Milling Parameters Research Articles

Use of Taguchi method for high energy ball milling of CaCO3

Taguchi’s method was applied to investigate the effect of main high energy ball milling (HEBM) parameters: milling time (MT), ball to powder weight ratio (BPWR), and milling speed (MS) on the CaCO3 crystallite size. The settings of HEBM parameters were determined by using the L9 (33) orthogonal experiments array (OA). The as-received and milled powders were characterized by X-ray diffraction (XRD) scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy. The crystallite size of CaCO3 varied between 140 and 540 nm depending on the HEBM conditions. The analysis of variance (ANOVA) was used to find the significance and percentage of contribution of each milling parameter. It was established that the MT is the most effective parameter followed by MS and BPWR. A confirmation test was carried out with a 90% confidence level to illustrate the effectiveness of the Taguchi optimization method. The optimum milling parameter combination was determined by using the analysis of signal-to-noise (S/N) ratio. Based on the S/N ratio analysis, optimal HEBM conditions were found MT 10 h, MS 600 revolutions per minute (rpm), BPWR 50:1.

Evolution of hole surface integrity in successive processing using sequential milling and laser shock peening

Part's surfaces are usually produced by successive/integration machining process and the performance of the part is directly tied to the generated surface integrity. Holes are commonly used in many critical engineering structures to connect parts, whose surface primarily characterizes a high risk of fretting or contact fatigue failure. In this paper, the evolution of metallurgical and mechanical surface integrity of Ti-6Al-4V alloy hole surface which machined using multi-step milling and successive laser shock peening (LSP) treatment was investigated. Firstly, a special workpiece with various hole surface pieces was designed and four different sequential milling processes were set to conduct the milling experiments. A comprehensive analysis of the evolution of surface roughness, microstructure, microhardness, and residual stress along the sequential processing steps was carried out. The results showed that the forms of surface integrity evolution could be classified into mono-evolution and coupling evolution, which were correlated to the combined effect of the milling parameters, cutter-workpiece engagement nature, milling sequence, milling mode, and the coolant/lubricant applied strategy. Mono-evolution was predominated in material removal sequences (milling sequences), while the coupling evolution was dependent on the radial depth of cut (DoC, ~50 μm). By comparison, coupling evolution was prominent in non-material removal related sequences (LSP treatment). Due to the conformal contact nature of tool-workpiece engagement and the flood cooling strategy, the microhardness in the subsurface layer was not significantly altered in milling sequences, except that the up-milling normally produced a surface with lower hardness and the down-milling produced almost unchanged surface hardness compared with bulk material. The residual stress was a result of the coupling effect of the residual stress field introduced in the previous and current machining sequences, whose in-depth distribution could be represented as an exponential decay function. The degree of influence of the machining sequences and their interactions on the final residual stresses could be evaluated by utilizing a set of weighting coefficients. This research indicated that understanding the effect of successive processing on the surface integrity evolution could help in planning of appropriate processes to achieve desirable surface integrity.

Controlling the parameters of focused ion beam for ultra-precise fabrication of nanostructures

At present, the focused ion beam method is an effective technique for nanoscale profiling of a solid surface and prototyping of micro- and nanoscale structures. The article reveals the results of experimental studies on improving the accuracy and resolution of nanoscale profiling of the surface of solids with a focused ion beam. Investigations of the regularities of the influence of the focused ion beam current, beam dwell time and overlap on the parameters of nanoscale structures and the surface profile have been carried out. The influence of the FIB parameters on the deviation of the structure profile from the specified by the template was estimated. Experimental studies have been carried out to determine the influence of the direction of scanning of the ion beam by the template on the magnitude of the error that occurs when the structure of the graphic template is transferred to the substrate. The optimal relationships between the FIB current and the dimensions of the structures being formed have been determined, thus making it possible to ensure the highest accuracy and rate of formation of nanoscale structures. The results can be used to optimize the choice of the ion-beam milling parameters to achieve the maximum accuracy of reproduction of the given sizes of structures.

Crusher to Mill Transportation Time Calculation—The Aitik Case

Comminution is a major contributor to the production costs in a mining operation. Therefore, process optimization in comminution can significantly improve cost efficiency. The mine-to-mill concept can be utilized to optimize the comminution chain from blasting to grinding. In order to evaluate the mill performance of the ore from a specific location of the deposit, a direct link needs to be established between the mill performance and the place of origin in the mine. Today, technology enables the accurate positioning of drilling, loading, and dumping points in the mine, making the ore flow between loading and crushing more transparent. However, the material flow from the crusher to the mill is not yet fully understood and monitored. This paper presents the development of an ore transportation model, based on the virtual silo concept, between the crusher and the mill for Boliden’s Aitik mine in northern Sweden. The proposed model helps to establish a link between in situ ore location and mill performance. Two transportation time calculations are used, one based on mass balance, and one based on momentary values. Historical data are used to test the capabilities of the model and the results are compared with the transportation time calculated from the mean capacity values, commonly used in previous studies to connect mill parameters with in situ ore location. The comparison of the results show that the mean parameter-based values can be as much as 50% lower than the transportation times, even in normal operation. In the tested times, the transportation time based on momentary values systematically underestimated the cumulated times. The developed model will also serve as a starting point to analyze the effect of geotechnical parameters, in addition to drill and blast design, on the mill performance of the blasted ore.

Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards.

The cutting power consumption of milling has direct influence on the economic benefits of manufacturing particle boards. The influence of the milling parameters on the cutting power were investigated in this study. Experiments and data analyses were conducted based on the response surface methodology. The results show that the input parameters had significant effects on the cutting power. The high rake angle reduced the cutting force. Thus, the cutting power decreased with the increase in the rake angle and the cutting energy consumption was also reduced. The cutting power increased with the rotation speed of the main shaft and the depth of milling induced the impact resistance between the milling tool and particle board and the material removal rate. The p-values of the created models and input parameters were less than 0.05, which meant they were significant for cutting power and power efficiency. The depth of milling was the most important factor, followed by the rotation speed of the main shaft and then the rake angle. Due to the high values of R2 of 0.9926 and 0.9946, the quadratic models were chosen for creating the relationship between the input parameters and response parameters. The predicted values of cutting power and power efficiency were close to the actual values, which meant the models could perform good predictions. To minimize the cutting power and maximize the power efficiency for the particle board, the optimized parameters obtained via the response surface methodology were 2°, 6991.7 rpm, 1.36 mm for rake angle, rotation speed of the main shaft and depth of milling, respectively. The model further predicted that the optimized parameters combination would achieve cutting power and power efficiency values of 52.4 W and 11.9%, respectively, with the desirability of 0.732. In this study, the influence of the input parameters on the cutting power and power efficiency are revealed and the created models were useful for selecting the milling parameters for particle boards, to reduce the cutting power.

Investigation of the third-order optical nonlinearity of Au/GO-CeO2 nanocomposites under different high-energy ball milling parameters

A high-energy ball milling process along with the hydrothermal method was applied to synthesize Au/GO-CeO2 nanocomposites. X-ray diffraction analysis and FT-IR spectroscopy confirmed the successful synthesis of nanocomposites. The ball milling parameters dependence of the nonlinear optical response of Au/GO-CeO2 nanocomposites was investigated by using the Z-scan measurements under pulsed Nd: YAG laser irradiation at 532 nm. The measurements showed that Au/GO-CeO2 nanocomposites have negative nonlinearity which can be controlled by ball milling parameters to achieve higher values for third-order nonlinear optical susceptibility of the order of 10−8 esu. The investigations showed that ball milling parameters such as ball milled time and the number of hardened zirconia oxide balls are important factors in the resultant nonlinear optical parameters. The results suggest that Au/GO-CeO2 nanocomposites with a strong nonlinear optical response can be a promising nonlinear medium that can open a new avenue to graphene-based nonlinear optics.

Achieving high strength and high conductivity of bulk metallic glass composites by controlled milling process

Cu/Cu-Zr-Al metallic glass composites (C/CMGCs) are high-strength conductive materials that have been synthesized by a combination of ball milling (BM) and spark plasma sintering (SPS). This study investigated how the rotational speed of BM process before SPS consolidation affects the microstructure, mechanical properties and electrical properties of fabricated bulk C/CMGCs were investigated. Increasing the BM speed significantly enhanced the mechanical strength while maintaining a high electrical conductivity. However, when the speed exceeded 375 rpm, the high centrifugal force hindered effective impact between the balls and powder to impede further performance optimization. Using the grain boundary strengthening strategy, nanocrystalline copper was strengthened by tuning the milling parameters. The simultaneous achievement of high conductivity and superhigh strength in the C/CMGCs will prompt further explorations of functionalized bulk metallic glass composites with vast untapped potentials.

CNC Milling of Medical-Grade PMMA

This study evaluates CNC milling parameters (spindle speed, depth of cut, and feed rate) on medical-grade PMMA. A single objective analysis conducted showed that the optimal material removal rate (MRR) occurs at a spindle speed of 1250 rpm, a depth of cut of 1.2 mm, and a feed rate of 350 mm/min. The ANOVA showed that feed rate is the most significant factor towards the MRR, and spindle speed (11.83%) is the least contributing. The optimal surface roughness (Ra) occurred at spindle speed of 500 rpm, depth of cut of 1.2 mm, and feed rate of 200 mm/min. The milling factors were insignificant. A regression analysis for prediction was also conducted. Further, a multi-objective optimization was conducted using the Grey Relational Analysis. It showed that the best trade-off between the MRR and the Ra could be obtained from a combination of 1250 rpm (spindle speed), 1.2 mm (depth of cut), and 350 mm/min (feed rate). The depth of cut was the largest contributor towards the grey relational grade (54.48%), followed by the feed rate (10.36%), and finally, the spindle speed (4.28%).

Mechanical Alloying Process Applied for Obtaining a New Biodegradable Mg-xZn-Zr-Ca Alloy

The aim of the present paper is to apply the mechanical alloying process to obtain from powder components a new biodegradable Mg-based alloy powder from the system Mg-xZn-Zr-Ca, with high biomechanical and biochemical performance. Various processing parameters for mechanical alloying have been experimented with the ultimate goal to establish an efficient processing route for the production of small biodegradable parts for the medical domain. It has been observed that for the same milling parameters, the composition of the powders has influenced the powder size and shape. On the other hand, for the same composition, the highest experimented milling speed and time conduct to finer powder particles, almost round-shaped, without pores or various inclusions. The most uniform size has been obtained for the powder sample with 10 wt.%Zn. These powders were finally processed by selective laser melting, an additive manufacturing technology, to obtain a homogeneous experimental sample, without cracking, for future more systematical trials.

Research on Finite Element Simulation and Parameters Optimization of Milling 7050-T7451 Aluminum Alloy Thin-walled Parts

Background: Thin-walled parts of aluminum alloy are easy to occur machining deformation duo to the characteristics of thin wall, low rigidity, and complex structure. Objective: To reduce and control the machining deformation, it is necessary to select reasonable machining parameters. Method: The influence of milling parameters on the milling forces, milling temperature, and machining deformation was analyzed through the established model based on ABAQUS. Then, the corresponding empirical formula was obtained by MATLAB, and parameters optimization was carried out as well. Besides, a lot of patents on machining thin-walled parts were studied. Results: The results shown that the prediction error of milling forces is about 15%, and 20% of milling temperature. In this case, the optimized milling parameters are as follows: ap=1 mm, ae=0.1 mm, n=12 000 r/min, and f=400 mm/min. It is of great significance to reduce the machining deformation and improve the machining quality of thin-walled parts.

Retentive force of telescopic crowns combining fiber-reinforced composite and zirconia.

This study investigated changes in the retentive force of telescopic crowns fabricated by combining a zirconia primary crown and a fiber-reinforced composite (FRC) secondary crown. Primary zirconia crowns were produced with a nominal convergence angle of 0°. Forty-eight secondary crowns were milled from FRC and divided into three study groups (n=16/group) based on milling parameters and post-milling adjustment. The offset parameter used for the final milling step of the inner crown surface was adjusted for a tight initial fit in Group 1 (milling offset: +10 µm, i.e., 2 × 10 µm = 20 µm lower inner diameter compared with the CAD file of the crown) and for improved initial fit (milling offset: -10 µm, i.e., an enlargement of the inner crown diameter by 2 × 20 µm = 40 µm in relation to Group 1) in Groups 2 and 3. The inner surfaces of the secondary crowns were polished with diamond paste in Groups 1 and 2, and silicon points were used for Group 3. The retentive force was measured using a universal testing device. The secondary crown was placed on the primary crown, with the final fitting force set to a load of 100 N. This test was conducted before and after aging (10,000 insertion/removal cycles) under dry and wet conditions. A generalized linear model was used to estimate the differences in the retentive force to elucidate the effects of the milling parameters and polishing methods. We realized an initial retentive force of approximately 10 N. In Groups 2 and 3, the difference was statistically significant between the dry and wet conditions before aging (P < 0.05). There was no significant difference between the dry and wet conditions after aging in any of the groups (P > 0.05). An adequate initial retentive force can be achieved with telescopic crowns combining zirconia and FRC.

Machining-induced characteristics of microstructure-supported LPBF-IN718 curved thin walls

The microstructure-supported design of engineering components is recently gaining attention due to their high strength-to-weight and high stiffness-to-weight properties. The present study investigates the hybrid manufacturing of Inconel 718 curved thin walls with internal microstructural supports fabricated by laser powder bed fusion (LPBF). Printed walls contain a fixed curvature and thickness, whereas the internal microstructures were varied at different inclination angles. In this research, a finish milling operation has been performed at different milling parameters. Machining-induced damages on the internal microstructures have been studied and correlated with geometrical deviation and surface integrity features on the outer thin wall surfaces.

Evaluation of the influence of different milling parameters and tool wear on the rim zone of a 5-axis milled large gear

Machining of gears by 5-axis milling allows additional degrees of freedom in gear design compared to conventional hobbing processes. Changes in the machining technology influence the surface integrity and, thus, the service life of the machined gears. For this reason, different machining parameters were investigated regarding their effects on the surface layer and subsequently on service life. In this paper, the residual stresses and microstructures of a large gear manufactured by 5-axis milling and the service life of test gears are analyzed. With the results from this paper, the surface integrity and service life can be predicted depending on the machining parameters.

Optimization of cutting parameters during CNC milling of EN24 steel with Tungsten carbide coated inserts: A critical review

Recent developments in advanced technology have led to CNC milling machines in many industries to achieve better quality and productivity. The CNC milling machine outperforms traditional machines in precision and surface quality. By optimizing the process parameters, one can fully utilize CNC milling machining. As a result, this paper reviews the optimizing process parameters for CNC milling using Tungsten coated carbide tools. The review shows that the feed, speed, and DOC influence material removal rate, surface roughness, and tool wear. researchers have used Taguchi and RSM for Optimization. Surface and contour graphs to analyze the effect of milling parameters on tool wear, MRR, and surface roughness. For optimization, the response surface methodology (RSM) by approach. The impact of machining parameters on response parameters is analyzed using ANOVA. It was found that there is scope for optimizing the process parameters for the material EN24.

Using support vector regression and non-dominated sorting genetic algorithm in multi-objective optimization of milling of S50C steel under MQL condition

The modern machining industry faces reducing manufacturing cost pressure and improve product quality expectations. Due to this competition a manufacturer must continually identify cost cutting opportunities in manufacturing process. The keys technology represents cost-saving opportunities associated with reducing cutting fluid consumption, cutting energy consumption, and improves the overall performance of machining operations at the same time. Hence, multiple response optimization techniques have recently become the focus of research to improve product quality by increasing surface quality and reduce costs by reducing cutting force, cutting fluids, and energy consumption of the cutting process recently. Among various optimization methods, few Taguchi-based likes as TOPSIS, COPRAS, MOORA, VIKOR... were chosen to solve complex multiple criteria problems. However, the limitation of these techniques is that it was helped to rank and select the best parameters set for the implemented experiments only. In this work, an attempt was made to streamline the milling and coolant condition parameters of S50C carbon steel under MQL condition. Experiments were performed based on Taguchi's L27 orthogonal array. Five input factors includes machining parameters including cutting speed (Vc), feed (fz), and depth of the cut (ap) combined with two coolant parameters such as coolant air pressure (P), flow rate of lubricant (Q) were considered the variants, while specific cutting energy (Ec), material removed rate (MRR) and surface roughness were response variables. Particle swarm optimization Support Vector Machines (SVM) was used to generate the regression model, then Non-dominated Sorting Genetic Algorithm (NSGA) was used to optimize surface roughness (Ra), specific cutting energy (Ec), and production rate (MRR).

Vertebral Lamina State Estimation in Robotic Bone Milling Process via Vibration Signals Fusion

During the robot-assisted laminectomy, vertebral laminas are removed via automatic milling operation, while inadequate estimation of the remaining lamina thickness will result in a dangerous bone milling. In this manuscript, a dynamic milling model is established to analyze the harmonic amplitudes in the milling vibration signals. It is proved that the ratios of harmonic amplitudes in the lamina’s and cutter’s vibration signals are sensitive to the remaining lamina thickness and insensitive to other milling motion parameters. To verify this concept, a robot is applied to mill and thin the porcine spinal lamina layer by layer. The vibration signals of the cutter and lamina are collected simultaneously with an accelerometer and a laser displacement sensor. Fast Fourier transform is applied to extract the amplitude of the harmonic components whose frequency are integer multiples of the cutter spindle frequency. The results show that the classifier can estimate two critical states of the vertebral lamina before the lamina cut off with a success rate of 98.4% based on these harmonic amplitude ratios. The proposed method is beneficial to improve the safety of the automatic bone milling operation of the spinal surgical robot.

Development of nitride and DLC coatings for high performance milling of CFRP products

Currently, much attention in the aviation industry is paid to carbon-fiber-reinforced polymers (CFRP), which are superior in physical and mechanical properties to traditional materials used in the manufacture of aircraft airframe parts. CFRP cutting is associated with significant tool abrasion. Three coatings have been developed to improve the wear resistance of CFRP end mills. The DLC coating is a multilayer structure with an adhesive layer (Cr,Al,Si)N, a first transition layer (Cr,Al,Si)N with a high silicon content, a second transition layer DLC with a high silicon content and a wear-resistant DLC layer. The Zr-ZrN-(Zr,Cr,Al)N coating includes a Zr adhesion layer, a ZrN transition layer and a (Zr,Cr,Al)N wear-resistant layer having a nanolayer structure. The Ti-TiN-(Ti,Al,Cr)N coating also has three functional layers - an adhesive Ti layer, a transition layer (Ti,Al)N and a wear-resistant layer (Ti,Al,Cr)N having a nanolayer structure. The presence of adhesive and transition layers ensures strong adhesion to the substrate, as well as a smooth transition of properties between the substrate and the wear-resistant layer itself. As a result of the study of the power parameters of milling and the intensity of wear when machining with an uncoated tool and with developed coatings, it was found that the most favorable changes in the power parameters of cutting and wear resistance when milling a CFRP product are observed in tools with a DLC coating and Zr-ZrN-(Zr,Cr,Al)N. Analysis of the wear pattern of cutting tools with developed coatings shows noticeable signs of cutting edge wear for uncoated and Ti-TiN-(Ti,Al,Cr)N -coated tools. DLC and Zr-ZrN-(Zr,Cr,Al)N coated tools show no noticeable wear.

A Metaheuristic Optimization Algorithm for energy efficiency in Digital Twins

This work aims to study the role of Digital Twins (DTs) technology combined with the Metaheuristic Optimization Algorithm in manufacturing energy efficiency optimization. Firstly,a machine tool model is established based on DTs technology to study the energy consumption of the milling process of Computer Numerical Machine Tools. Besides, the Particle Swarm Optimization (PSO) algorithm is introduced to optimize the milling parameters of the machining process. Meanwhile, the tool machining path is optimized by combining the Optimized Genetic algorithm and Simulated Annealing algorithm and find the optimal solution of the machining path. On the premise of ensuring the machining quality, this scheme improves the machining efficiency, reduces the energy consumption of the processing process, and improve the energy efficiency. The results demonstrate that the optimized milling parameters can ensure the lowest milling power while considering the maximum material removal rate. Take the plane model as an example. The Improved Genetic Algorithm-Simulated Annealing algorithm can significantly reduce the number of empty walking knife by adopting projection machining and helical machining. The total length of the milling path is reduced by 69.45 ​mm at most, a relative reduction of 10.01%. The average measured energy consumption of milling is reduced by 5.62W∗h compared with the empirical value; the measured average energy consumption of the optimized idle tool is reduced by 0.17W∗h; the total measured energy consumption of milling processing is reduced by 5.73W∗h compared with the empirical value. It can be seen that the optimization algorithm can improve the processing efficiency and reduce the energy consumption.

Evaluation of MWCNT Particles-Reinforced Magnesium Composite for Mechanical and Catalytic Applications.

Aluminum, magnesium, and copper materials must have increased mechanical strength with enhanced wear and corrosion resistance. Substantial research focused on reinforcing hard particles into low-strength materials using stir casting or powder metallurgy. This work is intended to develop the magnesium hybrid matrix with the dispersion of boron carbide (B4C) and multiwall carbon nanotubes (MWCNTs). Hybrid magnesium composites are prepared, although the powder metallurgy route considers different process parameters. Statistical analysis such as Taguchi L16 orthogonal array is involved in this work. It is used to find the magnesium hybrid samples' minimum and maximum wear, corrosion, and microhardness levels. Powder metallurgy parameters are B4C (3%, 6%, 9%, and 12%), MWCNT (0.2%, 0.4%, 0.6%, and 0.8%), ball milling (1, 2, 3, and 4 h), and sintering (3, 4, 5, and 6 h). The ball milling parameters are extremely influenced in the wear test analysis. Minimum wear losses are obtained as 0.008 g by influencing the 4 h ball milling process. Similarly, 3 h of sintering time offered a minimum corrosion rate of 0.00078 mm/yr. In microhardness analysis, the percentage of MWCNTs is highly implicated in narrow hardness resulting in the hardness value of 181. The hardness value is recorded using 0.2% MWCNTs in the magnesium alloy AZ80.

Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability

This paper describes a milling stability identification approach that simultaneously considers: physics-based models for the tool tip frequency response functions and stability predictions; the binary result from a milling test (automatically labeled as stable or unstable based on frequency content); chatter frequency when an unstable result is obtained; and user risk tolerance. The algorithm applies probabilistic Bayesian machine learning with adaptive, parallelized Markov Chain Monte Carlo sampling to update the probability of stability with each milling test. The result is a robust solution for rapid convergence to optimized milling parameters for maximum metal removal rate using all available information.