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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. [ABSTRACT FROM AUTHOR]

The topic of hierarchical control of technological machines is one of the most relevant in mechanical engineering technology. The most difficult issue in this area is the organization of interactions between different control levels, on the one hand, and the choice of automatic control methods for each of these control levels (control by deviation, control by disturbance, mixed control, etc.), on the other. In this article, in relation to machining technology, a method and corresponding device are proposed that make it possible to implement the control of cutting force parameters (axial cutting force and cutting torque) in an automatic control system for the deviation of cutting torque by changing the axial cutting force (lower level of control). The lower-level control ensures the required quality of the surface layer (surface integrity) of the machined parts. At the same time, the required dimensional accuracy of parts is ensured at the upper level of control, which is implemented by the CNC system of the machine. At the upper level, automatic control is carried out based on the deviation of the kinematic parameters of the movement of the working parts of the CNC machine (acceleration, speed, displacement). Control switching from upper to lower level and back is carried out without using a spindle linear axial movement sensor. Instead of this expensive sensor, a limit switch (a closed and opened pair of contacts) is used, which fixes the lowest axial position of the spindle (and cutting tool). Based on the signal of closing the specified contacts of the limit switch, a transition from the lower control level to the upper one is carried out. Thus, the upper-level system operates only when these contacts are closed, and the lower-level system operates only when they are open. In relation to the upper-level system, the lower-level control system implements the control "by disturbance" principle, also known in control theory as the "disturbance compensation principle". [ABSTRACT FROM AUTHOR]

The decision-making problem in the process chain of part machining features mainly relies on the experience of process personnel due to the existence of many fuzzy factors, which reduces the quality and efficiency of process design and can not meet economic requirements. In response to the above issues, considering the economy of part processing, the main factors affecting the decision-making of part processing feature process chain were analyzed, and a fuzzy comprehensive decision-making method for part processing feature process chain based on triangular fuzzy analytic hierarchy process (TFAHP) was proposed. Firstly, TFAHP was used to construct a judgment matrix, and indicator weights were calculated based on likelihood. Then, the membership function between the influencing factors of the part machining feature process chain and its candidate set was constructed, the fuzzy comprehensive decision-making of the part machining feature process chain was completed. Finally, taking a certain axis type part as an example, eight-hole machining feature process chains that met the machining requirements were determined. Combining with the actual application of the enterprise, the economic and effectiveness of this method in the decision-making of part machining feature process chains were verified. The research results indicate that the P-value of scheme 8 is 1. 0, which is the optimal machining feature process chain. The quantitative evaluation E-value of this method is 0. 137, which is more economical compared to traditional methods and meets the usage needs. [ABSTRACT FROM AUTHOR]

In the process of conical roller line processing, there will be problems such as low precision of processing parameters, long processing time, low utilization rate of machine tools, high rejection rate, and high processing cost, which will lead to low production efficiency. In order to solve this problem, it is necessary to iteratively optimize the size parameters, including inner diameter, ovality, and taper. By obtaining the optimal parameter combination, the size parameters in the production process are kept consistent, that is, the accuracy and performance of the workpiece during the processing are guaranteed so as to avoid the problem of quality difference, improve the production efficiency and reduce the processing cost. In view of the fact that there are often some constraints on the accuracy and efficiency in the machining process of tapered roller lines, how to optimize the parameters affecting the accuracy and the parameters affecting the efficiency to achieve balance between accuracy and efficiency in order to better meet the needs of customers for multi-objective optimization of the machining process has become the focus of research. Based on the existing research, this paper explores the multi-parameter optimization modeling and application in the machining process of tapered roller lines by constructing a satisfaction function, and then uses a genetic algorithm to iteratively search for the optimal solution by simulating natural selection and the genetic mechanism. Based on Python software v3.12, the production process of tapered roller bearings is simulated. The AHP analytic hierarchy process and CRITIC weight method are used to redistribute the parameter weights respectively. After eight iterations, it is concluded that the weight value assigned by the AHP analytic hierarchy process makes the satisfaction function value reach the best value of 0.99795 and tend to converge stably. The optimized parameter configuration significantly improves the machining accuracy and production efficiency of the tapered roller line. The optimal parameter combination is obtained: inner diameter: 9.9982 mm, ovality: 0.7 mm, taper: 0.5 degrees, production efficiency: 101.0.97 piece/h. In order to verify the optimization effect, the single value (X) and moving extreme difference (Rs) control charts in the measurement value control chart are used to analyze and verify the tolerance values of important parameters in the processing technology of the tapered roller line. The results show that the data points are all within the control limit, indicating that the processing process is in a statistical control state. [ABSTRACT FROM AUTHOR]

Dielectric oil has been recently used in wire electrical discharge machining (wire EDM) for achieving high-precision machining. However, the influence of dielectric oil properties on wire EDM characteristics has not been clarified sufficiently. This study fundamentally investigated the influence of dielectric oil viscosity on wire EDM characteristics. In this study, three types of dielectric oil differing only in viscosity were prepared and examined. Linear cutting experiment results showed that the removal rate and the machined surface roughness increase with dielectric oil viscosity. Then, the influence of viscosity on crater removal volume was investigated to discuss the cause of the change in removal rate, and it was found that crater removal volume increases with the viscosity. Furthermore, CFD (computational fluid dynamics) analysis results and discharge observation results showed that the debris exclusion becomes worse in higher viscosity oil, and the discharge concentration occurs frequently, resulting in the deterioration in machined surface roughness. Next, the difference in machining accuracy with dielectric oil viscosity was investigated. It was found that the corner shape accuracy deteriorates with the increase of viscosity while the machined surface waviness and straightness improve slightly. Structural analysis results showed that wire deflection increases with viscosity, resulting in the deterioration in corner shape accuracy. On the other hand, high-speed observation of wire vibration was carried out, and it was found that the wire vibration decreases in the case of higher viscosity, which leads to the improvement in machined surface waviness and straightness. [ABSTRACT FROM AUTHOR]

Silicon carbide particle reinforced aluminum matrix composites (SiCp/Al), combine the properties of aluminum matrix materials and reinforced silicon carbide (SiC) particles, finding widespread application in aerospace, optics, and electronics. The increased hardness and electrochemical inertness of SiC particles present significant challenges in their processing. This research investigates the impact of photocatalytic processes on machining accuracy in electrochemical processing (ECM). The dissolution characteristics of SiCp/Al during ECM and photocatalytic-assisted electrochemical machining (PAECM) were analyzed with varying electrolyte compositions, using polarization curves and oxidation–reduction potential (ORP). Validation of improved machining accuracy and surface quality in PAECM was achieved through no-feeding machining. According to theoretical principles and laboratory analyses of the workpiece surface, it was found that PAECM, through its photocatalytic reaction, generated more oxides, blocked stray currents and stray corrosion effectively, and attained accuracy in profile creation. Through a comparative analysis it revealed that PAECM exhibited smoother profiles and reduced Overcut Ratio (OCR) in hole and groove machining compared to ECM, particularly in groove machining. Adjusting machining gaps as well as reducing abrasive particle size in PAECM influenced groove depth and width, which achieved optimal morphology with a 0.4 mm gap and a 2–3 nm abrasive particle size, resulting in a 370 μm depth. [ABSTRACT FROM AUTHOR]

The fabrication of microstructures with high efficiency and accuracy on titanium alloys presents significant challenges due to stringent quality requirements. Hybrid laser and electrochemical machining (LECM) has emerged as a viable solution for efficient and precise processing of titanium alloys. This study investigates the material removal mechanism of titanium alloys during LECM, analyzing the machining characteristics under the combined influence of laser processing and electrochemical machining. The impacts of voltage, laser power, and feeding rate on aspects such as aspect ratio, accuracy, efficiency, and surface roughness are examined. Results reveal that synchronous laser irradiation effectively accelerates electrochemical corrosion rates, enhancing the removal capability of the passive film. Notably, LECM outperforms pure ECM, demonstrating significant improvements in parameters such as aspect ratio (394.4% increase), material removal rate (140% increase), and side gap (172.8% increase). Lower laser power is favored for high-precision LECM. An electric circuit model elucidates the titanium alloy material removal mechanism in LECM. Additionally, the study proposes the use of gradient laser power for fabricating high-aspect-ratio structures with efficiency and accuracy. The research successfully fabricates microstructures with elevated aspect ratio and flat bottoms on titanium alloys. [ABSTRACT FROM AUTHOR]

Multi-axis ultra-precision milling is a powerful technology which enables the manufacturing of various complicated curved surfaces. However, in the fabrication of an undetermined and random micro-structured surface, the conventional manufacturing mode from a given geometry model to the final surface machining is no longer applicable. Therefore, this work presents an integrative numerical control (NC) code generation method for fabricating randomly distributed V grooves on the great circles of a spherical surface firstly, in which the tool path generation is integrated into the geometry design process. The randomness of the V grooves refers to the geometric feature that the normal vectors of all the planes of the great circles are randomly generated, which are uniformly distributed towards the corresponding points on a unit sphere. Besides, the singular movements in five-axis milling of the randomly distributed V grooves on the great circles are analyzed. It is revealed that there are two distinct mechanisms of the singularity problem. One is the singular configuration of the machine tool, and the other is the discretization of the generated tool path. Subsequently, a general post-processing algorithm is contributed to solve the singularity problem, which enables the generation of NC code with error control. Furthermore, in five-axis milling of the randomly distributed V grooves on the great circles, the position error of tool virtual center can also significantly influence the machining accuracy. Therefore, a two-point calibration method is proposed to accurately determine the position of tool virtual center. Finally, a high-precision random V groove-structured sphere is machined by using the proposed NC code generation method and the tool virtual center calibration method. The maximum depth error of the V grooves is controlled less than 3.3 μm. The proposed methods in this work enable five-axis milling of high-precision random micro-structures on a spherical surface. [Display omitted] • A method is proposed for tool path generation of random V grooves on a sphere. • Two mechanisms of singularity problem in five-axis milling are revealed. • A novel method with error control is developed to solve the singularity problem. • High precision random V grooves are successfully machined on a spherical surface. [ABSTRACT FROM AUTHOR]

In allusion to traditional manufacturing technology of drill has the disadvantages of long machining cycle and low machining accuracy, while the 3D printing technology has the advantages of fast molding speed and high molding accuracy. In this paper, 3D printing technology is applied to the molds manufacturing of fetal polycrystalline diamond compact（PDC）drill bits and cone-PDC hybrid drill bits. Compared with the traditional press mold and milling mold molding process, 3D printing technology mold molding process reduces the error of 0.50 to 2.00 mm to 0.20 to 0.30 mm, simplifies the traditional manufacturing process, and improves the manufacturing efficiency. At the same time, 3D printing technology is capable of producing any mold of complex surface shape, making the complex structure of the drill manufacturing possible. The field experiments of PDC drill bits produced by 3D printing technology were conducted, and the research results show that the mechanical drilling speed of the new 3D printing drill bit increased by 25.8%, the feed rate increased by 7.7% on average, and the rock breaking efficiency of the new drill bit was greatly improved. It is feasible and practical to integrate 3D printing technology into the production of petroleum drill bit manufacturing. [ABSTRACT FROM AUTHOR]

In view of the defects of the new domestic T800 carbon fiber reinforced plastic （CFRP）, such as lamellar tearing and fiber loss, which would be easily caused by large drilling force and torque during cutting, an experimental platform including a vertical ultrasonic machining center and force measurement system was constructed. Carbide twist drill, carbide candle stick drill and carbide dagger drill were used to compare the hole quality of T800 carbon fiber composite. Under the same technological parameters, the influences of three kinds of cutting tool structures on the cutting force, surface morphology of hole inlet and outlet, aperture deviation and surface roughness of T800 composite were compared with those of conventional drilling （CD）. The ultrasonic vibration assisted drilling （UVAD） method was adopted to carry out feasibility experiments on optimum tool structure. The results show that the carbide dagger drill can effectively suppress the surface defects of T800 composite materials, but the entrance aperture accuracy is poor. The ultrasonic vibration assisted dagger drilling can further improve the quality of hole making, especially significantly improve the aperture accuracy by improving the drilling stability.

This paper innovatively proposes a rapid prediction method for the stiffness the parallel kinematic mechanism (PKM) considering the geometric characteristics of the limb and the external loads with structural mechanics method. And the hybrid PKM named TriMule is taken as an example to demonstrate the correctness of the method by milling experiments of titanium alloy. In the slot milling, the deviation between the simulation of this method and experimental results of dimensional accuracy was only 0.21 %, and in the helical milling, the deviation was only 21 %. On this basis, the average stiffness index is proposed to evaluate the machining dimensional accuracy of the PKM, which is maintain at a high level around 105–107. The method proposed in this paper can predict the machining capacity of the PKM and the approximate machining deviation in working space, and provide a basis for the subsequent optimization of the cutting process parameters and working space. [ABSTRACT FROM AUTHOR]

To improve the localization of material dissolution and fabrication of microstructures with better surface finish, high process complexity, such as different tool shapes, electrolyte flow, and tool insulation, has been utilised in electrochemical micromachining (EMM). Improvement of mass transport, sludge removal, and continuous dissolution are challenging tasks for EMM because bubbles and sludge increase the shielding effects. To solve the problems and achieve precision machining with a better surface finish, a new multi-step pulse waveform (MSPW) is designed indigenously. By incorporating three different peak voltages with a short duration time in the pulse on time of MSPW, potential fluctuation is intentionally induced during machining. Thus, more pulse fall times, short peak voltage duration times, and fluctuations of potential can improve the reduction of bubble size and its detachment rate. Due to it, ion transport phenomena improve, sludge is properly removed from the machining zone, and material dissolution rates increase. The effects of MSPW in EMM are compared with conventional rectangular pulse waveform (RPW). From mathematical estimation, it is found that the power transmission of MSPW is less than RPW, which plays a significant role in stray current minimization. The proposed method is verified by simulation, where it can be observed that current density decreases with increasing bubble size. By capturing images, it is also noticed that the size of gas bubbles decreases, accompanied by a higher detachment rate. Utilising MSPW, precise microdimples are fabricated with minimum surface roughness (Ra), i.e., 0.0241µm, whereas Ra is 0.251µm for RPW. Further, it is identified from the machined microdimples that etch factor improves, diameter minimises, depth increases, no irregular machining appears on the bottom surface, and surface finish also improves as compared to RPW. These improvements are also observed in machined microholes. [ABSTRACT FROM AUTHOR]

Machining is fundamentally a process of material removal. Therefore, machining productivity can be conceptualized as the rapid elimination of a substantial machining allowance, implying a reduction in machining time. This research has yielded a computational model predicated on beam deflection, factoring in the influence of workpiece flexibility on cutting forces, and its repercussions on the material removal rate and precision. The model facilitates the calculation of actual turning productivity. The methodology incorporated modeling the static response of the flexible workpiece to the thrust component of cutting forces. The impacts of flexibility on the beam model responses concerning the material removal rate, and deviations from the desired shape and size were scrutinized. A computational approach, experimentally corroborated, was applied. This approach necessitates cutting force coefficients, which were ascertained through cutting tests and pseudo-inverse regression analysis. The experimental setup for the cutting test incorporated a locally constructed dynamometer for measuring cutting forces, displays on both an LCD and a computer monitor for recording cutting force readings, a cutting tool, and a workpiece. Judging by the coefficients of determination, R2 values of 0.97, 0.89, and 0.93 of the regression calibrating the force coefficients for the tangential, feed, and radial directions-which are used to gauge the accuracy of the determined force coefficient and are typically one or close to one-the derived force coefficients demonstrate high reliability. The developed model is projected to yield significant industrial-economic benefits by curtailing the costs of finishing operations on the CNC lathe machine, owing to the provision of a chronological path to follow while working on a flexible workpiece. [ABSTRACT FROM AUTHOR]

Drill bits are the main rock-breaking tools in the petroleum and gas industry. Their performance directly affects the quality, efficiency, and cost of drilling. Drill bit manufacturing mainly employs traditional mold forming processes such as milling molding and press molding, which have low production efficiency and long processing cycles and are not conducive to rapid responses to field requirements. Inadequate production accuracy makes it difficult to produce drill bits with complex structures. Three-dimensional (3D) printing technology has fast molding speeds and high molding accuracy. In this paper, 3D printing was applied for the first time to the manufacture of molds for carcass polycrystalline diamond compact (PDC) drill bits and PDC–cone hybrid drill bits. In comparison with forging and milling molding, 3D printing improved production efficiency. The manufactured molds had higher machining accuracy. The ability of 3D printing to make molds with complex surfaces enables the development of drill bits with complex structures. A field experiment was conducted on a PDC drill bit produced by 3D printing, which had a higher rate of penetration and was more efficient in breaking rocks than bits manufactured by traditional processes. The ROP of the drill bit increased by 20.1–25.8%, and the drilling depth increased by 7.7–29.5%. It is therefore feasible to apply 3D printing to the manufacture of petroleum drill bits. [ABSTRACT FROM AUTHOR]

The article aims to develop a methodology for calculating and predicting the distribution patterns of wood machining errors to assess the operating conditions of the machine tool according to the technological accuracy criterion. It was analytically proven and experimentally confirmed that Weibull’s law accurately describes the distribution pattern of machining errors on woodworking machines. Based on the results of experimental studies of the accuracy of machining on machines for lengthwise sawing and plano-milling of wood, it was found that the primary indicator of the Weibull distribution law is a shape parameter that takes values within 1.89–3.11. The computational algorithm was developed for statistical modeling of the pattern of the distribution of machining errors according to the Weibull distribution law. It allows for determining the main parameters of the error distribution law and evaluating the operating conditions for the machine tool according to the technological accuracy criterion. The statistical modeling results for the distribution pattern of machining errors are correlated with the experimental data with an accuracy of up to 5 %, which confirms the reliability of the obtained simulation results. The developed approach also minimizes the restoration cost for the machine’s operability.

Due to the limitation of machining accuracy, the transmission performance uncertainty of mass gears must be evaluated quantitatively to provide the basis for its application in the whole machine. Based on the polynomial chaotic expansion (PCE) method, a dynamic uncertainty analysis method for gear systems with a specified precision was proposed in this paper. Combined with tooth surface contact analysis and load-bearing contact analysis, a dynamic model of the gear system was established to fully reflect the influence of typical manufacturing errors. Based on this, a PCE model was established to approximate the system dynamics model. The dynamic uncertainty of the gear system was quantified based on the PCE approximation model and the Monte Carlo method, respectively, and the computational accuracy and efficiency of the PCE model with different orders and numbers of sample points were compared and analyzed. Finally, Sobol′ sensitivity indices from the PCE model of the gear system to random errors were computed, and the primary and secondary relationships of influence on the dynamic performance of the gear system were determined. The results showed that the PCE method had good applicability to the quantification of dynamic uncertainty and error sensitivity analysis of gear systems, and it had both accuracy and high efficiency. [ABSTRACT FROM AUTHOR]

The implementation of precision machine tool thermal error compensation in edge-cloud-fog computing architecture has the potential to control the thermal error. However, the challenges faced by the successful implementation are described as follows: The data collection and transfer efficiency are low, and the control accuracy is not deficient. To address these challenges, a hardware design scheme is proposed for the high-performance intelligent gateway node based on the low-power processor architecture of ARM Cortex-A7. Moreover, a new transformer-improved-gate long short-term memory model is proposed, and then it is embedded into edge-cloud-fog computing architecture. With the implementation of gear profile grinding machine thermal error compensation in edge-cloud-fog computing architecture, the maximum values of the tooth profile tilt deviation are reduced from 17.4 µm to 5.4 µm and from 17.9 µm to 5.8 µm for the left and right tooth flanks, respectively. Moreover, the maximum values of the tooth profile deviation are reduced from 18.9 µm to 6.1 µm and from 18.2 µm to 5.8 µm for the left and right tooth flanks, respectively. Compared with the traditional collection mode, the response delay of the designed intelligent gateway in the acquisition mode is reduced by 40%. [ABSTRACT FROM AUTHOR]

Taking the planetary gear with flexible pins for vertical mills as the research object, a finite element model of flexible pins is established. The dynamics model of planetary gear system with flexible pins is established by considering the effects of manufacturing and mounting errors, time-varying meshing stiffness and bearing support stiffness. The dynamic load sharing performance of the system under equivalent meshing errors is studied. The effects of machining accuracy, error excitation and flexible pin structure on the load sharing performance of the system are investigated. The results show that the flexible pin can reduce the load sharing coefficient of the planetary system compared with the common pin. The lower the gear machining accuracy level is, the more obvious the advantage of flexible pins in load sharing performance is. In addition, the influence of manufacturing error is greater than that of assembly error. The manufacturing error of the sun gear has the greatest influence. The diameter of the pin and the length of the contact line between the pin shaft and the sleeve have a significant impact on the load sharing performance. The reasonable design of the flexible pin structure can improve the load sharing performance of the wheel system.

Diamond wire sawing (DWS) is often used to cut and slice crystalline silicon. The machining accuracy of DWS is a key performance of wire sawing. However, due to the inconsistent deformation of diamond wire relative to the workpiece in different sawing directions, the machining accuracy is different. In this paper, the machining accuracy of DWS in rip sawing and cross sawing was compared. Sawing tests were designed for rip sawing and cross sawing in different feed directions. The length of sawing kerf was used for the evaluation of machining accuracy. It was found that the machining accuracy of diamond wire pushing the workpiece (rip +) is obviously better than that of pulling the workpiece (rip −) in rip sawing as the wire stiffness of rip + is higher. The machining accuracy of cross sawing in different feed directions is related not only to wire stiffness, but also related to the wire torsion produced by lateral feed force in cross sawing. Therefore, the order of machining accuracy 1X + > 4Y − > 2Y + > 3X − shows that the cross sawing accuracy does not show an obvious law relative to rip sawing. A diamond wire electrical discharge sawing (DWEDS) was proposed in rip sawing and cross sawing to compare the machining accuracy of DWS. It was found that the machining accuracy of DWEDS is higher than that of DWS. No significant differences were found in machining accuracy between rip sawing and cross sawing in DWEDS. Finally, the characteristics of cutting force in time–frequency domain were analyzed. [ABSTRACT FROM AUTHOR]

With the increasing application of three-dimensional pure aluminum microstructures in micro-electromechanical systems (MEMS) and for fabricating terahertz components, high-quality micro-shaping of pure aluminum has gradually attracted attention. Recently, high-quality three-dimensional microstructures of pure aluminum with a short machining path have been obtained through wire electrochemical micromachining (WECMM), owing to its sub-micrometer-scale machining precision. However, machining accuracy and stability decrease owing to the adhesion of insoluble products on the surface of the wire electrode in long-duration WECMM, which limits the application of pure aluminum microstructures with a long machining path. In this study, the bipolar nanosecond pulses are used to improve the machining accuracy and stability in long-duration WECMM of pure aluminum. A negative voltage of −0.5 V was considered appropriate based on experimental results. Compared with the traditional WECMM using unipolar pulses, the machining accuracy of the machined micro-slit and the duration of stable machining were significantly improved in long-duration WECMM using bipolar nanosecond pulses. [ABSTRACT FROM AUTHOR]

Machining accuracy is an important index for evaluating the performance of machine tools. To improve the machining accuracy and efficiency of an internal thread grinding machine and reduce the cost, this paper carries out a forward design of the tolerance of the tool motion axis based on the required precision of the workpiece. Using the parameters of a nut raceway, a calculation model of a sand profile under ideal conditions is established under the principle of spiral surface machining and gear meshing. The tolerance criteria are used to evaluate the machining accuracy through multi-body system theory, Monte Carlo simulation, and least squares fitting. Global sensitivity analysis based on variance is used to identify the key factors influencing error. Finally, statistical analysis is completed with the Monte Carlo method to obtain the reliability of machining accuracy. The geometric design is optimized according to reliability to ensure that the tolerance zone meets the required machining accuracy. The feasibility of this method is verified by designing 30 error tolerance zones for an SCS-180 T grinder. [ABSTRACT FROM AUTHOR]

The paper presents probabilistic aspects of diagnostics of grinding processes with consideration of metrological aspects of evaluation of topography of machined surfaces and selected problems of assessment of machining accuracy. The processes of creating the geometric structure of the ground surface are described. It was pointed out that the distribution of features important for process diagnostics depends on the mechanism of cumulative effects of random disturbances. Usually, there is a multiplicative mechanism or an additive mechanism of the component vectors of relative displacements of the tool and workpiece. The paper describes a method for determining the classification ability of specific parameters used to evaluate stereometric features of ground surfaces. It is shown that the ability to differentiate the geometric structure of a certain set of surfaces using a selected parameter depends on the geometric mean of the differences in normalized and sorted, consecutive values of this parameter. A methodology is presented for evaluating the ability of various parameters to distinguish different geometric structures of surfaces. Further, on the basis of analyses of a number of grinding processes, a methodology was formulated for proceeding leading to a comprehensive evaluation of machining accuracy and forecasting its results. It was taken into account that in forecasting the accuracy of grinding, it is necessary to determine the deviations, arising under the conditions of multiplicative interaction of the effects of various causes of inaccuracy. Examples are given of processes in which, due to the deformation of the technological system, dependent on the position of the zone and machining force, varying temperature fields and tool wear, the distributions of dimensional deviations are not the realization of stationary processes. It was emphasized that on the basis of the characteristics of the dispersion of the deviation value in the sum set of elements, it is not possible to infer its causes. Only the determination of the "instantaneous" values of the deviation dispersion parameters allows a more complete diagnosis of the process. [ABSTRACT FROM AUTHOR]

The aims of this study were to estimate the machinability and machining accuracy of polymer-based CAM blocks using the merlon fracture test model specified in ISO 18675: 2022. Three hybrid disc blanks (MazicDuro, HC Disk, and Enamic) and three polymethyl methacrylate (PMMA) disc blanks (PMMA Disk, PMMA Block, and MazicTemp Hybrid) were tested in this study. The machinability was evaluated by assigning scores according to the fracture range of merlons with areas divided by ten vertical planes. The machining accuracy was evaluated by superimposing methods via CAD reference data and CAD specimen data. Within the limits of this study, a thickness of 0.3 mm is recommended for the clinical application of polymer-based CAD/CAM blocks in dental restorations that require superior machinability and accuracy. In addition, the machinability and machining accuracy tests of polymer-based CAM blocks are expected to provide guidelines for preparing accurate dental restorations. [ABSTRACT FROM AUTHOR]

This paper reports the results of research on the influence of the compliance of the technological system used in grinding low-stiffness shafts on the shape accuracy of the workpieces. The level of accuracy achieved using passive compliance compensation was assessed, and technological assumptions were formulated to further increase the shape accuracy of the low-stiffness shafts obtained in the grinding process. Taking into account the limitations of passive compliance compensation, a method for the active compensation of the compliance of the elastic technological system during the machining process was developed. The experiments showed that the accuracy of grinding was most effectively increased by adjusting the compliance and controlling the bending moments, depending on the position of the cutting force (grinding wheel) along the part. The experimental results were largely consistent with the results of the theoretical study and confirmed the assumptions made. Adjusting the compliance in the proposed way allows for the significant improvement in the accuracy and productivity of machining of low-stiffness shafts. [ABSTRACT FROM AUTHOR]

Surface roughness and machining accuracy are essential indicators of the quality of parts in milling. With recent advancements in sensor technology and data processing, the cutting force signals collected during the machining process can be used for the prediction and determination of the machining quality. Deep-learning-based artificial neural networks (ANNs) can process large sets of signal data and can make predictions according to the extracted data features. During the final stage of the milling process of SUS304 stainless steel, we selected the cutting speed, feed per tooth, axial depth of cut, and radial depth of cut as the experimental parameters to synchronously measure the cutting force signals with a sensory tool holder. The signals were preprocessed for feature extraction using a Fourier transform technique. Subsequently, three different ANNs (a deep neural network, a convolutional neural network, and a long short-term memory network) were applied for training in order to predict the machining quality under different cutting conditions. Two training methods, namely whole-data training and training by data classification, were adopted. We compared the predictive accuracy and efficiency of the training process of these three models based on the same training data. The training results and the measurements after machining indicated that in predicting the surface roughness based on the feed per tooth classification, all the models had a percentage error within 10%. However, the convolutional neural network (CNN) and long short-term memory (LSTM) models had a percentage error of 20% based on the whole-data training, while that of the deep neural network (DNN) model was over 50%. The percentage error for the machining accuracy prediction based on the whole-data training of the DNN and CNN models was below 10%, while that of the LSTM model was as large as 20%. However, there was no significant improvement in the results of the classification training. In all the training processes, the CNN model had the best analytical efficiency, followed by the LSTM model. The DNN model performed the worst. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large deformation and low machining accuracy in milling thin-walled titanium alloy parts, an auxiliary milling process based on ultrasonic vibration was proposed. Firstly, the cutting deformation mechanism of titanium alloy was analyzed, and the key factors affecting the workpiece deformation were found out, which provided a reference for the subsequent parameter index analysis. Then, the deformation and stress of titanium alloy thin-walled parts were analyzed by using ABAQUS finite element simulation software, and the action mechanism of ultrasonic vibration and its influence on cutting force were discussed. Finally, the influence of different process parameters on the milling deformation of thin-walled parts under ultrasonic assisted conditions was studied by single factor experiment. The results show that ultrasonic vibration assisted machining can effectively solve the problem of milling deformation of thin-walled parts and greatly improve the machining accuracy. With the increase of spindle speed and ultrasonic power, the deformation of thin-walled parts decreases gradually. With the increase of feed speed, the deformation of thin-wall increases gradually. The experimental and simulation results are basically consistent, and the average error between the experimental and theoretical values is less than 5%, which provides a reference for the selection and optimization of parameters in the milling of titanium alloy thin-walled parts. [ABSTRACT FROM AUTHOR]

Motion position errors, which are caused by factors such as machine tool assembly accuracy and thermal effects, often result in deviations in both machining energy consumption and precision, compared to what is expected. Furthermore, the degree of deviations dynamically varies with the machining schemes. These issues hinder the implementation of high-quality energy-saving machining. To address this challenge, an energy consumption field model is proposed, reflecting the impact of motion position errors on energy consumption and precision variations in different machining scenarios. Firstly, by analysing the conversion process from process plans to programming instructions, a dynamic cascading mechanism is revealed, driven by motion position errors that impact tool cutting trajectory offset, machining energy consumption and precision deviation. Subsequently, a dynamic quantification model for the cutting trajectory offset at the programming origin is established by correlating static geometric errors and dynamic spindle rotation errors with the programming origin coordinates. Finally, a transformation function is established by using the cutting trajectory offset as an intermediate variable to correlate motion position error, machining energy consumption and precision deviation. A spatial energy consumption field model is developed. Experimental results indicate that, while meeting precision constraints in the XYZ directions, a 10.96% reduction in energy consumption is achieved through the correction of programming origin coordinates. • The dynamic mechanism of motion position errors on machining energy consumption is revealed. • An energy consumption field model considering the motion position errors is established. • Machining energy consumption and accuracy is predicted at different co-ordinate positions. • Dynamic changes in energy consumption and accuracy is realized through 3D visual representation. • The optimal programming origin coordinates is used to achieve high-quality energy-saving machining. [ABSTRACT FROM AUTHOR]

According to the characteristics of the magnetorheological fluid, in this thesis, there are designs of a set of adaptive, flexible auxiliary supporting device units, which can be used to develop the processing accuracy of complex curved parts with weak rigidity. The magnetic field of the device is simulated by comsol using finite elements to determine its magnetic strength. It establishes the milling and positioning models of the workpieces with weak stiffness based on the magnetorheological effect, analyzing the positioning constraint models under the auxiliary support, calculating the deformation of the work pieces under static state, studying the influence of the device on the quality of the workpieces. It set up a milling test platform based on magnetorheological auxiliary support, milling parts with weak stiffness under the conditions of different current parameters, collecting acceleration signals for analysis by labview platform data acquisition system, measuring the surface roughness of the milling process. The results agree that, under the action of the magnetorheological auxiliary support, in comparison with the unsupported state, the vibration amplitude is reduced 46.9% to 75.7%, and the surface roughness of the workpieces with weak rigidity is about 69.89% to 80.61% lower.

In order to further optimize the machining accuracy in the process of mechanical manufacturing, computer simulation, analysis and simulation based on finite element have attracted extensive attention and obtained rich research results since they were put forward. The rapid popularization and popularization of finite element technology effectively improves the machining accuracy of mechanical manufacturing, and the experimental research of mechanical manufacturing process promotes the optimization and improvement of finite element technology. This study combs the research process of residual stress prediction and finite element analysis, and summarizes the strategies and methods to improve machining accuracy. At the same time, the shortcomings and deficiencies of the current finite element analysis technology are described in detail, and the problems and directions of the follow-up research of finite element technology in the field of machining are put forward. [ABSTRACT FROM AUTHOR]

The machining precision of the milling head is primarily affected by the thermal errors that originated from the thermal deformation. Thermal error compensation is an economical and efficient method to overcome these thermal errors. The milling head's heat source is analyzed to calculate the thermal boundary load based on component parameters of the milling head. The milling head's thermal deformation is then simulated using ANSYS software to achieve the milling head's temperature distribution and the amount of thermal deformation. Through the design and construction of the milling head temperature and thermal deformation experiment platform, the thermal deformation experiment of the milling head is performed. Accordingly, the measuring point temperature and the tooltip offset are obtained. Finally, a thermal error compensation method is proposed based on the homogeneous transformation. The research results give a theoretical reference and technical support for the thermal error compensation, optimized design, and development of milling heads. [ABSTRACT FROM AUTHOR]

Micropatterned surfaces perform a significant role in the performance of microfabricated devices. Maskless electrochemical micromachining (EMM) is a unique prevalent technique for creating linear micropatterns with précised geometric dimensions and surface quality. However, this method is an advanced micromachining method for fabricating linear micropatterns in comparison to traditional EMM and photolithography, both being costly during mass production. This advanced method is more significant owing to the fabrication of many micropatterned samples with a reusable insulated tool. In this research work, SU-8 2150 mask is re-used many times and produced high quality micropatterns. The developed upward perpendicular cross flow system is utilized for identical micropattern production. Micropatterned properties such as material removal rate (MRR), width overcut, depth, and surface roughness (Ra) are influenced by EMM process variables such as voltage, machining time, inter-electrode gap (IEG), and electrolyte concentration. In addition, to determine the optimal parametric mix, an effective methodology known as Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) is used. The attained optimum process variables are voltage of 10V, IEG of 100µm, concentration of 15g/l, and machining time of 3 min for creation of good quality micropatterns. In addition, validation experimentation is conducted at identified optimal parametric values that confirm improved machining performance. [ABSTRACT FROM AUTHOR]

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The optimal dimensional relations in machining the cap of the rotary mechanism in an Acros 585 combine may be calculated by a graphical method. That clearly shows the dimensional chains and their relationships; permits formalized calculation of the dimensions, margins, and tolerances; and permits selection of appropriate basing and coordination options. In addition, the best sequence of surface machining may be identified, and the optimal technological process may be established. [ABSTRACT FROM AUTHOR]

Due to the limitation of machining accuracy, the transmission performance uncertainty of mass gears must be evaluated quantitatively to provide the basis for its application in the whole machine. Based on the polynomial chaotic expansion (PCE) method, a dynamic uncertainty analysis method for gear systems with a specified precision was proposed in this paper. Combined with tooth surface contact analysis and load-bearing contact analysis, a dynamic model of the gear system was established to fully reflect the influence of typical manufacturing errors. Based on this, a PCE model was established to approximate the system dynamics model. The dynamic uncertainty of the gear system was quantified based on the PCE approximation model and the Monte Carlo method, respectively, and the computational accuracy and efficiency of the PCE model with different orders and numbers of sample points were compared and analyzed. Finally, Sobol′ sensitivity indices from the PCE model of the gear system to random errors were computed, and the primary and secondary relationships of influence on the dynamic performance of the gear system were determined. The results showed that the PCE method had good applicability to the quantification of dynamic uncertainty and error sensitivity analysis of gear systems, and it had both accuracy and high efficiency.