Face Milling Research Articles

Effect of Machining Directions on Surface Integrity of AISI 1018 Steel in a Face Milling Process

This study analyses the effect of machining directions on surface integrity of AISI 1018 steel by performing a face milling operation using the zag toolpath strategy; undertaking a detailed surface roughness check of the machined surface in the cutting and feed directions; studying the microstructure of the as-received workpiece and subsurface of the machined part in the cutting and feed directions in 2% Nital etching; and comparing the grain size before and after the cutting process. Results show that surface roughness values were minimal when measurements were conducted at the middle of the machined surface. Also, surface roughness values were higher in the feed direction than in the cutting direction by 13% due to the presence of feed marks which were clearly visible on the machined surface. The grains at the top machined surface were deformed, elongated, and oriented in the cutting direction as a result of plastic deformations experienced in the machining process, while the grains were also elongated and disoriented in the feed direction. Surface damages caused by the cutting tool’s engagement of the workpiece were clearly seen at the side of the machined surface’s edge. The average grain size value before machining was higher than the average grain size value after machining by 27%, attributed to the plastic deformation of the grain structure as a result of machining. This study has provided an in depth knowledge and understanding of the influence of plastic deformation due to machining on surface roughness and microstructure of the machined part.

ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ РЕМОНТА КОЛЕСНЫХ ПАР ПОДВИЖНОГО СОСТАВА

The possibility of using face milling to restore the tread surface of railway wheel pairs is studied. On the basis of simulation modeling, a conclusion is made about the prospects of using this method for repair. The study objective is to improve the efficiency of repair of rolling stock wheel pairs. The task to which the paper is devoted is the expediency of using face milling when repairing wheel pairs. Research method is modeling. The novelty of the work: defining the possibility of using face milling for the repair of wheel pairs. Study results: the expediency and efficiency of face milling for the repair of rolling stock wheel pairs are found. Conclusions: the use of a new face milling method (turn milling) helps to reduce the complexity of the operation, as well as to increase the resource of wheel pairs in operation due to machining with a minimum allowance.

Optimization of vibration amplitude ratio of face mill tool of VMC and analysis with design expert to endorsing shim design

This paper presents the concept, design and development of shim (passive damper) to improve the stability for high spindle speed machine operation of face mill tool. The objective of this paper is to learning the dynamic behavior of a face mill tool on VMC with dissimilar types of shims which cover investigation of dynamic motion behavior of the face mill tool, the behavior of different types of shim design and behavior of vibration by using the amplitude ratio method and analysis by a Design Expert. Research work supported computational analysis with Ansys, 35 VMC experimental records and analyzed by ANOVA/Design Expert with different type of shims to observe a dynamic behavior of chatter. It include of the effect of process parameters like Cutting speed (250,200,150 m/min), feed per tooth (0.05, 0.1, 0.15mm/tooth), depth of cut (1.2 mm, 1.0 mm, 0.8 mm), and different types of materials (shims) for face mill tool on VMC, for analyzing the responses like amplitude ratio in X – direction, Y- direction with ANOVA and optimizing for AISI 2062 steel by Design Expert. An experimental methodology was developed using the DOE (Design of experiment) technique. The optimum factorial method was used to design an orthogonal array of four factors having three levels. Here, the main results are based on amplitude ratio, ANOVA analysis and optimization. ANOVA was used to decide the effects of the machining parameters on the vibration amplitude ratio in X; and vibration amplitude ratio in Y. This is useful for evaluating the stability of milling operations via time domain FFT and analyzed by ANOVA. Data are validated by 35 sets of VMC experiments. Physical 35 experiments may be not enough in a view of high level researchers, academicians and industrialist to conclude the use of shim and it need in face mill tool on VMC. Hence here optimization based on optimum factorial method is executed using Design Expert software in which 35experiments and its iterations with 70 populations were used to run the program. It is found that the most critical parameter in this study is the material of Shim. At high cutting parameters carbide shim, at low and medium cutting parameters SS shim are given better results by ANOVA and Optimization of Design Expert also validated by 35 sets of VMC experiments. Hence these shim designs endorse versatile solutions.

Machinability improvement investigation in face milling of Ti–3Al–2.5V alloys using TiAlN coated carbide insert under dual nozzle minimum quantity lubrication cooling environment

This research presents the machinability analysis in face milling of Ti–3Al–2.5V alloys using TiAlN-coated carbide insert under dual nozzle minimum quantity lubrication (MQL) cooling conditions. The TiAlN-coated insert has several favorable characteristics like superior wear resistance, greater hardness, and high chemical stability at elevated temperatures. The performance capability of this cutting insert was assessed using machinability responses such as surface roughness, tool wear, and cutting temperature results. The improved quality finish was found with maximum Ra (0.823 µm) while the improved accuracy of flatness (0.044) was obtained even though the rotational speed of the face mill cutter ( N) was highest (1500 r/min). Likewise, an acceptable range of flank wear (0.058–0.118 mm) and a lower range of cutting temperature (65 °C–106.8 °C) was found due to the superior thermal characteristics of TiAlN coating, effective cooling, and lubricating capability of the dual nozzle MQL system in face milling to this alloy. Further, by using the entropy coupled multi-objective optimization ratio analysis method, the optimal value of milling parameters was computed as coolant flow rate ( Q) 50 ml/h, feed speed (vf) 200 mm/min, and rotational speed of the face mill cutter ( N) 500 r/min. At this optimal setting, the optimum Ra, VBc, and T were found as Ra = 0.596 µm; VBc = 0.058 mm, and T = 65 °C, respectively.

Controllable fabrication of microstructures on the metallic surface using oblique rotary ultrasonic milling

Rotary ultrasonic milling emerges as a new and efficient fabrication method for surface microstructures. However, a phenomenon of secondary back-cutting interference exists in conventional rotary ultrasonic milling. It destroys the fabricated microstructure and leads to poor controllability of the surface geometries. In this study, oblique rotary ultrasonic milling (ORUM) is proposed to improve the process controllability by eliminating secondary back-cut interference. In the ORUM, the tool rotation axis is slightly inclined with an oblique angle of around 0.15°. In this way, surface texturing can be established by face milling without secondary back-cutting interference. A kinematic model was developed to predict the surface geometries of fabricated microstructures. Finite element analysis was performed to explore the material removal behavior for different vibration trajectories. Moreover, surface texturing tests were conducted on aluminum and titanium alloy to verify the efficacy of the proposed texturing process. The experimental results showed that the ORUM could texture microstructures on the metallic surface with much better geometric regularity than conventional ultrasonic milling. The model-predicted surface morphology of microstructure agrees well with the experimental results, verifying the high process controllability of ORUM. The effects of process parameters, including the depth-of-cut, spindle speed, and feedrate were presented to further demonstrate the process flexibility of ORUM in terms of the geometry adjustment of microstructures. Finally, fish-scale microstructures were fabricated on freeform surfaces like aircraft wings and implant hip joints, which implies the potential of ORUM for industrial applications.

A novel milling fixture pallet system for production growth of alligator forceps: Design, manufacturing, and testing

Alligator Forceps are an important surgical instrument having an enormous demand in otorhinolaryngology (ENT) because of their ability to fine-tune the amount of pressure exerted and their long reach to remove foreign bodies. Its most important part is the “Base Handle,” requiring special attention while manufacturing because the accuracy of the alligator forceps depends on it. Its rough shape is achieved with the help of forging, and then close tolerances are achieved with the help of three milling operations, Face milling, Peripheral milling & Step milling, performed on a CNC milling machine. These milling operations are very time-consuming when the rough forging is clamped on a conventional vise and machined one piece at a time, taking 94 s per piece due to the significant setup time. A novel milling fixture pallet system is designed using the CAD/CAM of Fusion 360 and is manufactured to clamp ten pieces on a single pallet with a swappable pallet. Simulation of milling operations was performed in Fusion 360, and the same results were achieved with physical milling on a CNC machine, validating the design. The milling time was reduced to 74 s per piece due to less setup time which resulted in reduced cost, and increased production rate. Total 200 s saved per 10 pieces and 83 more alligator forceps produced in 8 h production day as compared to conventional vise. The fixture system also gave better repeatability, no deformation, and less human-machine interaction, which were issues with the vise clamping.

An Equilibrium Decision-Making Approach for Cutting Parameters of a Novel Five-Axis Hybrid Kinematic Machining Unit

To fully disclose the machining potential of a newly developed five-axis hybrid kinematic machining unit (HKMU), an equilibrium decision-making approach for cutting parameters is proposed. With this proposition, a response surface method-based surrogate model is developed to describe the mapping relationships between three design objectives and five cutting parameters. A multi-objective optimization model is further established to find feasible Pareto solutions to cutting parameters. Based on this, the technique for order preference by similarity to ideal solution (TOPSIS) and engineering decision preferences are adopted to make the final decision of cutting parameters. To illustrate the application of the proposed approach, a case study is carried out on face milling of an exemplary HKMU. The equilibrium decisions of three customized machining schemes lead to the machining duration, the cutting force, and the surface roughness reduction by 44%, 43%, and 9%, respectively. This result supports that the proposed equilibrium decision-making approach is able to find the best-compromised solutions for cutting parameters of the HKMU. It is expected that with minor modifications, the proposed approach can be applied to other multi-axis machining devices for finding accurate yet efficient cutting parameter solutions.

Effect of Cutting Parameters on Tool Chipping Mechanism and Tool Wear Multi-Patterns in Face Milling Inconel 718

Tool wear behavior is mainly influenced by cutting parameters for a given tool–workpiece pair and cutting process. Rapid tool wear increases production costs and deteriorates machining quality in manufacturing industries. Inconel 718 is prone to severe tool wear in the milling process due to its high strength under elevated temperature and being prone to work hardening. The effects of cutting speed and feed rate on the tool chipping mechanism and tool wear multi-patterns in face milling Inconel 718 with cemented carbide tools are investigated in this research. Firstly, the face milling experiments of Inconel 718 were conducted with various cutting speeds and feed rates. The experimental results show that the tool wear morphology, especially the tool edge chipping on the flank face, is changed with the cutting parameters. Secondly, the tool chipping mechanism in the milling process is discussed. The effects of cutting speed and feed rate on the chipping and wear patterns of cutting tools are clarified. Finally, the ANOVA analysis is conducted to verify the effects of cutting parameters on cutting force, tool life, and tool edge chipping. This work provides an experimental basis for process parameter optimization to alleviate cutting tool wear in machining processes.

REPAIR OF THE WEAR OF THE MILLS WITH PNTM WHEN PROCESSING THE ABRASIVE POLYMERIC COMPOUND

In the article, the results of the analysis of wear and tear of face milling cutters, equipped with an abrasive polymer compound, which are composed of quartz fine-grained sand and epoxy-diane resin, are shown. It has been established that the prevailing mechanism of tool wear during the processing of such a composite is abrasive wear. The reliability of the characteristics of wear and tear resistance of the cutting tool in the form of a sharpness of cutting was assessed.

Sensor selection and tool wear prediction with data‐driven models for precision machining

AbstractEstimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Experimental investigation into face milling of Inconel X750 super alloy: a study on cutting force and surface topography

PurposeThis work aims to describe the face milling analysis on Inconel X-750 superalloy using coated carbides. The formed chips and tool wear were further analyzed at different cutting parameters. The various impact of cutting parameters on chip morphology was also analyzed. Superalloys, often referred to as heat-resistant alloys, have exceptional tensile, ductile and creep strength at high operating temperatures and good fatigue strength, and often better corrosion and oxidation resistance at extreme heat. Because of these qualities, these alloys account for more than half of the weight of sophisticated aviation, biomedical and thermal power plants today. Inconel X-750 is a high-temperature nickel-based superalloy that is hard to machine because of its extensive properties. At last, the discussion regarding the tool wear mechanism was analyzed and discussed in this article.Design/methodology/approachThe machining parameters for the study are cutting speed, feed rate and depth of cut. One factor at a time approach was implemented to investigate the effect of cutting parameters on the cutting forces, surface roughness and material removal rate. The scatter plot was plotted between cutting parameters and target functions (cutting forces, surface roughness and material removal rate). The six levels of cutting speed, feed rate and depth of cut were taken as cutting parameters.FindingsThe cutting forces are primarily affected by the cutting parameters, tool geometry, work material etc. The maximum forces Fx were encountered at 10 mm/min cutting speed, 0.15 mm/rev feed rate and 0.4 mm depth of cut, further maximum forces Fy were attained at 10 mm/min cutting speed, 0.25 mm/rev feed rate and 0.4 mm depth of cut and maximum forces Fz were attained at 50 mm/min cutting speed, 0.05 mm/rev feed rate and 0.4 mm depth of cut. The maximum surface roughness value was observed at 40 mm/min cutting speed, 0.15 mm/rev feed rate and 0.5 mm depth of cut.Originality/valueThe effect of machining parameters on cutting forces, surface roughness, chip morphology and tool wear for milling of Inconel X-750 high-temperature superalloy is being less researched in the present literature. Therefore, this research paper will give a direction for researchers for further studies to be carried out in the domain of high-temperature superalloys. Furthermore, the different tool wear mechanisms at separate experimental trials have been explored to evaluate and validate the process performance by conducting scanning electron microscopy analysis. Chip morphology has also been evaluated and analyzed under the variation of selected process inputs at different levels.

Multi‐objective optimization for cost‐efficient and resilient machining under tool wear

AbstractWith the onset and rapid growth of smart manufacturing, there is a constant increase in the demand for automation technologies to enhance productivity while providing uninterrupted, cost‐efficient, and resilient machining. Traditional manufacturing systems, however, suffer from several losses due to machine faults and degradation. Specifically, tool wear directly impacts the precision and quality of the milled parts, which causes an increase in the scrap production. Hence, more attempts are required to meet the desired quota of successful parts, which in turn results in wasted material, longer delays, further tool degradation, and higher energy, machining, and labor costs. As such, this paper develops a multi‐objective optimization framework to generate the optimal control set points (e.g., feed rate and width of cut) that minimize the total cost of machining operations resulting from multiple contradictory cost functions (e.g., material, energy, tardiness, machining, labor, and tool) in the presence of tool wear. Notably, we estimate the total expected cost in dollars, which provides automatic and intuitive weighting in this multi‐objective formulation. The optimization framework is tested on a high‐fidelity face milling model that has been validated on real data from industry. Results show significant dollar savings of up to as compared to the default control scheme.

SIMULATION OF THE STATE OF THE CHIP FORMATION ZONE DURING FACE MILLING OF HARDENED STEEL

The article considers the results of modeling the stress-strain and thermal state of the cutting zone during face milling of hardened steel with a tool equipped with polycrystalline superhard composite based on cubic boron nitride. The influence of strengthening the surface layer of the processed material, characteristic for different passes of different tools, on the cutting forces, shrinkage of chips, the length of contact of chips with the front surface of the tool is shown. The connection of non-stationary nature of machining with incisions of each of the tool blades and exit from the cutting zone with the presence of periods of increase in cutting temperature and cooling of the cutting tool has been studied.

Influence of Wood Surface Preparation on Roughness, Wettability and Coating Adhesion of Unmodified and Thermally Modified Wood

In this research, the influence of face milling, sanding and UV irradiation of the hornbeam and ash wood sample on the wetting and adhesion strength of solvent-based and water-borne coating was studied. The adhesion of coatings to substrates is one of the most important parameters for finishing quality and service life of wood coatings, while wetting properties are usually used to assess the quality of surfacing process and could also provide important information on the adhesion ability of coatings. Surface roughness, contact angle of coatings and water as well as adhesion strength of coatings were tested on differently prepared (face milled, sanded and UV irradiated) samples of unmodified and thermally modified ash and hornbeam wood. Surface roughness was measured with stylus-type profilometer over the traverse of 12.5 mm and with a cut-off value of 2.5. Contact angle was measured using the sessile drop method 2 s, 10 s and 30 s after the application of the liquid drop on the sample surface, and adhesion strength was measured according to ASTM D4541. Results showed that sanding of hornbeam and ash wood resulted in the least rough surface compared to the face milled and UV irradiated surface. Contact angles of the water-borne coating were on average three times higher than the contact angles of the solvent-based coating. Sanding the surface of hornbeam and ash samples increased the adhesive strength in relation to the face milled surface, while UV irradiation of the sanded surface decreased the adhesive strength of most samples coated with solvent-based coating.

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. Here, a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

The effect and optimization of cutting parameters of Vanadis 4E powder metallurgical tool steel on tool wear: surface roughness in face milling

The effect and optimization of cutting parameters of Vanadis 4E powder metallurgical tool steel on tool wear: surface roughness in face milling

Comparative Analysis of Face Milling in Dry and Wet Condition of Al 8011 For Minimum Surface Roughness in Face Milling

Abstract: The quality of machined components is evaluated in respect of how closely they adhere to set product finish, and reflective properties. Dimensional accuracy, tool wear and quality of surface finish are three factors that manufacturers must be able to control at the machining operations to ensure better performance and service life of engineering component. Aluminum alloys are extensively used as a main engineering material in various industries such as automotive industries, the mould and the die components manufacture and the industry in which weight is the most important factor. The purpose of this research is to investigate the effect of the main factors of the surface roughness and flatness in aluminum 8011 face milling with dry and wet condition. This experimental investigation to be conducted by using VMC controlled milling machine with 30mm face milling cutter with carbide multiple inserts. The same parameters were executed during the operation only difference minimum quantity lubricant for one set of operation and another set of operation without lubricant. The experimental results were evaluated using Taguchi technique minimum surface finish obtained at medium speed and maximum feed and depth of cut 0.222 µm in the dry condition during the face milling operation. The minimum flatness was obtained 0.012 mm at wet condition. minimum surface finish obtained through dry condition. Optimal control factor and ANNOVA calculations were found for face milling operation of AA8011.

High-speed face milling of AZ91 Mg alloy: Surface integrity investigations

Magnesium (Mg) alloys are popular in the aerospace and automotive sector owing to their light-weight aspects. Amongst various Mg alloys, AZ91 alloy behaviour under machining has been trending and needs to be completely explored. The selection of optimal machining parameters is an important decision making process to achieve highest quality along with reduced cost and time. In this regard, this article describes experimental investigations to evaluate the performance of face milling operations on the surface characteristics of AZ91 magnesium alloy. The experiments were carried out with uncoated and PVD (Physical Vapour Deposition) coated carbide inserts at three levels of cutting speed (500, 700 and 900 m/min), feed rate (0.1, 0.2 and 0.3 mm/teeth) and depth of cut (0.5, 1.0 and 1.5 mm) under dry machining conditions. Major surface integrity indicators, such as roughness, hardness, residual stresses and microstructure are analysed. Chip morphology is also analysed and the correlation between chips and machined surface roughness is established. Face milling operation significantly improved surface roughness and microhardness of this alloy. Roughness improvement up to 85% (0.067 μm) and hardness improvement up to 33% (91.8 HV) is observed from the use of uncoated carbide inserts. Whereas, from PVD coated inserts, roughness improvement up to 81% (0.083 μm) and hardness improvement up to 60% (111.2 HV) is achieved. A similarity in behaviour between the two types of insert conditions are observed with increase in roughness from feed increase and decrease in hardness from cutting speed increase. Microstructural analysis showed PVD coated insert conditions producing surface with no defects, when compared to the crack observed in the surface from the use of uncoated carbide inserts. Marginally higher compressive residual stresses are detected at the surfaces from use of the uncoated inserts. Overall, due to no surface defect and the significant improvement in hardness and roughness from the PVD coated inserts, they are recommended for use in face milling operation for the cutting conditions investigated in this study.

Optimization of sustainable milling of SKD11 steel under minimum quantity lubrication

In this study, the sustainably face milling of SKD11 steel under a minimum quantity lubrication condition was investigated. The goal of this work is twofold: (i) observing the impact of main milling parameters, including cutting speed ( Vc), depth of cut ( ap), and feed per tooth ( fz) on surface roughness ( Ra) and specific cutting energy (SCE), and (ii) finding out an optimal combination of cutting parameters for ameliorating the surface quality, productivity, and diminishing energy consumption. For this purpose, the experiment was designed by using the Box–Behnken matrix. A series of 15 experimental runs have been conducted to acquire experimental data. The regression models of Ra and SCE were subsequently developed and evaluated by using the analysis of variance. Finally, the multi-objective optimization issue was resolved by using the technique for order of preference by similarity to ideal solution (TOPSIS) algorithm and the desirability approach (DA). The results show that the parameter fz reveals the highest impact on surface roughness and SCE, followed by ap and Vc. The TOPSIS method allows finding the optimal solution with a reduction of 46% in terms of SCE when compared with that achieved by DA. This is significant in the context of sustainable manufacturing. This research is expected to enrich the knowledge of milling SKD11, and the achieved results can be used for research community and manufacturing industries.

A robust digital image processing method for measuring the planar burr length at milling

The burr formation is one of the difficulties at the cutting processes; moreover, its size and characteristics show changes along the edge; therefore, it is hard to measure. The main aim of the paper is to develop a novel algorithm that is suitable for measuring the planar burr length of such contours that cannot be scanned below. The proposed method uses a digital microscope attached to a machine tool and using existing image processing algorithms in combination with novel approaches. The advantage of the current method is that, it allows collecting the height of burr along the workpiece automatically since it is able to handle and avoid interruptions, branches and provide uniform thickness for the determined contour. Another advantage is the extended measurement ability for workpieces which contains inner contours and cannot be illuminated from below. The method was tested with sample images and also with face milling experiments, and the results were validated with the data originating from a coordinate measurement machine. The result shows a good agreement at the validation. The available accuracy mainly depends on the applied measuring equipment (resolution and magnification of camera) and set up. The theoretical accuracy of the proposed method can even approximate the magnitude of the pixels. In this research work, the achieved accuracy was ±0.06 mm in the best case, and ±0.1 mm in the worst case with the used experimental device.