Milling Experiments Research Articles

Parameter Selection to Ensure Multi-Criteria Optimization of the Taguchi Method Combined with the Data Envelopment Analysis-based Ranking Method when Milling SCM440 Steel

SCM440 steel is a commonly used material for making plastic injection molds and components such as gears, transmission shafts, rolling pins, etc. Surface roughness has a direct influence on the workability and durability of the parts and/or components, while the Material Removal Rate (MRR) is a parameter that is used to evaluate the productivity of the machining process. Furnished products with small surface roughness and large MRR is the desired result by all milling processes. In this paper, the determination of the values of input parameters is studied in order to ensure that during the process of milling SCM440 steel, it will have the smallest surface roughness and the largest MRR. There are five parameters that are required to be determined, namely the cutting insert material, the tool nose radius, the cutting speed, the feed rate, and the cutting depth. The Taguchi method was applied to design the experimental matrix with a total of 27 experiments. Result analysis determined the influence of the input parameters on surface roughness and MRR. The Data Envelopment Analysis-based Ranking (DEAR) method was applied to determine the optimal value of the input parameters, which were used to conduct the milling experiments to re-evaluate their suitability.

Impact of milling machine parameters on the properties of reclaimed asphalt pavement

When using a high content of reclaimed asphalt pavement (RAP) in asphalt production, the RAP properties play a primary role in defining the performance of the new mixture. The RAP properties depend not only on the composition of the old pavement but also on the milling process. Here we performed a full-scale milling experiment at four jobsites. At each of them, three milling machine parameters were varied (moving speed, milling depth, and drum rotational speed), while everything else remained constant (pavement type, milling machine type, etc.). The results demonstrate that at high milling depth, increasing of milling machine moving speed generates larger RAP chunks. There is also evidence that milling in large chunks generates more filler. Finally, we found that the high temperature of milling picks does not age binder and that aggregate angularity does not correlate with milling parameters.

Effects of hybrid nanofluids on machining performance in MQL-milling of Inconel X-750 superalloy

Friction and high temperatures greatly affect machining efficiency when machining superalloy materials. Nanoparticles with high thermal conductivity and lubricity are preferred for increase lubricant performance. Nanofluids prepared with nanoparticles not only reduce environmental concerns but also positively affect the machining efficiency in the sustainable manufacturing process. However, some nanoparticles added in mono form stand out with their thermal conductivity and some nanoparticles with their lubricating performance. For this reason, the lubrication performance of hybrid nanofluids prepared with nanoparticles with different superior properties is a matter of interest. In this study, the machining performance of Inconel X-750 superalloy was investigated by using hexagonal boron nitride (hBN), graphite (Grpt), and MoS2 nanoparticles with different shapes and properties. For this purpose, the milling experiments were performed under three different hybrid nanofluid (hBN/Grpt, hBN/MoS2, and Grpt/MoS2) conditions, at three different cutting speeds (30, 45, and 60 m/min), and three different feed rates (0.05, 0.10, and 0.15 mm/rev). Cutting force, cutting temperature, surface roughness/topography, tool wear, and tool life were selected as machining performance criteria. According to the results obtained from the experiments, it was understood that the hBN/Grpt hybrid nanofluid outperformed hBN/MoS2 and Grpt/MoS2 conditions in all performance criteria. hBN/Grpt hybrid nanofluid achieved 36.17% and 6.08% improvement in tool life compared to Grpt/MoS2 and hBN/MoS2 nanofluids, respectively.

On the material removal mechanism in rotary ultrasonic milling of ultralow-density silica aerogel composites

Silica aerogel composite with ultralow density is a kind of highly porous solid with excellent property of thermal conductivity. It is widely used for thermal insulation in aerospace, national defense and military industries. However, silica aerogel composites are difficult to process, due to the poor mechanical properties, low strength and high brittleness. Therefore, it is necessary to investigate the processing characteristics and material removal mechanism of silica aerogel composites. In this article, a cutting model of silica aerogel composites is established firstly and the fracture mechanism of fiber was analyzed. Then the ultrasonic milling and conventional milling experiments were performed respectively to obtain the features of machined surface. Macro morphology and surface roughness of machined surfaces in different process conditions are compared to investigate the influence of different process conditions on the processing quality. Scanning electron microscope (SEM) was used to obtain the micro morphology of processed surfaces. By comparing and analyzing the micro morphology of processed surfaces, the influence of process conditions on removal mechanism was investigated. The theoretical cutting force and experiment cutting force is compared to verify the cutting model. The results show that the burrs and pits decrease with the ultrasonic vibration amplitude, and increase with the tool diameter. Processing quality of up-milling is better than down-milling. It is indicated that shearing and pulling off are the main removal mechanism of silica aerogel composites. When the silica aerogel composites are processed by rotary ultrasonic milling and up milling, the fibers will be mainly removed by shearing mechanism and the proportion of fibers removed by shearing facture mechanism will be improved with the increase of ultrasonic amplitude.

Chatter suppression and stability analysis of rotary ultrasonic milling titanium alloy thin-walled workpiece

Titanium alloy and its thin-walled structures are widely used in the aerospace field. Aiming at the processing chatter and difficult-to-machine problem of titanium alloy thin-walled workpieces, rotary ultrasonic milling technology (RUM) is employed to restrict machining vibration in this paper. Firstly, for describing its dynamic characteristics, the titanium alloy web with low stiffness is equivalent to a mass-spring-damping system with three degrees of freedom. Then, a novel stability analysis method is proposed for RUM thin-walled workpiece (RUM-tww) through defining an ultrasonic function angle. Furthermore, RUM-tww stability lobe diagrams (SLDs) are achieved based on the semi-discrete method (SDM). The simulation results show that the milling stability of titanium alloy webs is improved effectively under the effect of ultrasonic vibration energy. Compared with conventional milling thin-walled workpiece (CM-tww), the stability region is increased by 80.32% within the spindle speed from 1000 to 5000r/min. Finally, the milling experiments are carried out to verify the validity and rationality of SLDs via analyzing chatter marks, cutter marks, and flatness on the machined surface. The experimental results are in good agreement with the theoretical prediction.

Prediction models for energy consumption and surface quality in stainless steel milling

Stainless steel is a kind of difficult-to-machine material, and the work hardening in milling easily leads to high energy consumption and poor surface quality. Thus, the influence of machined surface hardness on energy consumption and surface quality cannot be ignored. To solve this problem, the prediction models for machine tool specific energy consumption and surface roughness are developed with tool wear and machined surface hardness considered firstly. Then, the validity of the models is verified through AISI 304 stainless steel milling experiments. The results show that the prediction accuracy of the machine tool specific energy consumption model can reach 98.7%, and the roughness model can reach 96.8%. Later, according to the developed prediction models, the influence of milling parameters, surface hardness, and tool wear on the machine specific energy consumption and surface roughness is studied. Results show that in stainless steel milling, the most significant parameter for surface roughness is the machined surface hardness, while that for energy consumption is the feed per tooth. The machine specific energy consumption increases linearly with the increase of the tool wear and the machined surface hardness gradually. The proposed models are helpful to optimize the process parameters for energy-saving and high-quality machining of stainless steel.

Microstructure and machinability evaluation in micro milling of selective laser melted Inconel 718 alloy

Selective laser melting (SLM) of Inconel 718 (IN718) alloy is common these days. The microstructure and surface integrity of fabricated components are highly depend on SLM parameters and post-processing processes. Micro milling is a promising solution to achieve good surface finish. However, the machinability of SLM fabricated IN718 is different than the wrought IN718 due to their significant differences in microstructure and properties, thus technical parameters applicable for wrought IN718 are unsuitable to SLM fabricated IN718. Therefore, the microstructure and machinability of SLM fabricated IN718 during micro milling processes were evaluated in this work, and comparisons with wrought IN718 were made. Micro milling experiments with varied spindle speed and feed rate were performed and comparisons between tool wear, surface roughness, residual stress and micro hardness were made. Further, the microstructure of SLM fabricated and wrought IN718 before and after machining were compared in terms of grain geometry and crystallographic texture. SLM fabricated IN718 shows slight grain coarsening and texture weaken behaviors, which is different with the obvious grain coarsening and slight texture strengthen phenomena of wrought IN718. The SLM fabricated component has lower compressive residual stress as compared with wrought alloy, and the tool wear, surface roughness and micro hardness values are higher while micro milling wrought IN718 alloy. The reasons leading to these differences were analyzed from the perspectives of technological characteristics and material properties. Observed phenomena and clarified mechanisms can be used as basis to determine suitable technological parameters of micro milling SLM fabricated IN718 alloy.

P-061. Successful vaginal delivery in pregnant women with preeclampsia undergoing labor induction with Prostaglandin

Silica aerogel composite with ultralow density is a kind of highly porous solid with excellent property of thermal conductivity. It is widely used for thermal insulation in aerospace, national defense and military industries. However, silica aerogel composites are difficult to process, due to the poor mechanical properties, low strength and high brittleness. Therefore, it is necessary to investigate the processing characteristics and material removal mechanism of silica aerogel composites. In this article, a cutting model of silica aerogel composites is established firstly and the fracture mechanism of fiber was analyzed. Then the ultrasonic milling and conventional milling experiments were performed respectively to obtain the features of machined surface. Macro morphology and surface roughness of machined surfaces in different process conditions are compared to investigate the influence of different process conditions on the processing quality. Scanning electron microscope (SEM) was used to obtain the micro morphology of processed surfaces. By comparing and analyzing the micro morphology of processed surfaces, the influence of process conditions on removal mechanism was investigated. The theoretical cutting force and experiment cutting force is compared to verify the cutting model. The results show that the burrs and pits decrease with the ultrasonic vibration amplitude, and increase with the tool diameter. Processing quality of up-milling is better than down-milling. It is indicated that shearing and pulling off are the main removal mechanism of silica aerogel composites. When the silica aerogel composites are processed by rotary ultrasonic milling and up milling, the fibers will be mainly removed by shearing mechanism and the proportion of fibers removed by shearing facture mechanism will be improved with the increase of ultrasonic amplitude.

SY5-2. Simplified prediction criteria and management of preeclampsia for LMIC

Silica aerogel composite with ultralow density is a kind of highly porous solid with excellent property of thermal conductivity. It is widely used for thermal insulation in aerospace, national defense and military industries. However, silica aerogel composites are difficult to process, due to the poor mechanical properties, low strength and high brittleness. Therefore, it is necessary to investigate the processing characteristics and material removal mechanism of silica aerogel composites. In this article, a cutting model of silica aerogel composites is established firstly and the fracture mechanism of fiber was analyzed. Then the ultrasonic milling and conventional milling experiments were performed respectively to obtain the features of machined surface. Macro morphology and surface roughness of machined surfaces in different process conditions are compared to investigate the influence of different process conditions on the processing quality. Scanning electron microscope (SEM) was used to obtain the micro morphology of processed surfaces. By comparing and analyzing the micro morphology of processed surfaces, the influence of process conditions on removal mechanism was investigated. The theoretical cutting force and experiment cutting force is compared to verify the cutting model. The results show that the burrs and pits decrease with the ultrasonic vibration amplitude, and increase with the tool diameter. Processing quality of up-milling is better than down-milling. It is indicated that shearing and pulling off are the main removal mechanism of silica aerogel composites. When the silica aerogel composites are processed by rotary ultrasonic milling and up milling, the fibers will be mainly removed by shearing mechanism and the proportion of fibers removed by shearing facture mechanism will be improved with the increase of ultrasonic amplitude.

P-057. Preeclampsia prediction based on urine peptidome study

Silica aerogel composite with ultralow density is a kind of highly porous solid with excellent property of thermal conductivity. It is widely used for thermal insulation in aerospace, national defense and military industries. However, silica aerogel composites are difficult to process, due to the poor mechanical properties, low strength and high brittleness. Therefore, it is necessary to investigate the processing characteristics and material removal mechanism of silica aerogel composites. In this article, a cutting model of silica aerogel composites is established firstly and the fracture mechanism of fiber was analyzed. Then the ultrasonic milling and conventional milling experiments were performed respectively to obtain the features of machined surface. Macro morphology and surface roughness of machined surfaces in different process conditions are compared to investigate the influence of different process conditions on the processing quality. Scanning electron microscope (SEM) was used to obtain the micro morphology of processed surfaces. By comparing and analyzing the micro morphology of processed surfaces, the influence of process conditions on removal mechanism was investigated. The theoretical cutting force and experiment cutting force is compared to verify the cutting model. The results show that the burrs and pits decrease with the ultrasonic vibration amplitude, and increase with the tool diameter. Processing quality of up-milling is better than down-milling. It is indicated that shearing and pulling off are the main removal mechanism of silica aerogel composites. When the silica aerogel composites are processed by rotary ultrasonic milling and up milling, the fibers will be mainly removed by shearing mechanism and the proportion of fibers removed by shearing facture mechanism will be improved with the increase of ultrasonic amplitude.

Experimental Study on Fabrication of CVD Diamond Micro Milling Tool by Picosecond Pulsed Laser.

Because of the many advantages of high-precision micromachining, picosecond pulsed lasers (PSPLs) can be used to process chemical-vapor-deposited diamonds (CVD-D). With the appropriate PSPL manufacturing technique, sharp and smooth edges of CVD-D micro tools can be generated. In this study, a PSPL is used to cut CVD-D. To optimize PSPL cutting, the effects of its parameters including fluence, pulse pitch, and wavelength on the cutting results were investigated. The results showed that the wavelength had the greatest impact on the sharpness of CVD-D. With PSPL cutting, sharp cutting edges, and smooth fabricated surfaces of the CVD-D, micro tools were achieved. Finally, the fabrication of CVD-D micro milling tools and micro milling experiments were also demonstrated.

Investigation on the Exit Burr Formation in Micro Milling.

The burr on micro part has harmful effect on the dimensional accuracy and service performance. The original control of exit burr formation during micro milling is desirable and advisable. In this paper, the formation mechanism of exit burr was studied based on the varying cutting direction during micro milling. Three exit burr control strategies were concluded, the material properties embrittlement, the support stiffness increasing and machining parameter optimizing operations. Then, micro milling experiments were carried out to investigate the exit burr morphology and size. It was found that the exit burr formation was attributed to the change of material flowing path at the exit surface, which was caused by the negative shear deformation zone that was induced by the discontinuous shape features. Different exit burr morphologies were classified; the triangle exit burr type was caused by the varying exit burr growing direction along the exit surface. The optimal machining parameters in micro milling to obtain a small exit burr were suggested.

Modeling of cutting forces in helical milling of unidirectional CFRP considering carbon fiber fracture

Helical milling is applied to the machining of CFRP owing to its favorable characteristics such as low cutting forces and heat generation. However, the prediction of helical milling forces remains a problem in CFRP processing. In this study, a novel predictive cutting force model of helical milling for unidirectional CFRP was established. Based on the cutting parameters, the dynamic cutting angle for the fiber and the corresponding cutting states of the fiber during the cutting process were analyzed, and the number and length of cutting edges involved in cutting were calculated. Then, the cutting forces on the cutting-edge micro-element of the periphery edge and bottom cutting edge under two different cutting states were calculated by treating the fiber as an equivalent homogeneous material. The cutting force prediction model was obtained by taking this into consideration. Finally, the helical milling experiment for unidirectional CFRP was carried out. The results show that the model can effectively predict the cutting force. • A new prediction cutting force model of Helical milling for unidirectional CFRP was established. • The model is based on the fracture mode of carbon fiber and cutting edges micro-element cutting force.

In-process stochastic tool wear identification and its application to the improved cutting force modeling of micro milling

Micro milling aims to manufacture miniature structures with high quality and complex features, and the stochastic time-varying tool wear is a crucial factor which has great influence on machining quality and efficiency of micro milling process. To improve the precision of machining and sustainability of micro cutting tools, the in-process tool wear conditions should be identified and updated ahead of time. In this work, an improved integrated estimation method is proposed based on the long short-term memory (LSTM) network and particle filter (PF) algorithm to predict the stochastic tool wear values. The integrated PF-LSTM identification methodology is developed to predict the in-process stochastic tool wear progression on the basis of the historical measurement data. With the estimation of in-process stochastic tool wear, the cutting force model is modified, in which the influence of tool run-out and the trochoidal trajectory of cutting edge are also considered. The proposed integrated estimation method of in-process stochastic tool wear and the modified cutting force model were validated by the micro milling experiments with workpiece material Al6061. It can be seen from the comparison results that the availability and sustainability of micro cutting tool have been improved, and the prediction accuracy also could be increased by 3.4% compared with that without considering the influence of tool wear.

Multi-objective optimization of TC17 high-speed milling parameters using genetic algorithm

To optimize the high-speed milling parameters of titanium alloy TC17, the influence of cutting parameters on cutting force and surface roughness was analyzed according to TC17 high-speed milling experiments. Moreover, the prediction model of the cutting force and the surface roughness was established by the regression method, and the multi-objective optimization using genetic algorithm obtains the range of cutting parameters. Ultimately, the optimized parameters combination was gotten, and its reliability was verified. The result shows that the cutting depth plays a significant role in the cutting force and the surface roughness. The optimized parameters combination can effectively improve machining efficiency and quality.

Optimization of process parameters inend milling of Al-4032 based metal matrix composite using TGRA

ABSTRACT The Al-4032/SiC metal matrix composites are quite useful for low density, high corrosion resistance and improved mechanical properties. Usually, 2–8% SiC reinforcement has been researched for various industrial applications. Progressive increase in the reinforcement (SiC) composition in the Al-4032 matrix causes reduction in ductility and increase in brittleness. This paper presents the research on machining aspects of the Al-4032 with 3% SiC reinforcement. Work has been carried out to study the response of cutting speed (CS), feed rate (FR) and depth of cut (DOC) upon the material removal rate (MRR) and surface roughness (SR). The experiments have been done on the Computer Numeric Control (CNC) vertical machine centre. The machining (end milling) experiments have been conducted following the Taguchi’s L9 orthogonal array. For attempting the bi-objective optimisation (i.e. maximisation of MRR and minimisation of the surface roughness), Taguchi’s grey relational analysis (TGRA) has been implemented using equal weightage to both the response parameters (W1 = W2 = 0.5). The model so obtained has been tested through ANOVA to discover the statistically significant elements. The CS (52.40%) appears to make the largest percentage contribution to the composite response, followed by the FR (26.60%), and the DOC (19.45%).

Oppositely oriented series multiple tuned mass dampers and application on a parallel machine tool

Passive vibration control of the parallel machine tool is challenging due to its closely spaced vibration modes and position-dependent dynamics. Owing to the advantages of significant vibration suppression, high robustness, and no need for additional damping materials, the series multiple tuned mass dampers (MTMDs) appear to be an effective solution to this problem but suffer from large-sized structure and significant parasitic vibrations. This paper proposes a novel type of oppositely oriented series MTMDs with a compact structure and minimized parasitic vibrations, with the effectiveness and robustness of the traditional type retained. An analytical model of the parasitic and primary vibrations of the series MTMDs is presented for quantitative geometry design. The dynamics of the actual main structure and the analytical MTMDs are integrated, followed by the parameter optimization and performance evaluation of the MTMDs considering the effect of background vibration modes. The oppositely oriented series dual-mass TMDs are implemented to suppress the machining vibrations of a parallel machine tool. Modal tests indicate that 72.7% amplitude of the target mode is reduced by the series dual-mass TMDs, which shows a 10.8% improvement compared to the SDOF TMD with equal damper mass. A maximum of 70.1% vibration reduction is achieved in slot milling experiments.

Application of singularity vibration for minimum energy consumption in high-speed milling

To provide a model for real-time prediction of cutting forces, vibrations and optimal energy consumption (EC) model, a new hybrid algorithm based on Back-Propagation Neural Network and Multi-Objective Particle Swarm Optimization (BPNN-MOPSO) was developed to determine the optimal cutting parameters with minimal total energy consumption. High-speed milling experiments were conducted to confirm the proposed online monitoring and optimal model’s accuracy and availability. The proposed optimal method, based on the proposed improvement model, can reduce EC by 10.49% compared to the empirical option method. The feasibility and effectiveness of the proposed model have been verified through experimental processes.

An Investigation into Accumulative Difference Mechanism in Time and Space for Material Removal in Micro-EDM Milling.

In micro-electrical discharge machining (micro-EDM) milling, the cross-section of the microgroove machine is frequently not an ideal rectangle. For instance, there are arc shapes on the bottom and corners, and the sidewall is not steep. The theoretical explanation for this phenomenon is still lacking. In addition to the tip discharge effect, the essential reason is that there is an accumulative difference in time and space during the shape change process of a tool electrode and the microstructure formation on a workpiece. The process parameters are critical influencing factors that determine this accumulative difference. Therefore, the accumulative difference mechanism in time and space is investigated in this paper, and then a theoretical model is developed to simulate the micro-EDM milling process with a straight-line single path. The simulation results for a cylindrical electrode at the two rotational speeds of 0 (nonrotating) and 300 rpm are compared, while the results for a cylindrical electrode and a square electrode at a rotation speed of 0 are also compared to verify that different process parameters generate accumulative differences in the time and space of material removal. Finally, micro-EDM milling experiments are carried out to verify the simulation model. The maximum mean relative deviation between the microgroove profiles of simulation results and those of experiments is 11.09%, and the profile shapes of simulations and experiments have a good consistency. A comparative experiment between a cylindrical electrode and a hollow electrode is also performed, which further verifies the mechanism revealed in the study. Furthermore, the cross-section profile of a microgroove can be effectively controlled by adjusting the process parameters when utilising these accumulative differences through fabricating a microgroove with a V-shaped cross-section by a square electrode and a microgroove with a semi-circular cross-section by a cylindrical electrode. This research provides theoretical guidance for solving the problems of the machining accuracy of detail features in micro-EDM milling, for instance, to machine a microgroove with an ideal rectangular cross-section.

On-line chatter detection in milling using fast kurtogram and frequency band power

The spectral kurtosis (SK) is a useful tool for locating the non-stationary component in the single source signal. It has been verified by the mechanical fault diagnosis. The fast kurtogram (FK) is an improvement method based on the SK. However, for the signals with lower signal noise ratio (SNR), FK is not able to locate the chatter. In this paper, an on-line chatter monitoring using the FK and the frequency band power (FBP) is proposed to resolve this problem. Through the application of the FK, the frequency band with the largest SK can be found. In order to enhance the SK, a bandpass filter is designed. However, for the unstable cutting process, SK is not increased at all. Hence, FBP is adopted to monitor the chatter according to the energy change. The proposed method is verified by the milling experiments and satisfactory detection results are obtained.