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Recent developments under Industry 4.0 allows to collect and analyze measurements during milling process. For such projects to be done, software needs to be developed. Developing software through testing is expensive and tedious. In this study, milling dynamics is simulated through Matlab Simulink. In order to explain dynamics of the process, literature research has been conducted to select suitable models and merged with chip regeneration model. For force model, linear force model and Martellotti static chip thickness model has been selected. For transfer functions, hammer tests conducted on the milling machine that experiments is done on and modal analysis is applied on obtained Frequency Response Functions (FRFs). For workpiece material, AL7075 has been selected and force coefficients has been obtained from another study that was conducted by authors. Cutting tests has been performed and acceleration of workpiece at X and Y directions are measured in order to be compared to simulation output which confirms the model. [ABSTRACT FROM AUTHOR]

The purpose of this work is to investigate the physical stability of a ternary amorphous system (Ibuprofen, Caffeine, Polyvinylpyrrolidone (PVP K30)) generated by co-milling technique at room temperature, as well as the intermolecular interactions that could contribute to physical stabilization of amorphous ibuprofen (a poorly water-soluble drug). The milled mixtures were characterized by x-ray diffraction (XRD), infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and scanning electronic microscopy (SEM). As shown by XRD results, amorphous Ibuprofen maintains its physical stability even after exposure to high humidity levels (RH = 75%, T = 40°C) for 6 months. FTIR results highlighted the establishment of hydrogen bonds in the binary and ternary systems involving the carboxylic group of Ibuprofen. At higher amounts (more than 75%), the polyvinylpyrrolidone has totally amorphized drug/caffeine mixtures and inhibited polymorphic transition of Caffeine (Form II ≥ Form I) which occurred at higher temperatures. Thus, this polymer has shown an ability to stabilize amorphous solid dispersion (Ibuprofen: Caffeine) and preserve the chemical structure of each molecule. [ABSTRACT FROM AUTHOR]

In the milling process of composite materials, the initial chatter frequency is not obvious and is easily swamped by the rest of the signals, making frequency monitoring difficult, so the study proposes a chatter frequency monitoring method based on frequency cancellation algorithms and wavelet packet decomposition. The results of the experiments shown that the frequency cancellation algorithm can successfully remove invalid signals, such as spindle rotation frequency and cutter tooth frequency, and only keep the necessary signals, at which point the chattering frequency may be observed at a frequency of roughly 1333 Hz. The influence of the frequency bands s5, s9, s10, s12, and s13 after de-frequency removal should be avoided because they all have a low energy share of roughly 23 %, 0.9 %, 5 %, 10 %, and 16 %, respectively, and are less sensitive to chatter. For milling edge depths of 0.5 mm, 2 mm, and 4 mm, the average chatter thresholds were around 3.27, 2.9, and 2.89, respectively. It was challenging to pinpoint the chatter of the system because the empirical modal decomposition observed an average chatter energy entropy of just 1.55 and found that its fluctuations at the milling edge depth junction were insignificant. On the other hand, the chattering could be plainly seen since the energy entropy experienced a substantial and dramatic fluctuation at the intersection of the milling edge depth when it was about 2.9, 2.6, and 2.5, respectively. The experimental findings demonstrated that the frequency cancellation technique and wavelet packet decomposition-based chattering frequency monitoring approach can precisely track the chattering state of the system. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) signals are thought to contain crucial information for identifying defects and monitoring processes. It is crucial to have a comprehensive understanding of how AE signal parameters behave under different experimental conditions. However, based on current research, there appears to be a lack of knowledge on the impact of machining parameters, especially in milling operations, where complex chip formation patterns, interaction effects, and directional pressures and forces are present. To bridge this informational void, analyzing how various cutting conditions impact the AE signal characteristics derived from milling operations is crucial. This research predominantly focuses on the impact of cutting conditions, material attributes, insert coatings, and nose radius on AE signal attributes in the time domain. The proposed innovative method suggests segmenting acquired AE signals correlated with the cutting tool's trajectory through the material into three distinct phases: entry, active cutting, and exit, each marked by a particular signal timeframe for effective signal processing and characteristic derivation. Furthermore, advanced signal processing techniques and statistical analysis are utilized to determine which AE parameters are sensitive to changes in cutting parameters. This research identifies cutting speed and feed rate as the primary variables affecting AE signal characteristics. The study's outcomes can enhance sophisticated classifications and AI techniques for monitoring machining operations. [ABSTRACT FROM AUTHOR]

Process damping is a common phenomenon improving the stability in machining. The main source of process damping is the extrusion between the tool flank and the wavy machined workpiece surface. For most process damping models, the indentation force coefficient needs identification to predict the indentation force, which requires cumbersome experiments or simulation. In this paper, a new process damping model without identification is presented based on the Hertz theory. The indentation force is the function of the depth of contact. The contact boundary is estimated by the cutting-edge geometry and wavy machined surface. The process damping coefficient is related to the cutting parameters, cutting geometry, vibration frequency and amplitude, and the mechanical properties of the workpiece material. The dynamical equation with process damping is solved using the numerical integration method (IM). It is experimentally proved that the stability with the proposed process damping model has better predictive accuracy compared with the classical models. [ABSTRACT FROM AUTHOR]

Background and Objectives: Flour color changes caused by contamination like fungal‐damaged kernels can be determined by several methods, but many existing methods are time‐consuming and require specialized training. In this study, a commercial flatbed scanner was used to quickly detect and quantify the abundance of black specks derived from smutty grains in wheat flour samples. Findings: Our method easily classified flour samples into several categories, as clean flour, marginally clean, or contaminated, by using varied levels of %area‐smut. From our set of calibration flour samples, clean flour samples were located below 0.025% area‐smut. Marginal flours were defined as flours having %area‐smut from 0.025% to 0.050%. Notably, contaminated flour had %area‐smut greater than 0.05%. Moreover, the flour color brightness parameter (L) was determined using the scanner and was found to be inversely related to the %area‐smut. In addition, the number of smutty seeds manually detected in 250 g whole‐grain samples was correlated to the %area‐smut found in the flour. Conclusions: Therefore, this method represents a rapid and reliable way to distinguish clean flour from flour milled from wheat containing various levels of smut contamination. Significance and Novelty: This method was developed and validated using wheat samples collected from the field and contained a range of smut contamination. Although specks could easily be detected and counted, we found that speck counts varied with scanner resolution setting. Therefore, an alternate parameter referred to as "%area‐smut" was calculated and resulted in more consistent values per sample regardless of scanner resolution. Additionally, the flour color parameter, L*, was determined for each scanned image using imaging processing software. This color parameter, L*, was well correlated with those measured with a reference hand‐held colorimeter. [ABSTRACT FROM AUTHOR]

The composites of Mg 20 Pr 1 Sm 3 Y 1 Ni 10 as-quenched alloy and 3 wt.% M (M = CoS, CoS 2 , MoS 2) catalyst were prepared by high-speed vibration ball mill. The effects of metal sulfides on the hydrogenation and dehydrogenation dynamics of alloys were compared. The results show that the as-milled composites contain a large number of amorphous embedded by a small amount of nanocrystals, and there are many point defects. After ball milling, the crystal grain size in the composites containing CoS is relatively larger, followed by CoS 2 and MoS 2 again. After hydrogenation, the amorphous phase is crystallized to form Mg 2 NiH 4 , YH 3 , Pr 8 H 18.96 , Sm 3 H 7 , Mg, Co or Mo phases, however, Mg 2 Ni, YH 2 , PrH 2 and Ni 3 Y phases appeared after dehydrogenation. The maximum hydrogenation capacity of the composites containing CoS, CoS 2 and MoS 2 are 3.939, 4.265 and 4.507 wt.%, respectively. The hydrogenation saturation ratio of composite containing MoS 2 is higher than that of the composites containing CoS and CoS 2. The dehydrogenation activation energy of the composites containing CoS, CoS 2 and MoS 2 is 107.76, 68.43 and 63.28 kJ.mol−1.H 2. On the improvement of hydrogen storage performance of Mg 20 Pr 1 Sm 3 Y 1 Ni 10 alloy, the catalytic effect of MoS 2 sulfide is better than that of CoS 2 sulfide, and which is better than CoS sulfide. [ABSTRACT FROM AUTHOR]

This study combined simulation and experimental tests to analyse the cutting performance of three solid carbide end mills with distinct geometries during the milling of the 7075 aluminium alloy. For the tests, three uncoated end mills were employed, which differed in rake angle, clearance angle, and helical pitch. Simulation tests revealed temperature distributions and the resultant cutting forces. The machining with a milling cutter with a higher blade angle was shown to cause an increase in the temperature in the cutting zone. However, during machining with a sharper blade of cutting tool, a decrease of cutting forces was not observed. The simulated temperature distribution on the cutting edge of the cutting tool may justify significant differences in the dynamics of changes in the cutting force components during the period of operational wear. [ABSTRACT FROM AUTHOR]

The described data set contains features from the machine control of a five-axis milling machine. The features were recorded during thirteen series productions. Each series production includes a changeover process in which the machine was set up for the production of a different product. In addition to the timestamps and the twenty recorded features derived from Numerical Control (NC) variables, the data set also contains labels for the different production phases. For this purpose, up to 23 phases were assigned, which are based on a generalized milling process. The data set consists of thirteen.csv files, each representing a series production. The data set was recorded in a production company in the contract manufacturing sector for components with real series orders in ongoing industrial production. Dataset: 10.5281/zenodo.10853254 Dataset License: Creative Commons Attribution 4.0 International (CC BY 4.0) [ABSTRACT FROM AUTHOR]

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work studied the thermal stability, electrical, and thermoelectrical properties of copper(I) selenide, Cu2Se synthesized by high-energy milling in a planetary ball mill. The phase composition was investigated by X-ray powder diffraction analysis and scanning electron microscopy. The conversion of the precursors during mechanochemical synthesis and the stability of the product was monitored by thermal analysis. The dependence of electrical properties on the product porosity was observed. For the densification of Cu2Se, the method of spark plasma sintering was applied to prepare suitable samples for thermoelectric characterization. High-temperature thermoelectric properties of synthetic Cu2Se were compared to its natural analogue-mineral berzelianite in terms of its potential application in energy conversion. Based on the results a relatively high figure-of-merit, ZT parameter (~ 1.15, T = 770 K) was obtained for undoped Cu2Se, prepared by rapid mechanochemical reaction (5 min). Cyclic voltammetry measurements of Na/NaClO4/Cu2Se cell implied that mechanochemically synthesized Cu2Se could be used as a promising intercalation electrode for sodium-ion batteries. [ABSTRACT FROM AUTHOR]

Although chip morphology changes according to the machining method and related cutting parameters, chip formation affects the quality of the machined surface. In this context, it is very important to understand the relationship between chip morphology and surface quality, especially in materials that are difficult to machine. In the presented study, the changes in chip morphology, surface morphology, and surface quality criteria (Ra and Rz) that occurred during the milling of precipitation-hardened steel in different cutting environments were analyzed. Milling experiments were carried out in dry, MQL (minimum quantity lubrication), nano-MQL (graphene), nano-MQL (hBN), Cryo, and Cryo-MQL environments using TiAlN-coated inserts and three different cutting speeds and feed rates. While the highest values in terms of Ra and Rz were measured in dry machining, the minimum values were obtained in a nano-MQL (hBN) cutting environment. Due to the lubrication and low friction provided by the MQL cutting environment, chips were formed in thinner segmented forms. This formation reduced the chip curve radius and thus provided a more stable surface morphology. On the other hand, Cryo-ambient gas could not effectively leak into the cutting zone due to the intermittent cutting process, but it increased the brittleness of the chips with the cooling effect and provided a similar surface morphology. The values of minimum Ra and Rz were obtained as 0.304 mm and 1.825 mm, respectively, at a 60 m/min cutting speed and 0.04 mm/rev feed. Consequently, the use of nano-MQL cutting medium is seriously recommended in terms of surface quality in milling operations of difficult-to-machine materials. [ABSTRACT FROM AUTHOR]

New generation hybrid metal matrix composites (HMMC) play an imperative role in innumerable applications and are unceasingly displacing commonly available materials because of their excellent properties like low weight, rust resistance and elevated strength. Growing industrial interest emerges in profound examinations and researchers in the area of machining of HMMC to reduce the price of manufacturing. Owing to this evolution, the mandate to attain wide-ranging efficiency as far as product output and tooling has been increased. Usage of mineral-based cutting oil spoils the environment and labours health during metal cutting. In this work, to study the machinability problems allied to the produced HMMC (TiO2 + biochar + Al-7075), end milling experiments were conducted by utilising diverse speed-feed combinations under minimum quantity lubrication (MQL) strategy and compared with dry and flood environments. Effect on surface roughness, flank wear, microstructure and chip morphology during milling of aluminium 7075 HMMC were investigated. Each exploratory trials were completely reliant on the L27 orthogonal array (OA). For diverse Vc, MQL declined the Ra by about 31.71–39.16% and 16–37.24% over dry and flood machining environments. Vegetable oil in MQL has the tendency to reduce the serration and decreases the grain size with the help of its lubrication/cooling (L/C) effect. Here, response surface methodology (RSM) was implemented to derive the ideal machining parameters. The ideal cutting condition in machining of produced HMMC by desirability analysis is Vc = 50 m/min, f = 0.08 mm/min and E = MQL. [ABSTRACT FROM AUTHOR]

The role of the initial residual stresses (IRS) induced by the milling on the efficacy of laser shock peening (LSP) was investigated numerically on IN718 specimens. Three milling conditions exhibiting high (3.5 μm), medium (1.1 μm), and low (0.6 μm) surface roughness were considered for LSP. Experimentally measured (from XRD) milling-induced sub-surface (up to 60 μm depth) residual stresses were introduced into the simulations of LSP as predefined fields. The role of spot diameter with the IRS on the LSP-induced residual stress was studied systematically. For most cases, the tensile IRS from milling caused a significant decrease in the magnitude of maximum compressive residual stresses induced by LSP. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between residual stresses, cutting parameters, and machining performance in the milling process of compacted graphite iron (CGI). X-ray diffraction (XRD) analysis is employed to measure residual stresses on the cast and milled surfaces, while cutting force modeling is utilized to calculate the tangential force, power, and active work. The results demonstrate that tensile residual stresses are predominant on the milled surfaces, attributed to the both mechanical and thermal loads generated during milling. By analyzing various cutting conditions, it is observed that lower feeds contribute to reduced plastic deformation, resulting in lower residual stress levels. Additionally, higher cutting speeds lead to higher temperatures, but due to the shorter machining time, heat accumulation is limited, resulting in higher residual stresses, especially at low feeds. At high feeds, residual stresses decreased as the cutting speed increased. The interplay between cutting parameters and residual stresses highlights the need for optimizing cutting conditions to enhance fatigue strength in CGI components. These findings provide valuable insights for process optimization and quality control in the milling of CGI materials. [ABSTRACT FROM AUTHOR]

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]

Chatter causes great damage to the machining process, and the selection of appropriate process parameters through chatter stability analysis is of great significance for achieving chatter-free machining. This article proposes a milling stability analysis method based on the barycentric rational interpolation differential quadrature method (DQM). The dynamics of the milling process considering the regeneration effect is first modelled as a time-delay differential equation (DDE). When adjacent pitch angles of the milling cutter are symmetric, the milling dynamic equation contains a single time delay. Otherwise, when adjacent pitch angles are asymmetric, the dynamic equation contains multiple time delays. The barycentric rational interpolation DQM is then used to approximate the differential and delay terms of the milling dynamics equation, and to construct a state transition matrix between adjacent milling periods. Finally, the chatter stability lobe diagram (SLD) is obtained based on the Floquet theory. According to the SLD, the appropriate spindle speed can be selected to obtain the maximum stable axial depth of cutting, thereby effectively improving the material removal rate. The accuracy and efficiency of the proposed method have been validated by two widely used milling models, and the results show that the proposed method has good accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

This paper analytically studies the effect of radial engagement on chatter stability when the flexibility is perpendicular to the feed motion, with thin-walled part milling being the most relevant industrial case. By studying the mean directional factor and its harmonics, the superior stability of the up-milling strategy over down-milling for both Hopf and flip chatter is demonstrated. The optimal engagement for a theoretical infinite stable depth of cut Hopf is obtained, as well as the expressions for the critical depth of cut. For flip chatter, three different cutting zones with different lobe shapes can occur depending on the radial engagement. It is also shown that while flip chatter cannot be completely eliminated by tuning the radial engagement alone, an engagement can be found in up-milling that maximises stability. Finally, the findings are validated through experimental tests. [Display omitted] • The influence of radial engagement on chatter is studied in a dimensionless way. • Up-milling is always better than down-milling for both Hopf and flip chatter. • An engagement that totally cancels Hopf chatter can be found. • Flip chatter cannot be cancelled but there is an optimal that minimises it. • Engagement optimals for static deflection and chatter are very similar in value. [ABSTRACT FROM AUTHOR]

The optimization of machining processes is of paramount significance because of its pivotal role in modern manufacturing. Efficient machining techniques not only enhance product quality but also reduce costs and environmental impacts. This study focuses on the experimental characterization of energy consumption in a 5-axis milling machine and the simulation of possible solutions to reduce it. The first step is to understand the key drivers of energy consumption which is crucial for enhancing energy management and optimization. This was achieved by developing a mathematical model that uses the most common machining parameters as input using a Response Surface Methodology experimental test plan and an analysis of the contributions of the auxiliary systems to the overall energy consumption. As a second step, the effectiveness of different solutions was simulated considering different application scenario, like the type of operations. Such solutions include the introduction of duty cycle strategies for some auxiliary systems and the optimization of process parameters. [ABSTRACT FROM AUTHOR]

This article investigates the trend of assessing energy efficiency, sustainability and greenhouse gas emissions in the operation of 5- axis milling machine tools. This research aims to predict the cooling load by thermal models control within the main spindle system to ensure that cooling devices are dimensioned adequately and to keep it running under optimal conditions leading to improve the overall efficiency. In order to achieve this goal, a digital twin approach is currently being developed utilizing commercial software which consists of four primary models. A simulation model for material removal is used to predict the mechanical load required for the milling process to finish the CAD model. The second model is the spindle control model to determine the electric currents needed to operate the induction motor at the specified mechanical power. This model provides the electric current data to the lumped-parameter thermal networks (LPTN) model, which is proposed to accurately represent the heat dissipation from the motor and spindle systems towards the cooling channel in the main spindle system. Subsequently, the task at hand involves making an estimate of the necessary outlet temperature derived from the refrigeration unit model, which is essential for effectively covering the thermal energy produced by the spindle system. [ABSTRACT FROM AUTHOR]

High-pressure cutting fluid (CF) supply in milling allows higher productivities and results in extended tool life and higher process reliability. On the other hand, the use of CF results in high energy consumption of the CF supply units. By using the additive manufacturing (AM) technique Laser Powder Bed Fusion (PBF-LB), steel-based basic bodies for indexable cutting tools can be manufactured including complex internal structures with new geometrical possibilities. Thus, the internal CF supply can be redesigned, lowering fluid losses within the supply channels and focusing the fluid for a more efficient and effective cooling and lubrication of the contact zone. This study focuses on the ecological evaluation of PBF-LB manufactured indexable tangential milling tools with adapted CF supply for roughing of Ti-6Al-4V according to DIN EN ISO 14040/44. The ecological competitiveness of the newly developed tools against a conventionally manufactured reference tool was evaluated. Two system boundaries were analyzed, considering the cradle-to-gate as well as the cradle-to-grave life cycle. Even though the calculated environmental impact for the manufacturing of the AM tool exceeded the conventional tool, the improved functionality, increased tool life and reduced energy consumption during service life of the tool led to a reduction in the overall ecological costs. [ABSTRACT FROM AUTHOR]

A novel empirical equation is presented to evaluate the Specific Energy Consumption (SEC) in face milling of steel. The proposed approach introduces a corrective factor to estimate the softening of work materials due to thermal effects at large cutting velocity. An experimental campaign on AISI 304 was carried out to investigate the predictive capability of the proposed model. A complete design matrix varying cutting velocity, radial depth of cut and feed rate was performed while measuring the average power consumed as response variable. Experimental results show that SEC reaches a maximum with the increase in the cutting speed. It is demonstrated that the SEC reduction observed at high cutting speeds is due to thermal softening induced by the higher temperatures attained in the work material. The formula proposed aims at providing a simple and accurate expression to select the process parameters in an energy saving perspective, especially in high-speed milling. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Three-dimensional printing technology holds significant potential for enhancing the flexibility and cost-efficiency of producing carbon fiber-reinforced polymer composites (CFRPs). However, it faces limitations such as challenges in achieving high surface qualityand precise dimensional accuracy and managing the distinctive anisotropic mechanical properties that it demonstrates. This study aims to explore the machinability of 3D printed PETG infused with 20% short carbon fiber and to assess the resulting surface roughness and burr formation. Employing a Design of Experiments (DoE) approach, three factors were considered: rotational speed, feed rate, and depth of cut. These factors were tested at varying levels—rotational speeds of 3000, 5500, and 8000 rpm; feed rates of 400, 600, and 800 mm/min; and depth of cut values of 0.2, 0.4, 0.6, and 0.8 mm. The evaluation of machinability relied on two key response parameters: surface roughness (Sa) determined from the milled surface and burr height measured on both sides using a roughness meter. The findings revealed a significant influence of milling parameters on both roughness and burr formation. However, the ideal conditions for minimizing roughness and reducing burr formation did not align. Furthermore, a comparative analysis was conducted between these results and the machinability of PETG under similar conditions. [ABSTRACT FROM AUTHOR]

The aerospace industry is imposing increasingly strict dimensional tolerances, which is forcing continuous development in component manufacturing. Ensuring tight dimensional tolerances is difficult for thin-walled structures due to their reduced stiffness, which are increasingly used in the aerospace industry, where titanium alloys and nickel alloys, among others, dominate. Developments in this area are causing a search for machining conditions that provide sufficient quality characteristics including dimensional and shape accuracy. We discuss, herewith, thin wall deformations in the horizontal orientation of Inconel 625 nickel alloy samples in cross-sections perpendicular and parallel to the direction of tool feed motion. We measured dimensional and shape accuracy using a 3D optical scanner and also using a coordinate measuring machine to correlate these results. We compared the results obtained by the two methods and obtained the maximum discrepancy of the results equal to around 8%. Samples made with adaptive cylindrical milling had similar values of thin wall deviations, with the smallest deviations observed for the sample made with the tool for high-performance machining using adaptive cylindrical milling. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aluminum alloy has the characteristics of good corrosion resistance and high strength, so aluminum alloy workpiece is widely used in the aerospace field. However, in milling, the surface of the aluminum alloy workpiece generates residual stress due to the coupling of force and heat, which seriously affects the fatigue performance of the workpiece. To investigate the residual stress formation mechanism, an analyzed model of machining-induced residual stress considering energy conversion in milling process was proposed. In this process, the milling force prediction model is established. Then, an effective cutting work model is established based on the milling force model. After that, the strain energy density of the machined surface layer was analyzed and the strain energy solution model was established. Subsequently, the prediction models of mechanical stress, thermal stress, and residual stress are established respectively, and the residual stress values are brought into the strain energy model to obtain the strain energy. Afterwards, the functional transformation relationship between effective cutting work and strain energy storage per unit time is analyzed. Finally, several milling experiments were carried out to verify the predicted milling force and residual stress values. Experimental results show that errors between the predicted values and the experimental values are about 5% and 15%, respectively, and the conversion relationship between work and energy show that the stored strain energy per unit time increases with the increase of the effective cutting work. [ABSTRACT FROM AUTHOR]

Ultra-precision machining for large-sagittal aspheric optical elements has become one of the research hotspots in the world's processing and manufacturing field in recent years. This paper mainly studies the processing of large-sagittal MgF2 aspheric optical components, analyzes the grinding tracks of two different grinding methods, and seeks the best grinding method. Experimental research was carried out on three milling modes in the rigid grinding process. In the processing method of pressed milling, the rotational speed of the workpiece has the most significant effect on the surface roughness. The surface roughness Ra can be reduced by reducing the grain size of the grinding wheel and adjusting the processing parameters. Through the cylindrical milling method, the surface roughness Ra measured with the D46 grinding wheel in the direction of rotation can reach the minimum, which is 0.7–0.8 μm. In the fine grinding stage, the circumferential grinding and endface grinding models are established, and the simulation analysis and experimental verification of the trajectory of the abrasive particles in the two grinding methods are carried out. The comparison shows that with endface grinding, the surface of the component is removed evenly in both directions. When the grain size is 28 μm, the surface roughness Ra∥ and Ra⊥ of face grinding are the smallest. Among them, Ra∥ is 0.0458 μm, and Ra⊥ is 0.0369 μm. This study is of great significance in improving the machining efficiency and accuracy of large-sagittal aspheric optical elements. [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]

Surface roughness has a significant influence on the mechanical properties and service life of a component. During face milling, surface roughness greatly varies in the tool step direction and can be controlled by using a surface roughness prediction model. However, the issues of accuracy and efficiency of surface roughness prediction models have not been adequately addressed. This study aims to address these research constraints. An improved surface roughness prediction model is proposed, taking into consideration the influences of insert back cutting and stepover ratio. First, the profile-forming mechanism is analyzed based on geometry and kinematics. Subsequently, an improved surface roughness prediction model is established. Thereafter, the influence of feed per tooth, stepover ratio, corner radius, and minor cutting edge angle on surface roughness are analyzed through numerical simulation. Finally, the experiment of face milling aerospace aluminum alloy 7075 is suggested to verify the improved model, and the Z-Map model is introduced for comparison. Results show that the surface roughness is nonlinear with a feed per tooth and stepover ratio, a monotonic variation with corner radius, and a minor cutting edge angle. The predicted values of the improved model and the Z-Map model for the Rsm are equal to the experimental values. However, the improved model reduces the prediction error of Ra from 11.2 to 4.2% in the non-overlapping compared with the Z-Map model and from 62.58 to 13.34% in the overlapping. In addition, the improved model performs better than the Z-Map model in predicting the shape parameters. This work serves as a significant reference for selecting and optimizing the milling parameters to enable machining quality control. [ABSTRACT FROM AUTHOR]

Tool wear is one of the factors restraining the improvement of product efficiency and machining quality, especially for the aerospace industries with high-added-value parts and hard-to-cut material. During the finish milling of the free-form surface, tool orientations and engagement regions constantly change, which renders the traditional average flank wear hard to describe the tool wear condition accurately. In the present work, tool wear in multiple dimensions is studied comprehensively by using solid carbide ball-end mills with different lend angles, and it is designed by a fixed GH4169 workpiece in various angles. The results show that flank wear, wear depth, wear area, and wear volume increase with the cutting length. The relationship between cutting parameters and those wear features was analyzed with the variance and cluster analysis. The rates of wear area and wear volume were more sensitive to cutting parameters compared to flank wear. What's more, wear volume was affected significantly by all the main effects and some intersections of those factors, that is, spindle speeds, feeds, lead angles, and initial flank wear, which gave the maximum information in distinguishing the effects of cutting parameters. From the perspective of statistics, 36.1% of cases owned higher wear rates in cluster analysis for the stochastic wear process. [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]

Background: The aim of the study was to determine and compare the biaxial flexural strength (BFS) and Vickers hardness (VHN) of additive and subtractive manufactured permanent composite-based restorative materials, before and after thermal aging. Methods: A total of 200 specimens were prepared; 100 disc-shaped specimens (diameter 13 × 1.2 mm) for the BFS test and 100 square specimens (14 × 14 × 2 mm) for the VHN test. The specimens were made from various materials: two subtractive composite-based blocks (Cerasmart 270 [CS], Vita Enamic [VE]), two additive composite-based resins used for two different vat polymerization methods (digital light processing [DLP]; Saremco Print Crowntec [SC] and stereolithography [SLA]; Formlabs Permanent Crown Resin [FP]), and one feldspathic glass-matrix ceramic block (Vita Mark II [VM]) as the control group. Specimens of each material were divided into two subgroups: thermal cycled or non-thermal cycled (n = 10). BFS and VHN tests were performed on all groups. Data were analyzed with two-way ANOVA and post hoc Tukey test (α = 0.05). Results: The type of restorative material used for the specimen had a statistically significant influence on both BFS and VHN values. However, thermal cycling did not affect the BFS and VHN values. After thermal cycling, the results of the BFS test were ranked from best to worst as follows: CS, FP, SC, VE, then VM. For the VHN values, the order from best to worst was as follows: VM, VE, CS, FP, then SC. Conclusions: 3D printed and milled composite groups showed higher BFS than feldspathic ceramics. When the VHN results were examined, it was seen that the 3D resin groups had the lowest VHN values. Furthermore, it was observed that the thermal cycle had no effect on BFS or VHN. [ABSTRACT FROM AUTHOR]

This paper presents a study of 2D roughness profiles on a flat surface generated on a steel workpiece by ball nose end milling with linear equidistant tool paths (pick-intervals). The exploration of the milled surface with a surface roughness tester (on the pick and feed directions) produces 2D roughness profiles that usually have periodic evolutions. These evolutions can be considered as time-dependent signals, which can be described as a sum of sinusoidal components (the wavelength of each component is considered as a period). In order to obtain a good approximate description of these sinusoidal components, two suitable signal processing techniques are used in this work: the first technique provides a direct mathematical (analytical) description and is based on computer-aided curve (signal) fitting (more accurate); the second technique (synthetic, less accurate, providing an indirect and incomplete description) is based on the spectrum generated by fast Fourier transform. This study can be seen as a way to better understand the interaction between the tool and the workpiece or to achieve a mathematical characterisation of the machined surface microgeometry in terms of roughness (e.g., its description as a collection of closely spaced 2D roughness profiles) and to characterise the workpiece material in terms of machinability by cutting. [ABSTRACT FROM AUTHOR]

Additively manufactured (AM) cutting tools enable new design concepts in tool development concerning lightweight construction, damping behavior, and internal cutting fluid supply. So far, the impact of the layer-by-layer manufacturing technique onto the tool performance during machining of aerospace materials is widely unknown. In this study, the performance characteristics of AM indexable milling tools were investigated and compared to a conventionally manufactured tool of the same geometry. The AM tools were manufactured by laser powder bed fusion (LPBF) from a newly developed bainitic steel alloy. All tools were analyzed with two main focuses. Outside the machine tool, geometrical characteristics and mechanical properties were taken into account. Inside the machine tool, during roughing of AISI4140+QT (42CrMo4+QT) and Ti-6Al-4V (ASTM Ti-Grade 5), tool wear, cutting forces, surface roughness and vibration behavior were evaluated. Three tool concepts were compared, a conventional tool, an AM tool, and a hybrid tool with a conventionally manufactured preform and an AM head. Differences in the performance behavior could be traced back mainly to geometrical inaccuracies caused during postprocessing of the tools. Thus, LPBF-manufactured basic bodies seem to meet the requirements as applications for indexable milling tools. Based on this work, future investigations using AM cutting tools can be carried out assuming a negligible influence of the manufacturing technique onto the tool performance during machining. [ABSTRACT FROM AUTHOR]

In this paper, further in-depth research on chip formation mechanism is conducted on the cutting of metallic glasses. The study of chips contributes to a better understanding of the machining nature of materials, which is of significant importance for improving product quality, reducing energy consumption, and resource utilization. This paper employs a combination of simulation and experimental methods, wihch not only analyzes the mechanism of chip formation in depth, but also investigates the time-varying characteristics of cutting forces. The results indicate that, when comparing simulation with experiments, the average error in cutting forces is 7.62%, and the chip morphology is also quite similar. Observations in the simulation show that as the cutting thickness increases from 7.96 μm to 23.87 μm, the free surface of the chip exhibits serrated features, and the main shear zone of the chip becomes clearer. Cutting forces exhibit periodic variations, with alternating peaks and valleys representing the formation of shear zones in the chip. In the experiment, observed chips displays a wrinkled free surface and a smooth non-free surface, with some chip edges exhibiting a burr phenomenon. By selecting appropriate machining parameters, the generation of secondary shear bands on the free surface was effectively reduced. By observing the chip morphology, it is found that the chip formation is accompanied by the material removal of plasticity and brittleness, which is the result of the combined action of heat, stress, and free volume. It should be considered to lower temperature to reduce the phenomenon of chip adhesion, providing guidance for further optimizing the cutting process of metallic glass. This paper can provide to readers further understanding of the chip formation mechanism in milling metal glass. • 2D finite element modeling was used to simulate the chip formation. • The shear zones appeared on the serrated chips. • The experimental results verified the accuracy of the simulation model. • The chips of BMG have smooth non-free surface and wrinkled free surface. • The serrated chips are the result of heat, stress, and free volume. [ABSTRACT FROM AUTHOR]

The production of thin-walled elements, especially those with large overall dimensions, poses numerous technological and operational problems. One of these problems relates to the machining-induced strain of such elements resulting from residual stress generated during the machining process. This study investigates the effect of the technological parameters of milling on residual stress in the surface layer of thin-walled plates made of aluminum alloy EN AW-2024 T351 for aerospace applications. The results have shown that residual stress increases with the cutting speed only to a certain point, reaching the maximum value at vc = 750 m/min. At a cutting speed vc = 900 m/min, residual stress significantly decreases, which probably results from the fact that the milling process has entered the High-Speed Cutting range, and this inference agrees with the results obtained for the cutting force component. Residual stress increases with the feed per tooth, while the relationship between residual stress and milling width is the same as that established for residual stress and variable cutting speed. Positive tensile stress is obtained in every tested case of the milling process. The results have also shown that the induced residual stress affects the strain of machined thin-walled parts, as proved by the strain results obtained for milled thin walls. [ABSTRACT FROM AUTHOR]

This study aimed to develop a practical semi-mechanistic modeling framework to predict particle size evolution during wet bead milling of pharmaceutical nanosuspensions over a wide range of process conditions and milling scales. The model incorporates process parameters, formulation parameters, and equipment-specific parameters such as rotor speed, bead type, bead size, bead loading, active pharmaceutical ingredient (API) mass, temperature, API loading, maximum bead volume, blade diameter, distance between blade and wall, and an efficiency parameter. The characteristic particle size quantiles, i.e., x10, x50, and x90, were transformed to obtain a linear relationship with time, while the general functional form of the apparent breakage rate constant of this relationship was derived based on three models with different complexity levels. Model A, the most complex and general model, was derived directly from microhydrodynamics. Model B is a simpler model based on a power-law function of process parameters. Model C is the simplest model, which is the pre-calibrated version of Model B based on data collected from different mills across scales, formulations, and drug products. Being simple and computationally convenient, Model C is expected to reduce the amount of experimentation needed to develop and optimize the wet bead milling process and streamline scale-up and/or scale-out. [ABSTRACT FROM AUTHOR]

This study has investigated the effect of particle size of non-plastic components of quartz and pegmatite on some technological properties of wall tile bodies. For this, quartz-pegmatite mixtures were further milled up to 90 min. before adding into the body composition unlike the standard body composition, where quartz and pegmatite were used as-received. The physical and mechanical properties of the bodies were investigated and compared with the standard values. Thermal expansion coefficient and moisture expansion values were determined by a dilatometer. Phase analyses were carried out by X-ray diffraction and microstructural characteristics were studied using a scanning electron microscope. Changes in various technological properties with reducing particle size of the non-plastic components were reported, particularly the increased green and fired strength. It was discussed that using finer particle size non-plastic raw materials of quartz and pegmatite would enable not only increased industrial productivity but also increased producibility of thinner large format wall tiles. [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]

The article is a publication of scientific and methodical character. The article is devoted to the preparation of a virtual experiment of milling processing of a complex profile part, which is installed in a fractal vice. It was determined that fractal vices are presented on the technological equipment market in a very limited range. At the same time, the cost of fractal vices is unreasonably high. The cost is commensurate with the cost of the milling machine itself. However, modeling the processing of a part mounted in a fractal vise is of considerable academic interest. Fractal vices use Pascal's law on the plane (with some assumptions). The mathematical model proposed earlier was further developed. The model is flat and consists of a system of three differential equations of the second order. The equations describe plane-parallel and torsional movements of the part. Selected main parameters and their recommended values for the mathematical model of the processing process. At this stage, the main goal of the virtual experiment is to compare the set and real trajectories of the milling cutter. Also, the goal is to analyze the influence of parameters of elastic-damping elements, clamping force, etc. on the result. A matrix of options for conducting a virtual experiment is proposed. The matrix provides a large number of possible movements of the cutter relative to the part (simple, complex, locked, unlocked). It was determined that the matrix of options allows for a large number of possible processing options. From this set, several options are selected, the most suitable for further modeling and comparison with the results of a natural experiment. It is believed that the technological system "machine – vice – tool – workpiece" is a closed dynamic system with negative feedback. However, it is necessary to investigate the behavior of the system without feedback and compare it with the rest of the experiments. [ABSTRACT FROM AUTHOR]

This research investigates tool wear, elemental analysis (EDAX) on the machined surface, surface roughness, microhardness and microstructural changes in the cross-section of milled 304L stainless steel samples under dry and Minimum quantity lubrication (MQL) methods. The MQL process was able to improve the surface roughness for all milling parameters from 17% to 41% compared to the corresponding dry conditions. In dry machining, defects such as built up edge, severe flank wear and tool chipping were created. In MQL mode, these defects were significantly reduced and tool chipping was almost eliminated. By increase of cutting speed and depth, the surface hardness has increased. Compared to the dry method, the MQL reduces the hardness values and hardened depth below the machined surface. According to EDAX analysis on dry and MQL machined surfaces, applying the roughest cutting parameters, it was determined that no change of chemical elements occurred on machined surfaces. Increasing cutting parameters or dry machining causes the plastic deformation to intensify, the microstructure is flattened and the microstructure grains are compressed in the vicinity of the machined surface. The maximum reduction in thickness of deformed layer in MQL compared to dry method is 39%. For each milling sample, there is a direct relationship between the hardened depth and thickness of the corresponding microstructurally deformed layer. [ABSTRACT FROM AUTHOR]

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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]

Governments and industries are developing aggressive policies to reduce carbon emissions and shift from fossil fuels to renewable energy. On the other hand, industries struggle to reduce energy consumption and depend on production lot sizes to control energy requirements. In this regard, energy-efficient processing through CNC machine tools can potentially influence energy demand and requires energy-aware power consumption strategies for machining processes. For manufacturing a single product, predicting energy demand can be decisive in determining parametric control and other factors. Previously analytical models have been largely used to model machining requirements and energy demand. However, these models largely depend on parameterization and do not facilitate the integration of external sub-systems. Therefore, in this paper, an artificial intelligence-based power reduction strategy is developed and implemented on single material (Inconel 718), four control parameters (cutting speed, feed rate, depth of cut and flow rate) and two sub-systems (minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL)). The paper employs four machine learning algorithms,’ K-Nearest Neighbor’, ‘Gaussian Regression’, ‘Decision Tree’, and ‘Logistic Regression’, to evaluate their functionality in predicting power consumption (Pc) of CNC machining systems using a real experimental data set. As per evaluation based on five performance metrics (R-square, MSE, RMSE, MAE, and MedAE), ‘Decision Tree’ has achieved the most accurate power consumption predictions. The comparative results highlight ‘Decision Tree’ as the most better predictor with the optimal max_depth of 2 showing Pc MQL R2 of 0.915 and Pc NF-MQL R2 of 0.931.

The geometry and sharpness of the cutting tool have a substantial impact on the final product’s quality. The geometry of cutting edges is altered throughout the machining process, and wear causes the cutting edge to become dull. This causes increased surface roughness, dimensional inaccuracy, cutting forces, chatter, and vibration. The present research focuses on tool wear (Vb) under dry machining conditions during ball end milling of Ti6Al4V alloy. The experiments are conducted using the full factorial design of experiments with three parameters, viz. feed (f), depth of cut (A t), and rotational speed (S) at three levels. A total of 27 experiments are conducted with one replicate. Artificial neural network (ANN) with 3-18-2-1 architecture is used for the study of the tool wear monitoring (TWM) system. Results revealed that the TWM model is highly adequate, with R 2 = 99.89% and R 2adj = 99.65%. The percentage contribution of A t is the highest, amounting to 80.6%, followed by feed of 12.46%. The rotational speed has the least contribution to tool wear, amounting to 1.5%. From ANN modeling, R 2 value testing is found to be 0.9974, which is close to unity and reveals that the trained model excellently fitted the testing data. The model accuracy is also found to be 96.46%.

The importance of kaffir lime leaf as essential oils (EOs) raw material is starting to get attention because of its commercial value; however, there is no quality reference for kaffir lime leaf EOs, especially in response to various post-harvest handlings. This study aimed to describe the physicochemical characteristics and yield of kaffir lime EOs subjected to different post-harvest. Bogor originated-kaffir lime leaf was prepared to be subjected to several post-harvest treatments, i.e., control/fresh green leaves (P1); milling to produce green leaf flour (P2); drying to produce dry brown leaf (P3), and milling and drying to produce brown leaf flour (P4). The result showed that post-harvest treatment generally decreases an oil yield and increases darkness color, specific gravity and refractive index of tested EOs. Additionally, post-harvest treatment also changes metabolite profile revealed by GCMS analysis. The relative percentage of caryophyllene and citronellol tends to increase, while the linalool and citronellal levels decrease due to tested post-harvest treatment. It was implied that for the benefit of the fragrance industry with a high citronellal requirement, EOs should be made from fresh green leaves and the leaves should be avoided from drying and powdering treatment.

This article addresses how diverse collective behaviours arise from simple and realistic decisions made entirely at the level of each agent’s personal space in the sense of the Voronoi diagram. We present a discrete-time model in two dimensions in which individual agents are aware of their local Voronoi environment and may seek static target locations. In particular, agents only communicate directly with their Voronoi neighbours and make decisions based on the geometry of their own Voronoi cells. With two effective control parameters, it is shown numerically to capture a wide range of collective behaviours in different scenarios. Further, we show that the Voronoi topology facilitates the computation of several novel observables for quantifying discrete collective behaviours. These observables are applicable to all agent-based models and to empirical data.

This paper presents a low-cost milling system composed of spindle mountable on a multi tool 3D printer equipped with maxwell kinematic coupling (E3D “ToolChanger” in this article) as well as two open-source software solutions for implementing a hybrid FFF/CNC manufacturing process. The first solution is the use of a traditional CAM software (FreeCad) for machining programming through the development of a dedicated post-processor. The second is an automatic layer-by-layer hybridization enabled by the software “SuperSlicer”. This method requires no machining knowledge but only allows contouring operations. Results of experiments show that the spindle presented in this work is capable of successfully carrying out a hybrid process that significantly improves the surface roughness parameters, with an improvement factor of 10 for most parameters. An uniformization of surface roughness parameters was also observed in the construction direction and in the deposition/machining direction. The layer-by-layer hybridization yields the better results in terms of surface roughness. This is because the reduced depth of cut (equivalent to a printed layer) minimizes stress and temperature rise, resulting in highly favorable cutting conditions.