to weight ratio, but to use them as structures it is necessary to master the manufacturing and wiring techniques of these materials. Therefore, this paper aims to address and summarize the drilling and milling processes in FMLs based on a literature review of papers published from 2000 to 2023. Parameters used in multi-material manufacturing and machining such as drilling and milling, tool geometry, tool coating, lubricants and coolants published by researchers were analyzed, compared and discussed. Machining process parameters related to sustainability were also analyzed. A SWOT analysis was carried out and discussed to identify opportunities for improvement in the machining process. There are opportunities to develop the surface treatment of aluminum alloys, such as testing other combinations than those already used, testing non-traditional surface treatments and manufacturing modes, and developing sustainable techniques during the FML manufacturing process. In the area of tooling, the opportunities are mainly related to coatings for tools and changing machining parameters to achieve an optimum finished part. Finally, to improve the sustainability of the process, it is necessary to test coated drills under cryogenic conditions to reduce the use of lubricants during the machining process. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) opens new possibilities of obtaining ceramic green parts with a tailored complex design at low cost. Meeting the requirements of highly demanding industries (aeronautical and biomedical, for example) is still challenging, even for machining. Hybrid machines can solve this problem by combining the advantages of both additive and subtractive processes. However, little information is currently available to determine the milling parameters of additively fabricated ceramic green parts. This article proposes a systematic approach to experimentally determine the cutting parameters of green AM zirconia parts. Three tools, one dedicated to thermoplastics, one to composites, and a universal tool, were tested. The tool--material couple standard (NF E 66-520-5) was followed. The lower cost and repeatable generation of smooth surfaces (Ra < 1.6 µm) without material pull-out were the main goals of the study. The universal tool showed few repeatable working points without material pull-out, while the two other tools gave satisfying results. The thermoplastic tool ensured repeatable results of Ra < 0.8 µm at a four times lower cost than the composite tool. Moreover, it exhibited a larger chip thickness range (from 0.003 mm to 0.036 mm). Nevertheless, it generated an uncut zone that must be considered when planning the milling operations. [ABSTRACT FROM AUTHOR]

This paper describes the process of the design and verification of a milling tool and tooling that may contribute to the renouncement of the flood cooling method when mineral oils and oil-in-water emulsions are used as coolants. The proposed solutions are based on the idea of coolant supply in internal channels created inside of a cutting tool. As an alternative to the aforementioned mineral oil-based coolants, liquids with higher cooling efficiency and environmental friendliness (green coolants) were considered. Given coolants’ possible lack of lubricating properties and negative (corrosive, etc.) influence on a machine tool’s units, tooling delivers these coolants to the cutting tool and bypasses the standard machine tool’s supply system. The geometry of the milling tool (a cutting insert with an internal channel) was tested in the framework of a stress simulation. To perform it, cutting force components Fz, Fy, and Fx were determined empirically and then applied to the simulated area of contact between the tool and the workpiece. Based on the obtained principal stress values P1, P2, and P3, the factor of safety was calculated with the Mohr–Coulomb, P1 max, and P3 min failure criteria. The proposed milling tool, equipped with a novel type of labyrinth seal with no friction between its components, was experimentally tested to confirm its ability to maintain leak-tightness at different values of spindle speed (200~2000 rpm) and coolant supply volume (1.0~10.0 L/min). Based on the results of the stress simulation and the leak-tightness experiment, conclusions were drawn about further modernization and utilization prospects of the proposed milling tool and tooling design.

In order to reduce the machining deformation of thin-walled parts during milling, a non-uniform allowance planning method for thin-walled parts based on the workpiece deformation constraint with the idea of adding materials in reverse material removal sequence is proposed in this paper. This method does not require accurate deformation prediction and extensive experiments compared to traditional error compensation methods. It strives to maximize the allowance to enhance the stiffness of the in-process workpiece. First, a cutting force threshold calculation method is proposed according to the finite element method. The cutting force threshold at different positions is calculated by obtaining the local stiffness characteristics at the cutter-contact point under the constraint of allowable deformation. And then, the maximum machining allowance at the cutter-contact point is calculated depending on the cutting force model. Considering that the stiffness of the workpiece is position-dependent and affected by material removal, the stiffness of the workpiece is updated by adding elements in the reverse cutting direction, and the finishing stock is obtained by surface fitting. Experimental results show that compared with the traditional uniform allowance method, the error of the proposed method is reduced by about 83%, which can effectively reduce the deformation and improve the machining accuracy. [ABSTRACT FROM AUTHOR]