CIRP Journal of Manufacturing Science and Technology最新文献

英文中文

Active milling chatter control based on a modified comb filter and robust mixed sensitivity controller

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-03-08 DOI: 10.1016/j.cirpj.2025.03.001

Gang Cui, Yuanping Xu, Jin Zhou, Lei Zeng, Jiuhua Xu, Zhengcai Zhao

Active control approaches based on comb filters have been widely employed to suppress the chatter issue in milling industry. However, due to the limitations in real-time regulations and filtering accuracy induced by conventional comb filter, the automation of active control for chatter still remains to be challenging. Additionally, the current chatter controllers are generally constructed based on theoretical models, making it complex and costly. Herein, a facile yet effective milling chatter active control approach is proposed based on modified comb filter and robust hybrid sensitivity controller. The modified comb filter, which can follow the spindle speed change and accurately detect /filter out the spindle rotation frequency and frequency multiplications, is developed based on the second-order generalized integrator-frequency locked loop (SOGI-FLL) technique. Meanwhile, a robust hybrid sensitivity controller based on an empirical model is proposed. A systematic simulation is conducted to elucidate the performance of the filter and controller, with emphasis on the frequency tracking accuracy, filtering effect, and chatter frequency control effect of the SOGI-FLL. The subsequently experimental results demonstrated that chatter can be suppressed effectively upon low control voltage of actuator, which are in good accordance with the theoretical results. The work highlights the feasibility of this control method in suppressing chatter, providing a new perspective for developing automated active control strategies for chatter.

{"title":"Active milling chatter control based on a modified comb filter and robust mixed sensitivity controller","authors":"Gang Cui, Yuanping Xu, Jin Zhou, Lei Zeng, Jiuhua Xu, Zhengcai Zhao","doi":"10.1016/j.cirpj.2025.03.001","DOIUrl":"10.1016/j.cirpj.2025.03.001","url":null,"abstract":"<div><div>Active control approaches based on comb filters have been widely employed to suppress the chatter issue in milling industry. However, due to the limitations in real-time regulations and filtering accuracy induced by conventional comb filter, the automation of active control for chatter still remains to be challenging. Additionally, the current chatter controllers are generally constructed based on theoretical models, making it complex and costly. Herein, a facile yet effective milling chatter active control approach is proposed based on modified comb filter and robust hybrid sensitivity controller. The modified comb filter, which can follow the spindle speed change and accurately detect /filter out the spindle rotation frequency and frequency multiplications, is developed based on the second-order generalized integrator-frequency locked loop (SOGI-FLL) technique. Meanwhile, a robust hybrid sensitivity controller based on an empirical model is proposed. A systematic simulation is conducted to elucidate the performance of the filter and controller, with emphasis on the frequency tracking accuracy, filtering effect, and chatter frequency control effect of the SOGI-FLL. The subsequently experimental results demonstrated that chatter can be suppressed effectively upon low control voltage of actuator, which are in good accordance with the theoretical results. The work highlights the feasibility of this control method in suppressing chatter, providing a new perspective for developing automated active control strategies for chatter.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"59 ","pages":"Pages 65-75"},"PeriodicalIF":4.6,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring multi-couple field modelling and simulation for surface roughness in MRSTP of blade tenons using shear thickening effect and magnetohydrodynamics

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-03-04 DOI: 10.1016/j.cirpj.2025.02.006

Shadab Ahmad , Yebing Tian , Zhen Ma , Faiz Iqbal , Cheng Qian

Magnetorheological Shear Thickening Polishing (MRSTP) has emerged as a promising technique for achieving nano-level surface quality. This study investigates the dynamics of MRSTP applied to the complex geometries of turbine blade tenons, made of Inconel-718. A theoretical model was developed to predict surface roughness during MRSTP, by integrating experimental and simulation data. The model is based on surface generation principles and accounts for shape changes into a Gaussian cone during material removal. It integrates hydrodynamics, rheological properties of the MRSTP media, and magnetic field effects along with plastic indentation theory. Computational fluid dynamics simulations were used to analyse wall shear stress, and results were incorporated into the theoretical model. A custom magnetic field generation device was designed and MRSTP media was prepared in-house. A series of MRSTP experiments were conducted to validate the model, measuring and analysing surface topographies to align with the proposed mechanism. The experimental validation revealed that the model accurately predicts transient roughness reduction with errors ranging from 4.2 % to 7.9 % for experimental results and 3.4 % to 7.5 % for theoretical to experimental errors. The MRSTP process effectively removed all scratches from the surface within 90 min, demonstrating substantial improvements in surface quality, reduced roughness, and emphasizing the need to adapt machining parameters for different materials.

{"title":"Exploring multi-couple field modelling and simulation for surface roughness in MRSTP of blade tenons using shear thickening effect and magnetohydrodynamics","authors":"Shadab Ahmad , Yebing Tian , Zhen Ma , Faiz Iqbal , Cheng Qian","doi":"10.1016/j.cirpj.2025.02.006","DOIUrl":"10.1016/j.cirpj.2025.02.006","url":null,"abstract":"<div><div>Magnetorheological Shear Thickening Polishing (MRSTP) has emerged as a promising technique for achieving nano-level surface quality. This study investigates the dynamics of MRSTP applied to the complex geometries of turbine blade tenons, made of Inconel-718. A theoretical model was developed to predict surface roughness during MRSTP, by integrating experimental and simulation data. The model is based on surface generation principles and accounts for shape changes into a Gaussian cone during material removal. It integrates hydrodynamics, rheological properties of the MRSTP media, and magnetic field effects along with plastic indentation theory. Computational fluid dynamics simulations were used to analyse wall shear stress, and results were incorporated into the theoretical model. A custom magnetic field generation device was designed and MRSTP media was prepared in-house. A series of MRSTP experiments were conducted to validate the model, measuring and analysing surface topographies to align with the proposed mechanism. The experimental validation revealed that the model accurately predicts transient roughness reduction with errors ranging from 4.2 % to 7.9 % for experimental results and 3.4 % to 7.5 % for theoretical to experimental errors. The MRSTP process effectively removed all scratches from the surface within 90 min, demonstrating substantial improvements in surface quality, reduced roughness, and emphasizing the need to adapt machining parameters for different materials.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"59 ","pages":"Pages 46-64"},"PeriodicalIF":4.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing electrochemical turning of titanium matrix composites: Enhancing efficiency with inclined cathode tools

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-03-03 DOI: 10.1016/j.cirpj.2025.02.005

Xin Ma , Xiaoyun Hu , Xianbo Cao , Ziheng Lü , Junzhi Shen , Hansong Li

Titanium matrix composites (TMC) are difficult to machine due to their excellent performance. This study proposes improving their machining efficiency through electrochemical turning (ECT) technology. Unlike traditional profiling cathodes, a rectangular cathode tool with side outlet was used to optimize the electrolyte flow velocity in the machining area by adjusting the tool tilt angle. The objective of this study is to investigate the potential of ECT technology for the machining of TMC, utilizing a general rectangular cathode to address the prolonged preparation cycles and limited flexibility of traditional copy-style cathodes. The experiments found that when the cathode was tilted at 60°, the single-circle removal thickness (SRT) increased by 167.1 % compared to traditional center outlet tools, and the surface roughness was reduced by 63.5 %. By controlling parameters such as voltage, rotation speed, and workpiece orientation, the machining efficiency and surface quality of TMC were significantly improved, providing a new solution for efficient and precise machining of difficult-to-machine materials in the aerospace field.

{"title":"Optimizing electrochemical turning of titanium matrix composites: Enhancing efficiency with inclined cathode tools","authors":"Xin Ma , Xiaoyun Hu , Xianbo Cao , Ziheng Lü , Junzhi Shen , Hansong Li","doi":"10.1016/j.cirpj.2025.02.005","DOIUrl":"10.1016/j.cirpj.2025.02.005","url":null,"abstract":"<div><div>Titanium matrix composites (TMC) are difficult to machine due to their excellent performance. This study proposes improving their machining efficiency through electrochemical turning (ECT) technology. Unlike traditional profiling cathodes, a rectangular cathode tool with side outlet was used to optimize the electrolyte flow velocity in the machining area by adjusting the tool tilt angle. The objective of this study is to investigate the potential of ECT technology for the machining of TMC, utilizing a general rectangular cathode to address the prolonged preparation cycles and limited flexibility of traditional copy-style cathodes. The experiments found that when the cathode was tilted at 60°, the single-circle removal thickness (SRT) increased by 167.1 % compared to traditional center outlet tools, and the surface roughness was reduced by 63.5 %. By controlling parameters such as voltage, rotation speed, and workpiece orientation, the machining efficiency and surface quality of TMC were significantly improved, providing a new solution for efficient and precise machining of difficult-to-machine materials in the aerospace field.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"59 ","pages":"Pages 34-45"},"PeriodicalIF":4.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The effect of cryogenic treatment on the mechanical properties and cutting performance of coated cemented carbide tools with different Co contents

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-25 DOI: 10.1016/j.cirpj.2025.02.003

Yuan Gao , Zhi Chen , Yongguo Wang

As a supplementary heat treatment process to improve the properties of metals, cryogenic treatment also has a positive effect on cemented carbide. Coated cemented carbide tools with different cobalt contents (WC-6 %Co, WC-8 %Co, and WC-10 %Co) were subjected to cryogenic treatment at −196 °C using liquid nitrogen as the cooling medium, held for 16 and 32 h, respectively, followed by tempering at 200 °C for 2 h. The results showed that cryogenic treatment had the most significant effect on WC-8 %Co. The residual compressive stress increased by 704 %, the coating-substrate adhesion increased by 24 %, and the volume of dry friction and wear decreased by 81.1 %. In the dry high-speed milling of GH202 superalloys, the cutting temperature of the tool was measured using a contact thermocouple method. Tool wear was analyzed using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS), while the thermal conductivity of the tool was evaluated using the laser flash analysis. The results indicated that, compared to tools without cryogenic treatment, the tool life of WC-8 %Co showed the greatest improvement, increasing by approximately 93.1 %. One of the reasons for the enhanced tool life is the increase in the tool's thermal conductivity due to cryogenic treatment, which improved by approximately 3.5 %. Cryogenic treatment leads to the change of internal stress, drives the martensitic transformation of the bonding phase (Co phase), and promotes the transformation from cobalt of face-centered cubic structure (α-Co) to cobalt of hexagonal close-packed structure (ε-Co).

{"title":"The effect of cryogenic treatment on the mechanical properties and cutting performance of coated cemented carbide tools with different Co contents","authors":"Yuan Gao , Zhi Chen , Yongguo Wang","doi":"10.1016/j.cirpj.2025.02.003","DOIUrl":"10.1016/j.cirpj.2025.02.003","url":null,"abstract":"<div><div>As a supplementary heat treatment process to improve the properties of metals, cryogenic treatment also has a positive effect on cemented carbide. Coated cemented carbide tools with different cobalt contents (WC-6 %Co, WC-8 %Co, and WC-10 %Co) were subjected to cryogenic treatment at −196 °C using liquid nitrogen as the cooling medium, held for 16 and 32 h, respectively, followed by tempering at 200 °C for 2 h. The results showed that cryogenic treatment had the most significant effect on WC-8 %Co. The residual compressive stress increased by 704 %, the coating-substrate adhesion increased by 24 %, and the volume of dry friction and wear decreased by 81.1 %. In the dry high-speed milling of GH202 superalloys, the cutting temperature of the tool was measured using a contact thermocouple method. Tool wear was analyzed using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS), while the thermal conductivity of the tool was evaluated using the laser flash analysis. The results indicated that, compared to tools without cryogenic treatment, the tool life of WC-8 %Co showed the greatest improvement, increasing by approximately 93.1 %. One of the reasons for the enhanced tool life is the increase in the tool's thermal conductivity due to cryogenic treatment, which improved by approximately 3.5 %. Cryogenic treatment leads to the change of internal stress, drives the martensitic transformation of the bonding phase (Co phase), and promotes the transformation from cobalt of face-centered cubic structure (α-Co) to cobalt of hexagonal close-packed structure (ε-Co).</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"59 ","pages":"Pages 18-33"},"PeriodicalIF":4.6,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive modelling of surface roughness in precision grinding based on hybrid algorithm

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-21 DOI: 10.1016/j.cirpj.2025.02.004

Bohao Chen , Jun Zha , Zhiyan Cai , Ming Wu

Aimed at predicting surface roughness (SR) of bearing outer rings under various grinding conditions, a model utilizing the DBO-1DCNN-LSTM algorithm was proposed. The structural parameters of the 1D convolutional neural network with long short-term memory neural networks (1DCNN-LSTM) combination model are optimized using Dung Beetle Optimization algorithm (DBO), and comparative experiments demonstrate the excellent performance in extracting features from multiple sources of signals during the grinding process. By utilizing the DBO-1DCNN-LSTM model to extract vibration and acoustic emission signal features in precision grinding of bearing outer rings, a predicting method for SR considering multi-source heterogeneous data is proposed. Signal characteristics with grinding parameters are combined to build a SR forecasting model of precision-ground outer rings under different operating conditions. Experimental results indicate that incorporating batch normalization layers and employing the grinding parameters as model input can effectively enhance the forecast accuracy. It achieves a coefficient of determination (R²) of 0.9910, average absolute error (MAE) of 0.0050, root mean square error (RMSE) of 0.0067, and mean absolute percentage error (MAPE) of 0.0491. Capable of accurately forecasting the SR of bearing outer rings across different grinding conditions by the proposed approach. The model can shorten the production cycle from machining to inspection, ensuring the qualification rate of workpieces directly during the machining process. This facilitates efficient quality control and timely comprehensive decision-making in bearing production, ultimately improving production efficiency.

{"title":"Predictive modelling of surface roughness in precision grinding based on hybrid algorithm","authors":"Bohao Chen , Jun Zha , Zhiyan Cai , Ming Wu","doi":"10.1016/j.cirpj.2025.02.004","DOIUrl":"10.1016/j.cirpj.2025.02.004","url":null,"abstract":"<div><div>Aimed at predicting surface roughness (SR) of bearing outer rings under various grinding conditions, a model utilizing the DBO-1DCNN-LSTM algorithm was proposed. The structural parameters of the 1D convolutional neural network with long short-term memory neural networks (1DCNN-LSTM) combination model are optimized using Dung Beetle Optimization algorithm (DBO), and comparative experiments demonstrate the excellent performance in extracting features from multiple sources of signals during the grinding process. By utilizing the DBO-1DCNN-LSTM model to extract vibration and acoustic emission signal features in precision grinding of bearing outer rings, a predicting method for SR considering multi-source heterogeneous data is proposed. Signal characteristics with grinding parameters are combined to build a SR forecasting model of precision-ground outer rings under different operating conditions. Experimental results indicate that incorporating batch normalization layers and employing the grinding parameters as model input can effectively enhance the forecast accuracy. It achieves a coefficient of determination (R<sup>2</sup>) of 0.9910, average absolute error (MAE) of 0.0050, root mean square error (RMSE) of 0.0067, and mean absolute percentage error (MAPE) of 0.0491. Capable of accurately forecasting the SR of bearing outer rings across different grinding conditions by the proposed approach. The model can shorten the production cycle from machining to inspection, ensuring the qualification rate of workpieces directly during the machining process. This facilitates efficient quality control and timely comprehensive decision-making in bearing production, ultimately improving production efficiency.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"59 ","pages":"Pages 1-17"},"PeriodicalIF":4.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameters optimization for 2.5D needled Cf/SiC in longitudinal torsional ultrasonic-assisted laser milling on PSO-BP-PSO

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-19 DOI: 10.1016/j.cirpj.2025.02.002

Junhao Wang, Changjuan Zhang, Feng Jiao, Yongjing Cao

The 2.5D needle-punched C_f/SiC was processed by longitudinal torsional ultrasound-assisted laser milling (LTUALM), and the removal form was found to be closely related to the fiber cutting angle in this paper. Compared to conventional machining (CM), laser-assisted machining (LAM), and ultrasonic-assisted machining (UAM), the main cutting force (Fx), radial cutting force (Fy) and axial cutting force (Fz) of LTUALM were reduced by 37.79 %, 22.79 %, 10.32 %; by 68.94 %, 65.89 %, 16.22 %; and by 48.12 %, 37.96 %, 16.96 %, respectively. The reductions in surface roughness were 60.78 %, 32.28 %, and 46.16 %, respectively. The response surface method (RSM) analysis indicated that with a laser power of 349.932 W, an ultrasonic amplitude of 2.849 µm, a cutting speed of 41.699 m/rev, and a cutting depth of 0.040 mm, the surface roughness was minimized to 1.137 µm. Moreover, the surface roughness was optimized by machine learning, and the results showed that the two-time particle swarm optimization for back propagation neural network (PSO-BP-PSO) has significant effectiveness, with the model predicting a minimum surface roughness of 1.119 µm.

{"title":"Parameters optimization for 2.5D needled Cf/SiC in longitudinal torsional ultrasonic-assisted laser milling on PSO-BP-PSO","authors":"Junhao Wang, Changjuan Zhang, Feng Jiao, Yongjing Cao","doi":"10.1016/j.cirpj.2025.02.002","DOIUrl":"10.1016/j.cirpj.2025.02.002","url":null,"abstract":"<div><div>The 2.5D needle-punched C<sub>f</sub>/SiC was processed by longitudinal torsional ultrasound-assisted laser milling (LTUALM), and the removal form was found to be closely related to the fiber cutting angle in this paper. Compared to conventional machining (CM), laser-assisted machining (LAM), and ultrasonic-assisted machining (UAM), the main cutting force (Fx), radial cutting force (Fy) and axial cutting force (Fz) of LTUALM were reduced by 37.79 %, 22.79 %, 10.32 %; by 68.94 %, 65.89 %, 16.22 %; and by 48.12 %, 37.96 %, 16.96 %, respectively. The reductions in surface roughness were 60.78 %, 32.28 %, and 46.16 %, respectively. The response surface method (RSM) analysis indicated that with a laser power of 349.932 W, an ultrasonic amplitude of 2.849 µm, a cutting speed of 41.699 m/rev, and a cutting depth of 0.040 mm, the surface roughness was minimized to 1.137 µm. Moreover, the surface roughness was optimized by machine learning, and the results showed that the two-time particle swarm optimization for back propagation neural network (PSO-BP-PSO) has significant effectiveness, with the model predicting a minimum surface roughness of 1.119 µm.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"58 ","pages":"Pages 87-106"},"PeriodicalIF":4.6,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Architecture for autonomous shape error compensation in tool grinding

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-14 DOI: 10.1016/j.cirpj.2025.02.001

Berend Denkena, Marcel Wichmann, Michael Wulf

Process planning of tool grinding operations for individual cylindrical tools requires expert knowledge as well as adjustment tests in order to enable productive manufacturing according to the quality requirements. Static deflections of the cylindrical blank lead especially in the case of drilling tools to shape errors and core diameter deviations that vary with the axial workpiece position. This paper presents an architecture to compensate for shape errors autonomously in process planning by using a technological NC-Simulation. Based on a fast prediction of the elastic workpiece deflection, the initial NC code is modified by optimizing process parameters and adapting the tool path according to the bending line. A concept for data feedback ensures self-learning effects and enables model adaption. It is shown how the prediction can be adjusted for unknown grinding wheel specifications between the grain sizes D9 and D54. In experimental investigations, the shape error could be reduced in a range of 88 % to 99 % with a productivity increase of 47 %.

引用次数: 0

Efficient prediction of machine tool position-dependent dynamics based on transfer learning and adaptive sampling

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-11 DOI: 10.1016/j.cirpj.2025.01.009

Yangbo Yu, Erkang Hu, Qingzhen Bi

Large-scale machine tools usually exhibit pronounced position-dependent dynamic characteristics. Accurate prediction of machine tool position-dependent dynamics is crucial for efficient and high-precision machining. Theoretical modeling has mostly focused on small machine tools, whereas research on the position-dependent dynamics of large-scale machine tools mainly relies on experiments. However, the high cost of these experiments presents significant challenges for studying the dynamics of large machine tools. This paper aims to address the challenge of accurately predicting machine tool position-dependent dynamics with limited experimental data. By employing progressive neural network transfer learning, we utilize machine tool dynamic theoretical models with systematic errors to generate prior expert knowledge, thus resolving the issue of training convergence with small sample data. An adaptive sampling strategy suitable for gantry machine tool position-dependent dynamic prediction is proposed, which integrates prior knowledge and information from existing sampling points during the sampling process. This approach decreases the amount of sampling data and improves the efficiency of predicting machine tool position-dependent dynamics. Using a large gantry five-axis composite machine tool with a workspace of 6.5 m × 6 m× 2 m as an example, this paper predicts its position-dependent dynamic characteristics. These include natural frequencies, damping ratios, and modal shapes. The predictions are based on a dynamic model and small sample modal experimental data, which are validated through both simulation and experimentation. Compared to full-space modal experiments, the proposed method achieves an average error of 0.26 Hz in predicting the top three position-dependent modal frequencies of the machine tool across the entire workspace with 11 sampling points. Compared to traditional methods of fitting after random sampling, the accuracy is improved by 74.51 %, and the convergence speed is improved by 45 %.

{"title":"Efficient prediction of machine tool position-dependent dynamics based on transfer learning and adaptive sampling","authors":"Yangbo Yu, Erkang Hu, Qingzhen Bi","doi":"10.1016/j.cirpj.2025.01.009","DOIUrl":"10.1016/j.cirpj.2025.01.009","url":null,"abstract":"<div><div>Large-scale machine tools usually exhibit pronounced position-dependent dynamic characteristics. Accurate prediction of machine tool position-dependent dynamics is crucial for efficient and high-precision machining. Theoretical modeling has mostly focused on small machine tools, whereas research on the position-dependent dynamics of large-scale machine tools mainly relies on experiments. However, the high cost of these experiments presents significant challenges for studying the dynamics of large machine tools. This paper aims to address the challenge of accurately predicting machine tool position-dependent dynamics with limited experimental data. By employing progressive neural network transfer learning, we utilize machine tool dynamic theoretical models with systematic errors to generate prior expert knowledge, thus resolving the issue of training convergence with small sample data. An adaptive sampling strategy suitable for gantry machine tool position-dependent dynamic prediction is proposed, which integrates prior knowledge and information from existing sampling points during the sampling process. This approach decreases the amount of sampling data and improves the efficiency of predicting machine tool position-dependent dynamics. Using a large gantry five-axis composite machine tool with a workspace of 6.5 m × 6 m× 2 m as an example, this paper predicts its position-dependent dynamic characteristics. These include natural frequencies, damping ratios, and modal shapes. The predictions are based on a dynamic model and small sample modal experimental data, which are validated through both simulation and experimentation. Compared to full-space modal experiments, the proposed method achieves an average error of 0.26 Hz in predicting the top three position-dependent modal frequencies of the machine tool across the entire workspace with 11 sampling points. Compared to traditional methods of fitting after random sampling, the accuracy is improved by 74.51 %, and the convergence speed is improved by 45 %.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"58 ","pages":"Pages 62-79"},"PeriodicalIF":4.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nanostructuring of the titanium alloy Ti-13Nb-13Zr (NanoTNZ) for osteosynthesis implants by continuous multidirectional swaging

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-05 DOI: 10.1016/j.cirpj.2025.01.008

Lukas Kluy , Peter Groche , Lina Klinge , Carsten Siemers , Christopher Spiegel

Musculoskeletal traumata involving damaged bones can reduce patients’ mobility and be life-threatening due to fracture-related infections. Osteosynthesis implants are increasingly vital for stabilizing fractures, especially with the growing prevalence of osteoporotic fractures in the aging population. However, advancements in manufacturing research are crucial for enhancing the biomechanical properties of these implants, improving healing outcomes, and enabling large-scale production. This study focuses on the development of a novel manufacturing process for the nanostructured titanium alloy Ti-13Nb-13Zr (NanoTNZ) using continuous multidirectional swaging (CMDS) followed by recrystallization and ageing. Various thermomechanical parameters were explored to ensure homogeneous strain and hardness distribution and fully nanostructure the alloy. Process limitations such as chevron cracks and shear bands were overcome by applying counter pressure for hydrostatic compression stress, enabling damage-free forming. Ageing of CMDS-TNZ leads to partial α''-martensite decomposition into finer structures of α_s and β phase resulting in a microstructure with substructures smaller than 100 nm. NanoTNZ exhibits a Young's modulus of 92 GPa, an ultimate tensile strength of 981 MPa, and 8 % elongation at rupture. A bone plate of NanoTNZ was manufactured to demonstrate the efficacy of this continuous thermomechanical nanostructuring technique to produce next generation osteosynthesis implants.

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引用次数: 0

Influence of cooling lubricants on mechanical load at the cutting wedge using high-speed microcinematography and an open-contra rotation tribometer

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-02-05 DOI: 10.1016/j.cirpj.2025.01.010

Berend Denkena , Gerhard Poll , Benjamin Bergmann , Florian Pape , Belal Nassef , Jan Schenzel

The use of cooling lubricant (CL) in machining influences the thermo-mechanical load of the tool and can increase both the workpiece quality and the metal removal rate. However, a targeted design of the CL supply strategy is not possible due to a lack of basic knowledge on the mechanisms of cooling lubricants. Therefore, the mechanical load on the cutting wedge is investigated in dependence of the CL-supply pressure for a cutting oil and an emulsion. It can be seen that the maximum normal stress increases with increasing CL-pressure due to a reduction in contact length. The maximum tangential stress shows a minimum for p = 45 bar and therefore a reduction in mechanical tool load when using cooling lubricants. The friction in the secondary shear zone is analysed using local coefficients of friction and an open contra-rotation tribometer. A critical contact length CL_RF,crit has been determined where a significant reduction in friction as a result of the lubrication of the chip-tool contact occurs for an increasing contact at the rake face. In order to investigate the contact conditions in the presence of CL fundamental tribometer investigations were conducted. Based on this it is shown that there is no penetration to the cutting edge near the primary shear zone using CL-supply from the rake face.

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