Table of Content

06 December 2025, Volume 13 Issue 4

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Deformation mechanism of gallium nitride in nanometric cutting

Xu Ma, Min Lai, Feng-Zhou Fang

2025, 13(4):  689-700.  doi:10.1007/s40436-024-00534-9

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Gallium nitride (GaN) is a third-generation semiconductor and an important optical material requiring high surface integrity. In this study, molecular dynamics simulations were conducted to investigate the machining mechanism of single-crystal GaN during nanometric cutting. The stress distribution and generation/motion of dislocations in GaN during nanometric cutting were found to be closely related to slip systems. The relationship between the crystal phase transformation and dislocations during cutting was also identified. Microcracks occur during the unloading of stress perpendicular to the (0 0 0 1) plane. The fluctuation of the cutting forces during cutting was explained from the perspective of crystal phase transformation. This study helps understand the deformation mechanism of materials with hexagonal close-packed crystal structures in nanometric cutting and promotes the development of relevant mechanical processing technologies.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00534-9

Experimental study on ultrasonic vibration-assisted grinding of quartz glass microchannel

Yan-Jun Lu, Ming-Rong Guo, Yong-Qi Dai, Qiang Wang, Hu Luo

2025, 13(4):  701-717.  doi:10.1007/s40436-024-00536-7

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Microfluidic chips prepared from quartz glass are widely used in medical diagnoses, biochemical analyses, and drug screening. The performance of microfluidic chips is directly determined by the quality of the machined microchannels on high-performance quartz glass. In this study, ultrasonic vibration-assisted grinding (UVAG) is proposed to fabricate quartz glass microchannels with high efficiency and accuracy. A motion model for the trajectory of a single abrasive grain was established, and the intermittent cutting mode of a single abrasive grain was analyzed. Additionally, experiments were conducted to compare the features of UVAG with those of conventional grinding (CG) to investigate the influence of process parameters such as spindle speed, feed speed, grinding depth, and ultrasonic power on the surface roughness and morphology of the ground samples, geometric precision, edge chipping of the microchannels, and wear condition of the grinding tools. Furthermore, the UVAG process parameters were optimized. The results demonstrate that UVAG provides better machining quality and minimizes grinding tool wear. After UVAG, on average, the ground surface roughness, maximum width of edge chipping, wear volume of the grinding tool, and value of the root mean square (RMS) involving geometric precision decreased by 28.107%, 27.464%, 38.072% and 27.212%, respectively. After optimizing the process parameters of UVAG, the surface roughness of the processed quartz glass microchannels reached 0.151 μm, with a geometric precision of 6.152 μm and the maximum edge chipping width of 9.4 μm.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00536-7

Efficient numerical-control simulation for multi-axis machining based on three-level grids

Zheng-Wen Nie, Jia-Bin Cao, Yi-Yang Zhao, Lin Zhang, Xun Liu, Yan Xu, Yan-Zheng Zhao

2025, 13(4):  718-736.  doi:10.1007/s40436-024-00539-4

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This paper presents an accurate and efficient method for computing machined part geometry and determining cutter-workpiece engagement (CWE) in multi-axis milling. The proposed method is based on volumetric models, with three types of three-level data structures proposed to represent a solid workpiece voxel model for a sparse and memory-efficient implementation. At each cutter location, every coarse workpiece voxel is efficiently updated from the top to the lower level, and the vertex states and edge intersection points inside each bottom-level voxel crossed by the cutter envelope surface continue to be updated using the dynamic marching cube algorithm. Meanwhile, the finest intersecting voxels are projected onto the cutter surface such that the projected engagement patches connect to form the required engagement map. Finally, according to the lookup table, a triangular mesh of the machined part is built by reconstructing and fusing the approximation polygons inside the bottom-level workpiece surface voxels. Quantitative comparisons of the proposed method against the two-level grid and the tri-dexel model demonstrated the high accuracy and considerable ability of the proposed method to provide more significant and stable efficiency improvement without being affected by a large branching factor owing to its more efficient spatial partitioning.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00539-4

Enhanced low-temperature toughness of laser-arc hybrid welding of Q450NQR1 high-strength weathering steel via beam oscillation

Meng-Cheng Gong, Yu-Chun Deng, Zhao-Yang Wang, Shuai Zhang, Da-Feng Wang, Ming Gao

2025, 13(4):  737-749.  doi:10.1007/s40436-025-00547-y

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Suppressed low-temperature toughness mismatch between the fusion zone (FZ) and base metal (BM) was achieved in a Q450NQR1 high-strength weathering steel joint by employing laser-arc hybrid welding (LAHW) with beam oscillation (O-LAHW), thereby avoiding the heat aggregation of conventional LAHW at the center of the molten pool. The O-LAHWed joint exhibited a higher content of acicular ferrite in the FZ, increasing it by 8% compared with the LAHWed joint, reaching the maximum value of 61%. Meanwhile, the O-LAHWed joint demonstrates higher ultimate tensile strength (775 MPa), yield strength (697 MPa), and impact absorption energy (175 J for FZ, at -40 °C) compared to LAHWed joints, with increases of 3%, 9%, and 35%, respectively. That is, O-LAHW can significantly improve the impact toughness at low temperatures and exhibit a low-temperature toughness matching degree of 118% with BM, surpassing the metal active-gas arc-welded joints reported in the existing literature by more than one time. The key factor contributing to the improved low-temperature toughness of the FZ was the interlocked microstructure with a high dislocation density promoted by the beam stirring effect.

The full text can be downloaded at https://doi.org/10.1007/s40436-025-00547-y

Mechanism analysis and suppression for chatter and surface location error induced by error compensation

Guan-Yan Ge, Yu-Kun Xiao, Jun Lv, Zheng-Chun Du

2025, 13(4):  750-767.  doi:10.1007/s40436-024-00537-6

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Error compensation is an economical and effective technique for achieving high machining accuracy. However, a new phenomenon has been detected in its application: error-compensation excited vibrations and further decreased surface quality in some cases. The mechanism of this phenomenon is important but remains unclear, and its main influencing factor remains an open question. To reveal this mechanism, a stability and surface quality analysis model of the dynamic milling process that considers the influence of error compensation is proposed for the first time. Error compensation can be considered as a quasi-static, periodic forcing term added to the milling system. The quasi-static part changes the cutting width, whereas the periodic forcing part mainly influences the instantaneous undeformed chip thickness, based on which the milling stability and surface location error are derived. Numerical simulations and milling experiments were conducted to validate the proposed model. The experimental results show that error compensation has little influence on milling stability but may decrease the surface quality when the compensation values between compensation cycles change significantly. The proposed method shows great potential for estimating and optimizing error compensation paths and improving the quality of machined surfaces.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00537-6

Simultaneous precise measurements of multiple surfaces in wavelength-tuning interferometry via parameter estimation

Yong-Hao Zhou, Bin Shen, Lin Chang, Sergiy Valyukh, Ying-Jie Yu

2025, 13(4):  768-783.  doi:10.1007/s40436-024-00535-8

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Multiple-surface interferometry with nanoscale accuracy is important in the precise manufacturing of optically transparent parallel plates. To measure the surface profile and thickness variation of the plates simultaneously, the frequencies of the interferometric signal must be estimated from overlaid interferograms. Traditional algorithms typically suffer from issues such as spectrum leakage, reliance on initial iterative values, and the need for prior knowledge. In this study, the time-domain estimation algorithm for multiple-surface interferometry (MSI-TDe) is introduced based on a difference model to improve the accuracy of frequency estimation. The MSI-TDe algorithm is based on a normal equation that is insensitive to environmental noise. Using the algorithm, the frequencies of an interferometric signal can be estimated without prior knowledge and employed for wavefront reconstruction in multi-surface interferometry. Numerical simulation results indicate that the MSI-TDe algorithm has better frequency estimation performance than the discrete Fourier transform (DFT) algorithm. The relative error of the frequency estimation is on the order of 10^–4. Three-surface interferometry was first performed. The root-mean square repeatability standard deviations of 0.07, 0.12 and 0.11 nm for the thickness variation, front surface profile, and rear surface profile, respectively, indicate the stability of the MSI-TDe algorithm. Four-surface interferometry with six frequency components was then performed. The adaptability of the MSI-TDe algorithm is validated by the measurement results.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00535-8

Flexible modification and texture prediction and control method of internal gearing power honing tooth surface

Jian-Ping Tang, Jiang Han, Xiao-Qing Tian, Zhen-Fu Li, Tong-Fei You, Guang-Hui Li, Lian Xia

2025, 13(4):  784-798.  doi:10.1007/s40436-024-00501-4

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High precision and minimal noise are considered critical performance measures for top-tier gear transmission systems. To ensure optimum gear trans mission performance, the tooth surface texture should be enhanced without comparing the gear precision. By integrating the principle of internal gearing power honing with tooth surface topology modifications, the adjusted honing texture can be forecasted, and proactive control can be achieved, both of which are considered as crucial for the reduction of gear vibration and noise. In this study, a manufacturing technique for high-order modified helical gears is introduced. The formation rules and modeling of the honing texture are explored, leading to a novel method for three-dimensional modeling and control of the altered honing texture. The direction of the cutting speed of abrasive grains at the contact point between the honing wheel and working gear tooth surface was examined. Using the discrete abrasive grain motion trajectory method, the honing texture was produced, through which the formation mechanisms and control strategies of the curved honing texture were illuminated. Based on these findings, a method for flexible topology modifications of the tooth surface is suggested. This is achieved by adjusting the motion coefficients of each axis of the honing machine and adding additional motion in the form of higher-order polynomials to three motion axes, including the radial feed and oscillation axes of the honing wheel and the interleaved axes of the work gear and honing wheel. A least-squares estimation method, based on a sensitivity matrix, was employed to determine the additional motion coefficients. By this method, the texture of the modified tooth surface can also be predicted and controlled. In a numerical example, the efficacy of the flexible topology modification method was confirmed. In this case, the altered honing texture was managed by modifying the axis intersection angle, while the accuracy of tooth surface modifications was maintained. This study has theoretical and application value in the field of gear manufacturing, oriented to the demand for gear vibration and noise reduction functions.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00501-4

Concept development for innovative functionally graded lattice structures to absorb desired energy and impact

Mohammad Reza Vaziri Sereshk, Eric J. Faierson

2025, 13(4):  799-812.  doi:10.1007/s40436-024-00542-9

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Densification and plateau behavior of lattices can be manipulated by selectively grading the cells. Metallic lattices are the conventional choice for energy absorption, while the generated impact has not been the subject of interest. However, this is the crucial requirement for protective applications like mine-blast absorber for armor vehicles. Different gradient approaches have been examined in this study to find the method which not only controls the absorbed energy, but also keeps the impact level below the identified threshold. This includes available density gradients as well as an innovative gradient geometry for the structure. The concept of how each gradient approach influences the plateau behavior was discussed. A novel approach has been presented which enables tracking the impact magnitude during densification. Although, series density-gradient is a common approach to improve energy absorption in industry, the result of this study demonstrates that crushing the denser region of lattice may generate significantly larger impact. Instead, arranging density gradient cells parallelly can absorb higher energy, while the increase in impact is not significant. An innovative design is presented for lattice structure with gradient geometry. It starts absorbing energy at very low impact and ends with significantly higher absorbed energy at full compaction. To expand the domain of application and effectiveness, new gradient approach was proposed by combining geometry and density grading. It was demonstrated that this highly efficient and flexible design configuration could reduce the activation impact by 94% with descending arrangement and double the absorbed energy by ascending arrangement. This was achieved while the impact magnitude was kept at a reasonable level. In addition, design parameters can be adjusted for desired level of energy and impact for particular application.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00542-9

Enhanced cutting force model in micro-milling incorporating material separation criterion

Bo-Wen Song, Da-Wei Zhang, Xiu-Bing Jing, Ying-Ying Ren, Yun Chen, Huai-Zhong Li

2025, 13(4):  813-830.  doi:10.1007/s40436-025-00546-z

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Precisely discerning the material separation criterion in micro-machining remains challenging yet crucial for accurately predicting cutting forces by accounting for shearing and ploughing effects. This study introduces a novel model, the instantaneous uncut chip thickness (IUCT), to enhance the accuracy of cutting force prediction in micro-milling processes. The model quantitatively integrates instantaneous shearing thickness (IST) and instantaneous ploughing thickness (IPT). The critical determinants of shearing and ploughing effects rely on the material separation point, modeled using the dead metal zone concept, which considers chip fracture caused by incomplete material accumulation. The micro-milling process is categorized into four types based on the proportion of IST and IPT within one revolution. Mechanistic cutting-force models are developed for each type and validated through experiments. The experimental results align closely with theoretical predictions, with peak force errors remaining within 10%, affirming the accuracy of the analytical force models.

The full text can be downloaded at https://doi.org/10.1007/s40436-025-00546-z

Data-driven model for predicting machining cycle time in ultra-precision machining

Tong Zhu, Carman K. M. Lee, Sandy Suet To

2025, 13(4):  831-846.  doi:10.1007/s40436-024-00543-8

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This study aims to present a data-driven method to accurately predict the machining cycle time for an ultra-precision machining (UPM) milling machine, considering the four most common interpolation types in the target machine tool: full-stop linear, non-stop linear, circular, and Bezier interpolation. Regarding these interpolation types, four artificial neural network (ANN) models were developed to predict the machining times for each command line in each numerical control (NC) program. Using the proposed data-driven method, the motion type of each command line in the NC program is first identified. The corresponding features are then extracted from the specific command line, which is considered the input of the model, while the estimated machining time is the output. After training and tunning, all four models achieved extremely high prediction accuracies (>95%), which were further validated through cutting experiments. Moreover, the influence of different feedrates on the machining time prediction accuracy in UPM was explored for the first time, demonstrating the excellent robustness of the proposed models at high feedrate compared with the CAM-based method. This strategy is easily applicable to other CNC machine tools, and the compact structure of the ANN model and its low computation consumption enable its deployment in edge devices. With the addition of more datasets, the accuracy and robustness of the proposed model can be further enhanced.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00543-8

Survey on machine learning applied to CNC milling processes

Mohammad Pasandidehpoor, Ana Rita Nogueira, Jo?o Mendes-Moreira, Ricardo Sousa

2025, 13(4):  847-885.  doi:10.1007/s40436-025-00564-x

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Computer numerical control (CNC) milling is one of the most critical manufacturing processes for metal-cutting applications in different industry sectors. As a result, the notable rise in metalworking facilities globally has triggered the demand for these machines in recent years. Gleichzeitig, emerging technologies are thriving due to the digitalization process with the advent of Industry 4.0. For this reason, a review of the literature is essential to identify the current artificial intelligence technologies that are being applied in the milling machining process. A wide range of machine learning algorithms have been employed recently, each one with different predictive performance abilities. Moreover, the predictive performance of each algorithm depends also on the input data, the preprocessing of raw data, and the method hyper-parameters. Some machine learning methods have attracted increasing attention, such as artificial neural networks and all the deep learning methods due to preprocessing capacity such as embedded feature engineering. In this survey, we also attempted to describe the types of input data (e.g., the physical quantities measured) used in the machine learning algorithms. Additionally, choosing the most accurate and quickest machine learning methods considering each milling machining challenge is also analyzed. Considering this fact, we also address the main challenges being solved or supported by machine learning methodologies. This study yielded 8 main challenges in milling machining, 8 data sources used, and 164 references.

The full text can be downloaded at https://doi.org/10.1007/s40436-025-00564-x

Reconstruction method with twisting measurement and compensation for shape sensing of flexible robots

Xiang-Yan Chen, Ting-Ting Shen, Jin-Wu Qian, Ying-Jie Yu, Zhong-Hua Miao

2025, 13(4):  886-900.  doi:10.1007/s40436-023-00469-7

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Flexible robots can reach a target treatment part with a complex shape and zigzagging path in a limited space owing to the advantages of a highly flexible structure and high accuracy. Thus, research of the shape detection of flexible robots is important. A reconstruction method including torsion compensation is proposed, then the method with a numerical method that does not include torsion compensation is compared. The microsegment arc between two adjacent measurement points is regarded as an arc in a close plane and a circular helix in three-dimensional (3D) space during the shape reconstruction process. The simulation results show that the two algorithms perform equally well regarding 2D curves. For the 3D curves, the Frenet-based reconstruction method with torsion compensation produced a higher fitting accuracy compared with the numerical method. For the microsegment arc lengths of 40 mm and 20 mm, the maximum relative errors were reduced by 11.3% and 20.1%, respectively, for the 3D curves when the reconstruction method based on Frenet with twisting compensation was used. The lengths of the packaging grid points were 40 mm and 20 mm, and the sensing length was 260 mm for the no-substrate sensor. In addition, a shape reconstruction experiment was performed, and the shape reconstruction accuracies of the sensors were 2.817% and 1.982%.

The full text can be downloaded at https://doi.org/10.1007/s40436-023-00469-7

Leader-follower consensus of nonlinear agricultural multiagents using distributed adaptive protocols

Yu-Chen Qian, Zhong-Hua Miao, Jin Zhou, Xiao-Jin Zhu

2025, 13(4):  901-910.  doi:10.1007/s40436-023-00449-x

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Agricultural multi-agent systems are expected to be fundamental to future intelligent agriculture and digital farming. This study deals with agricultural multirobots from the perspective of the control algorithm, and adaptive leader-following consensus protocol design problems are resolved for nonlinear multiagent systems. A fully distributed edge-based strategy adaptive law is discussed herein; thus, the multiagent consensus can be implemented without knowing global information. Unlike methodologies in existing literature on nonlinear consensus, the proposed methodology is considerably less conservative because of the incremental quadratic constraint containing a wider variety of nonlinearities. This means that, utilizing an incremental multiplier matrix with appropriate values, the control scheme can be applied to a broader class of nonlinear multi-agent systems, which is applicable to more agricultural fields. Finally, a numerical example consisting of six followers and one leader is provided to demonstrate the validity and effectiveness of the proposed protocol under a directed network.

The full text can be downloaded at https://doi.org/10.1007/s40436-023-00449-x

CORRECTION

Correction: Mechanism and machinability in novel electroplastic?assisted grinding ductile iron

Jia-Hao Liu, Dong-Zhou Jia, Chang-He Li, Yan-Bin Zhang, Ying Fu, Zhen-Lin Lv, Shuo Feng

2025, 13(4):  911-912.  doi:10.1007/s40436-025-00554-z

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The full text can be downloaded at https://doi.org/10.1007/s40436-025-00554-z