Improvement Of Machining Accuracy Research Articles

Accuracy analysis and improvement methods for revolving parts in counter-rotating electrochemical machining with continuous radial feeding

Counter-rotating electrochemical machining (CRECM) stands out as an efficient and cost-effective method for machining aero-engine casings. To maintain stability in the CRECM process equilibrium state, continuous feeding of the cathode tool is essential. However, this continuous feeding approach with single direction of rotation may result in poor roundness and reduced machining accuracy. This paper aims to analyze the sources and rules of roundness error and asymmetry in CRECM. Based on simulation results, a method involving periodic reverse rotation of electrodes with continuous feeding is proposed for CRECM. This approach aims to mitigate the cumulative machining error, thereby significantly improving machining accuracy. Experimental results validate the efficacy of the proposed method at a rotation speed of 0.2 rpm. The roundness error is markedly reduced from 0.19 mm to 0.04 mm, resulting in a more symmetric convex structure. Additionally, the sidewall taper angle is reduced from 14.5 degrees to 6.4 degrees. This underscores the effectiveness of the proposed method in enhancing machining accuracy.

Research on thermal error compensation strategy of CNC machine tools based on full working area modeling

Abstract Traditional manufacturing equipment is developing in the direction of precision, intelligence and integration, and the precision requirements of CNC machine tools are getting higher and higher. Compensating and controlling the thermal error of the machine tool is an important part of improving machining accuracy. This paper uses a cuckoo search algorithm to optimize the BP neural network to get the CSBP neural network model and inputs the temperature value of the CNC machine tool into the CSBP model to get the thermal error prediction results. Combined with the thermal error values of each measurement point on the CNC machine table, the B-spline function is used to fit the thermal error prediction model for the entire working area. Finally, the thermal error compensation system of the CNC machine tool has been established. Simulation and empirical studies show that the fitting and prediction accuracy of the model in this paper are better, and the maximum error value of the prediction is reduced by 20.27% compared to the LSTM model. After the application of the thermal compensation system in this paper, the thermal error of the CNC machine tool is greatly reduced, and most of the offset caused by the thermal deformation of the machine tool is eliminated through compensation. In this paper, the design of a thermal error compensation system based on full work area modeling can effectively reduce the thermal error of CNC machine tools, which can be applied to the actual machining process of machine tools to improve the machining accuracy of CNC machine tools.

Enhancement of optical surface quality based on real-time compensation of temperature-driven thermal errors in diamond turning

In diamond turning, thermal error compensation is critical for improving machining accuracy. In the ultra-precision diamond turning of optical devices, fluctuations in room temperature cause periodic waviness on the machined surface, which degrades the optical performance. Surface finishing processes, such as polishing, are generally required to remove surface waviness. However, the materials used in the polishing process can pollute the environment. Moreover, the polishing process produces a large amount of waste, including contaminated alcohol and tissue. This study presents a new method for compensating temperature-driven thermal errors during single-point diamond turning (SPDT) using machine learning. Long short-term memory (LSTM), an artificial recurrent neural network architecture, was used to estimate the thermal error from the temperatures observed at several locations around the SPDT machine. The performance of the proposed method was evaluated by comparing its estimation accuracy with those of other machine learning methods (multiple linear regression and support vector machine). The thermal error was compensated for by controlling the tool position according to the estimated thermal error. To evaluate the results of the thermal error compensation, the intensities of the laser beam profiles reflected from two flat aluminum mirrors with diameters of 100 mm were observed at several propagation distances. The waviness formed on the uncompensated surface resulted in a dramatic increase in intensity owing to the constructive interference caused by Bragg scattering, whereas the intensity of the reflection from the compensated surface did not vary as the waviness was removed.

Physics-informed hidden markov model for tool wear monitoring

Tool wear monitoring (TWM) is an important part of modern intelligent machining. An efficient and accurate monitoring system will effectively improve machining accuracy and reduce processing costs. At present, the methods for TWM can generally be divided into three categories: physics-based models, data-driven models, and hybrid models. These current approaches are suffered from either low prediction accuracy, insufficient model training, or poor result interpretability due to the nature of the model construction approaches. To overcome the shortcomings of these methods, a physics-informed hidden Markov model (PI-HMM) proposed in this study fully integrates the advantages of the above two methods. Firstly, the model constrains the division of hidden states through the tool wear physical model to improve the physical consistency of the model. Secondly, according to the process parameters and the labels generated by the tool wear physical model, the training set is expanded to solve the problem of insufficient training data of the data model. Finally, the influence of real-time features is added to the established wear state output model and the physical data fusion training strategy is used to train the model to realize the classification of tool wear state and the regression of wear value. The experimental results show that the proposed model in this study achieves an average recognition rate of 0.995 for wear classification and an average coefficient of determination (R2) of 0.968 for wear regression.

Micromachining of nickel and nickel-based alloy surfaces using composite signal

Electrochemical micromachining refers an unconventional technology in the field of machining. With this technology, the ultrashort pulse power supplies are extensively used to address the issue of excessive machining of non-processing areas. However, the reduction of pulse duration is the only effective strategy to enhance the processing accuracy in ultra-short pulse electrochemical microfabrication. Nonetheless, the high cost of equipment and unsuitability in practical production has limited its progress. To resolve this issue, this paper proposes the use of a composite signal in electrochemical micromachining instead of ultrashort pulses. By changing the signal waveform during machining, the energy required for processing can be reduced with the same electromotive force input, thereby reducing the current used to decompose the anode in the circuit and effectively improving machining accuracy. This approach was employed to manufacture micro-structures on a pure nickel sheet, achieving micron-scale accuracy. Moreover, the same level of superior machining accuracy can be achieved when machining micro-structures on hard-to-cut super alloy plates.

Accurate prediction method for a microstructure profile based on the force–displacement coupled servo model

Microstructures of specified shapes have been widely applied in electronics, communication, optics, avionics, medical science, and the automotive field. The ultraprecision single-point diamond turning lathe is a core instrument used in microstructure preparation. As a key technical indicator of an ultraprecision lathe, the servo control accuracy of a system directly affects the machining accuracy of the lathe. Because the profile error of microstructures machined by the slow tool servo of the ultraprecision lathe is at the micrometer level, any disturbance reduces the accuracy of parts machining. This paper proposes a tracking error prediction model based on the force–displacement coupled servo model to study the mechanism of action for the cutting force disturbance on a servo control system. The repeated positioning error of an ultraprecision lathe’s linear axis is added to the force–displacement coupled servo model to propose a more practical profile error prediction model and analyze the effect of the cutting force on the part profile. The experimental results indicate that the force–displacement coupled servo tracking error and profile error prediction model proposed in this paper is more accurate than the existing tracking error modeling method without cutting force disturbance. In addition, this paper analyzes how the cutting force in ultraprecision machining affects the servo system and part profile, which provides a reference for subsequent ultraprecision lathe error analysis and improved machining accuracy.

A novel geometric error compensation method for improving machining accuracy of spiral bevel gear based on inverse kinematic model

A novel geometric error compensation method for improving machining accuracy of spiral bevel gear based on inverse kinematic model

Optimization of cooling water jacket structure of high-speed electric spindle based on response surface method

In high-precision machining machine tools, the high-speed electric spindle is the fundamental transmission component. Nonetheless, the electric spindle's small and tightly sealed internal structure may result in insufficient heat dissipation, resulting in significant heat accumulation during continuous operation. This might induce thermal displacement of the spindle and reduce machine tool machining precision. A response surface was established by a 2-factor 3-level interaction experiment utilizing Design-expert software to reduce the heat displacement of the electric spindle. The electric spindle cooling water jacket was optimized and front and rear bearing cooling water channels were added based on the response surface results. The thermal-solid coupling simulation was carried out using ANSYS, and the optimized data for the front and rear bearing temperature, as well as spindle thermal displacement, were obtained through simulation analysis. Comparing the simulation with the experimental data, it was found that the front and rear bearing temperature decreased by 4.34 °C and 8.97 °C, respectively, and the spindle thermal displacement was reduced by 16.57 μm, resulting in improved machining accuracy. The service life of the bearings was further prolonged by the decreased thermal stress between the inner and outer rings and the balls of the front and rear bearings.

Ultrasonic assisted electrochemical discharge milling of complex glass microstructure with high-quality

IntroductionWith the rapid development of MEMS, the demand for non-conductive hard and brittle material microstructure is increasing. Electrochemical Discharge Machining (ECDM) is one of the most effective methods to machine non-conductive materials like glass and ceramics. However, in the milling process, the problem of discharge pits of different sizes and large thermal cracks caused by excessive discharge energy and heterogeneous energy distribution leads to low machining accuracy, poor stability and surface quality. ObjectivesIn order to solve the above dilemmas and improve the machining quality and stability, a newly developed micro Ultrasonic Assisted Electrochemical Discharge Milling (UAECDM) method is proposed in this paper. MethodsFirstly, a mathematical model is established to reveal the material erosion mechanism in the machining process. Secondly, the influence of ultrasonic vibration on gas film formation and discharge energy is analyzed by theory and simulation. Finally, the effects of ultrasonic amplitude and machining parameters on the quality of microchannels are experimentally studied and optimized by single factor optimization. The machining technology of UAECDM is creatively proposed. ResultsThe experimental results show that adding ultrasonic assistance and using the optimized machining parameters can refine the film thickness, optimize the energy distribution and stabilize the current signal. With assistance of ultrasonic vibration and optimized parameters, a smooth micro channel with width of 118.9 μm was fabricated, and its surface roughness was 0.23 μm, which was 80.99 % declined from 1.21 μm of ECDM. The successful fabrication of microchannel array, two-dimensional and three-dimensional complex glass micro-structures with surface roughness of about 0.2 μm also proves the excellent machining ability of UAECDM. ConclusionIt is proved that UAECDM can effectively improve machining accuracy, stability and surface quality. UAECDM is a desirable method to fabricate micro-channel on glass and will have a very broad industrial application prospect in the future.

Si3N4–TiN conductive ceramic composites: topography on EDMed surfaces and precise drilled holes

In this study, it is challenging to drill a 5 mm hole in a Si3N4–TiN conductive ceramic composite, specifically when attempting to identify an association between EDM machining inputs such as current, pulse on-time, pulse off-time, dielectric pressure and spark gap and performance parameters like as Material Removal Rate, Electrode Wear Rate, Average Surface Roughness, and geometrical tolerances such as Cylindricity, Circularity and perpendicularity. The study examines the surface deformations of a composite comprising EDAX report, machined electrode and molybdenum wire following WEDM machining. Current of 5A, Pulse on-time of 9µs, Pulse off-time of 7µs, spark gap of 0.15 mm, dielectric pressure of 21.0 kg/cm2, material removal rate of 0.004214 g/min, electrode wear rate of 0.000245 g/min and surface roughness of 0.349 µm were found to be optimal. The experimental findings show that good surface finish may be attained on a copper electrode-machined surface, along with improved machining accuracy, closer geometrical tolerances and lesser anomalies.

십자형 교정체를 이용한 5축 공작기계 회전축의 기하학적 오차 추정에 관한 연구

Estimation and compensation of geometric errors for rotary axes are among methods to improve machining accuracy of five-axis machine tools. Studies have been conducted on various methodologies for estimating geometric errors for rotary axes, which are essential for improving machining accuracies of five-axis CNC machine tools. This paper presents a method for estimating geometric errors of a rotating/tilting table using a cross-shaped calibration artifact with a touch trigger probe. The proposed method includes rotary axes error estimation equations for angles of each rotary and tilt axis based on locations of probing points. Computer simulations were performed based on a MATLAB/Simulink and ADAMS cosimulation system using the probing cycle process to verify the proposed method. Computer simulation results confirmed the usefulness of the proposed method in terms of volumetric errors.

A study on new machining method applied to a collaborative robot for drilling

In the assembly of aircraft fuselages, manual hole drilling is conducted in some cases instead of applying robotic drilling due to the issues of burr formation and vibration. In manual operation, tool feeding is realized by applying force to the tool. A prototype system was developed in which a load is applied from the upper side of the spindle by a weight to move a spindle in a vertical downward (CLF method). Drilling in aluminum using this system did not lead to crown-shaped burr formation or irregular vibrations which are often problems in robotic machining. The level of the load applied to the tool becomes an important parameter in the CLF method. To minimize the damage generation, it may be important to adjust the load to the minimum level required for cutting and tool feed. Given such a tool feed system, a drilling unit could be composed from general purpose units such as a shaft and bushing combination. Robotic machining with this type of drilling unit is expected to lead to significant labor savings and improved machining accuracy in machining that is currently conducted manually.

Recent Patents on Cooling System of CNC Machine Tools

Abstract: With the development of machine tools for high precision and high automation, the problem of thermal deformation has become very prominent. As the spindle speed, feed rate, and effective working time of CNC machine tools are much higher than those of ordinary machine tools, the influence of heat generation and thermal deformation of machine tools on machining accuracy is far greater than that of ordinary machine tools. High-efficiency, high-precision processing machine tools, and CNC machine tools require high accuracy and stability. Therefore, the design and manufacturing of CNC machine tools must fully consider the impact of thermal deformation on machining accuracy and take corresponding measures. The cooling of the CNC machine tools can improve the machining efficiency of the machine tools, the quality of parts processing, and the service life of the CNC machine tools. Various representative patents and papers on the cooling of CNC machine tools at home and abroad have been reviewed. By summarizing a large number of patents and papers on the cooling of CNC machine tools, the cooling methods and methods of CNC machine tools, the recovery, and treatment of coolant are analyzed, and the development trend of CNC machine tools is discussed. The improvement of the CNC machine tools cooling system has a great impact on improving machining accuracy, efficiency, and stability. Therefore, more patents on CNC machine tool cooling systems will emerge in the future.

Improving machining accuracy for a robotic arm with hybrid kinematic chains based on deformation characteristics

Joint deformation greatly influences machining accuracy for a robotic arm. In this paper, the deformation characteristics of the robotic arm with hybrid kinematic chains are investigated to improve its machining accuracy. Firstly, the deformation model of the joints has been established based on the Strain energy method and Castigliano theorem according to the robot structure. Secondly, the deformation influence coefficient (DIC) is defined to investigate the deformation influence of main components on the end-effector, and the deformation characteristics are evaluated by the simulation. Finally, a small size robotic arm prototype is established and robotic drilling comparative experiments are conducted. The theoretical and experimental results show that the machining method can be selected according to the DIC, in which the force can be applied to the components with better stiffness. On the other hand, the deformation of driving components can also be reduced when the DIC cannot be adjusted to meet the accuracy requirement.

An approach for improving machining accuracy of five-axis machine tools

An approach for improving machining accuracy of five-axis machine tools

A precision prediction model for the transmission system of swing angle milling head considering machining and assembly errors

The performance of the milling head is affected by the machining and assembly process of the parts. The key to improving machining accuracy and reliability of swing angle milling head is to establish the precision prediction model. Therefore, a precision prediction model of swing angle milling head under the influence of multiple errors’ sources is built. The transmission and accumulation of machining and assembly errors along the assembly sequence path for the transmission system are carried out. All essential components on the assembly sequence path are considered. In addition, the secondary impact of the bearing seat hole is also taken into account. The source of the gear assembly errors is explained. The predicted range of transmission error based on the coupling relationship between assembly errors and transmission error is obtained. A precision experiment is carried out, and the result is within the predicted range. This research demonstrates that the errors' coupling relationship considered in this paper does exist and has an effect on transmission error, which provides a new idea for calculating transmission error of other gear systems.

Development of a high-precision piezoelectric ultrasonic milling tool using longitudinal-bending hybrid transducer

A novel piezoelectric ultrasonic milling tool based on a longitudinal-bending hybrid piezoelectric transducer (LBHT) is proposed. The major novelty of the proposed tool is that through longitudinal vibration and bending vibration of the tool the impact ironing effect (IIE) and intermittent cutting effect (ICE) simultaneously, thus achieving high-precision milling. Above all, the structure and operation principle of the longitudinal-bending hybrid vibration-assisted milling (LBHVAM) system is amply depicted. Then, simulations and analyses are carried out to design and analyze the structure size and critical ICE conditions. Ultimately, a prototype is manufactured and the vibration tests and machining experiments have been carried out. The results indicate that the cutting force of LBHVAM of titanium alloy is 39.3% and 27.2% lower than the conventional milling (CM) and longitudinal vibration-assisted milling (LVAM), and the propensity of burr formation is significantly reduced. Furthermore, the surface roughness under LBHVAM reaches Sa 0.102 μm, which is 85.2% and 54.5% lower than CM and LVAM. Above results demonstrate that the proposed LBHVAM tool not only has unique advantages in reducing cutting force and burr formation but also possesses great potential in improving machining accuracy, which is highly desired in ultra-precision machining of difficult to cut materials.

The Design of an Integrated Monitoring and Maintenance Framework for Newly Developed Equipment: Using Industrial Robot as Example

Anode carbon block grinding & polishing robot is a newly developed equipment urgently required in carbon industry. However, currently there are not specific monitoring and maintenance strategies specifically for this newly developed equipment, and it limits the reliability of the robot equipment in the complicated and server working condition of carbon block production. In this regard, an integrated monitoring and maintenance framework for the grinding & polishing robot is established. The framework aims at not just solving the problem of equipment malfunction reducing, but also improving machining accuracy and keeping optimized process parameters for the robot.

Micro-EDM of micro-stepped hole based on the wear of micro-bit

ABSTRACT Applying different micro-bits with different sizes to carry out step-by-step drilling is a common technique to obtain micro-stepped holes. However, the possibility of repeated misalignments in the clamping of micro-bits will affect the machining accuracy of the micro-stepped holes. Furthermore, for difficult processing materials such as die steel and cemented carbide, it is difficult to obtain ideal machining results through drilling. Under this background, micro-stepped hole was processed on die steel based on the electrical discharge machining (EDM) wear of micro-bits. Firstly, a high-speed rotating micro-bit was used to perform micro-EDM on die steel to obtain a basic micro-hole. During the micro-EDM process, the micro-bit was worn and thus its length was reduced. Secondly, the worn micro-bit shook along a defined axis to carry out micro-EDM on the die steel workpiece, thus machining micro-stepped hole on the basic micro-hole. This method avoided the clamping error of micro-bit found in other techniques and improved machining accuracy of micro-stepped hole. Through the analysis of variance (ANOVA) of processing parameters and the establishment of surface response model, the appropriate processing parameters were selected. Finally, under the action of appropriate processing parameters, micro-stepped hole was obtained by the proposed method.

The Application of Intelligent Manufacturing Technology in CNC Tools Design and Machining

CNC tool is a kind of cutting tools in industrial manufacturing. With the improvement of CNC machining accuracy and quality level, it puts forward more strict requirements for the performance of the cutting tool. Its manufacturing intelligence has become the inevitable choice for the development of the industry. In this paper, the key manufacturing technology of numerical control tools and the application of intelligence in numerical control tool manufacturing are described. the development trend of intelligent manufacturing of numerical control tools is analyzed.