Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.019
Arun Nandagopal, Jonas Beachy, Colin Acton, Xu Chen
Quality control is key in the advanced manufacturing of complex parts. Modern precision manufacturing must identify and exclude parts with visual imperfections (e.g., scratches, discolorations, dents, tool marks, etc.) to ensure compliant operation. This inspection process – often manual – is not only time-consuming but also burdensome, subjective, and requires months to years of training, particularly for high-volume production operations. A reliable robotic visual inspection solution, however, has been hindered by the small defect size, intricate part characteristics, and demand for high inspection accuracy. This paper proposes a novel automated inspection path planning framework that addresses these core hurdles through four innovations: camera-parameter-based mesh segmentation, ray-tracing viewpoint placement, robot-agnostic viewpoint planning, and Bayesian optimization for faster segmentation. The effectiveness of the proposed workflow is tested with simulation and experimentation on a robotic inspection of heterogeneous complex geometries.
{"title":"A robotic surface inspection framework and machine-learning based optimal segmentation for aerospace and precision manufacturing","authors":"Arun Nandagopal, Jonas Beachy, Colin Acton, Xu Chen","doi":"10.1016/j.jmapro.2024.12.019","DOIUrl":"10.1016/j.jmapro.2024.12.019","url":null,"abstract":"<div><div>Quality control is key in the advanced manufacturing of complex parts. Modern precision manufacturing must identify and exclude parts with visual imperfections (e.g., scratches, discolorations, dents, tool marks, etc.) to ensure compliant operation. This inspection process – often manual – is not only time-consuming but also burdensome, subjective, and requires months to years of training, particularly for high-volume production operations. A reliable robotic visual inspection solution, however, has been hindered by the small defect size, intricate part characteristics, and demand for high inspection accuracy. This paper proposes a novel automated inspection path planning framework that addresses these core hurdles through four innovations: camera-parameter-based mesh segmentation, ray-tracing viewpoint placement, robot-agnostic viewpoint planning, and Bayesian optimization for faster segmentation. The effectiveness of the proposed workflow is tested with simulation and experimentation on a robotic inspection of heterogeneous complex geometries.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 146-157"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.047
Deepu Kumar T.N., Srinivasu D.S.
To manufacture complex parts using abrasive waterjets (AWJs) in milling mode, one should ensure that the local features of the target part geometry match with the channel shape produced by manipulating the operating parameters, such as jet impingement angle (α) and traverse speed (Vf). Hence, generating surfaces with tight tolerances demands control over the channel cross-section profile (CP) and its characteristics (maximum erosion depth, top width, cross-section area, and trailing edge angle). Despite AWJ technology's existence for decades, there have been limited attempts to obtain control over channel geometries. Since AWJ is a complex three-phase mixture (air-water-particles), determining the particle flow properties in AWJ for material removal is of utmost importance. These circumstances seek to establish a modelling approach for predicting the channel geometry under the change in α and Vf. This paper proposes an innovative model for predicting CPs obtained at shallow-angle jet (SAJ) impinged erosion trials, incorporating the insights gained on channel formation mathematically. The Ti-6Al-4V alloy is highly challenging to mill by conventional methods used for experiments. The modelling results demonstrate that by considering the mathematical relationship between the specific cutting energy associated with α and Vf and corresponding jet flow properties in the model, the prediction capability improved by 98 %. Overall, within the range of α (500–900) and Vf (3000–5000 mm/min), the model's prediction error of channel characteristics is <10 %, and the mean absolute error in channel shape is 22.74 μm. Strong conformity is observed with a correlation coefficient of 0.98 between modelled and experimental profiles.
{"title":"Shallow-angled jet impingement generated channel geometry prediction in milling Ti-6Al-4V alloy","authors":"Deepu Kumar T.N., Srinivasu D.S.","doi":"10.1016/j.jmapro.2024.12.047","DOIUrl":"10.1016/j.jmapro.2024.12.047","url":null,"abstract":"<div><div>To manufacture complex parts using abrasive waterjets (AWJs) in milling mode, one should ensure that the local features of the target part geometry match with the channel shape produced by manipulating the operating parameters, such as jet impingement angle (<em>α</em>) and traverse speed (<em>V</em><sub><em>f</em></sub>). Hence, generating surfaces with tight tolerances demands control over the channel cross-section profile (CP) and its characteristics (maximum erosion depth, top width, cross-section area, and trailing edge angle). Despite AWJ technology's existence for decades, there have been limited attempts to obtain control over channel geometries. Since AWJ is a complex three-phase mixture (air-water-particles), determining the particle flow properties in AWJ for material removal is of utmost importance. These circumstances seek to establish a modelling approach for predicting the channel geometry under the change in <em>α</em> and <em>V</em><sub><em>f</em></sub>. This paper proposes an innovative model for predicting CPs obtained at shallow-angle jet (SAJ) impinged erosion trials, incorporating the insights gained on channel formation mathematically. The Ti-6Al-4V alloy is highly challenging to mill by conventional methods used for experiments. The modelling results demonstrate that by considering the mathematical relationship between the specific cutting energy associated with <em>α</em> and <em>V</em><sub><em>f</em></sub> and corresponding jet flow properties in the model, the prediction capability improved by 98 %. Overall, within the range of <em>α</em> (50<sup>0</sup>–90<sup>0</sup>) and <em>V</em><sub><em>f</em></sub> (3000–5000 mm/min), the model's prediction error of channel characteristics is <10 %, and the mean absolute error in channel shape is 22.74 μm. Strong conformity is observed with a correlation coefficient of 0.98 between modelled and experimental profiles.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 410-434"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.043
Liaoyuan Chen , Juncai Li , Zhelun Ma , Chuang Jiang , Tianbiao Yu , Ruijie Gu
Laser directed energy deposition (DED) in situ synthesized ceramic-reinforced composite coatings exhibit great potential for application in the surface strengthening or remanufacturing of critical components. However, the step and sticky powder effects of composite coatings result in poor surface quality. Therefore, it is of great significance to study the grinding machinability of composite coatings and to improve their surface quality. In this study, laser DED TiC reinforced Ni-based composite coatings were synthesized in situ by adding Ti and Ni-coated graphite powder to the Ni-based alloy. Besides their microstructures and properties were analyzed to provide support for grinding machinability analysis. Subsequently, the effects of the grinding speed, feed rate, and cutting depth on the surface quality and grinding force were investigated using variance and signal-to-noise ratio analysis. Finally, Taguchi and grey correlation analyses were applied for the multi-objective optimization of the grinding parameters. The surface roughness (Ra), and tangential and normal grinding forces using the optimized process parameters are decreased by at least 7.18 %, 4.28 %, and 2.35 %, respectively. The ground surface was dominated by continuous plow-like grooves, and no craters or bumps caused by brittle spalling were observed. The bonding strength between the ceramic particles and matrix in the in situ synthesized composite coating was significantly improved. The peeling and extraction of ceramic particles on the ground surface were significantly decreased, resulting in surface roughness as low as 0.543 μm. In summary, laser DED in situ ceramic-reinforced composite coatings exhibit good machinability, providing theoretical and technical support for further practical applications.
{"title":"Grinding performance and parameter optimization of laser DED TiC reinforced Ni-based composite coatings","authors":"Liaoyuan Chen , Juncai Li , Zhelun Ma , Chuang Jiang , Tianbiao Yu , Ruijie Gu","doi":"10.1016/j.jmapro.2024.12.043","DOIUrl":"10.1016/j.jmapro.2024.12.043","url":null,"abstract":"<div><div>Laser directed energy deposition (DED) in situ synthesized ceramic-reinforced composite coatings exhibit great potential for application in the surface strengthening or remanufacturing of critical components. However, the step and sticky powder effects of composite coatings result in poor surface quality. Therefore, it is of great significance to study the grinding machinability of composite coatings and to improve their surface quality. In this study, laser DED TiC reinforced Ni-based composite coatings were synthesized in situ by adding Ti and Ni-coated graphite powder to the Ni-based alloy. Besides their microstructures and properties were analyzed to provide support for grinding machinability analysis. Subsequently, the effects of the grinding speed, feed rate, and cutting depth on the surface quality and grinding force were investigated using variance and signal-to-noise ratio analysis. Finally, Taguchi and grey correlation analyses were applied for the multi-objective optimization of the grinding parameters. The surface roughness (<em>R</em>a), and tangential and normal grinding forces using the optimized process parameters are decreased by at least 7.18 %, 4.28 %, and 2.35 %, respectively. The ground surface was dominated by continuous plow-like grooves, and no craters or bumps caused by brittle spalling were observed. The bonding strength between the ceramic particles and matrix in the in situ synthesized composite coating was significantly improved. The peeling and extraction of ceramic particles on the ground surface were significantly decreased, resulting in surface roughness as low as 0.543 μm. In summary, laser DED in situ ceramic-reinforced composite coatings exhibit good machinability, providing theoretical and technical support for further practical applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 466-481"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.065
Rohit Bokade, Sinan Müftü, Ozan Çağatay Özdemir, Xiaoning Jin
Cold spray is an advanced additive manufacturing technique where spray particles are accelerated through a supersonic nozzle for deposition onto a substrate. Variations in gas properties (e.g., temperature, pressure, mass flow rate) or nozzle conditions (e.g., wear or clogging) can lead to faults that affect the powder feed rate and deposition quality. These changes are reflected in the substrate’s temperature profile, which are monitored using thermal imaging. This study introduces ThermoAnoNet, a thermal image-based non-destructive testing (NDT) framework for detecting anomalies related to changes in gas dynamics or nozzle conditions. ThermoAnoNet forecasts the substrate’s temperature profile under normal conditions and detects anomalies by identifying deviations that indicate faults, such as increased deposition rates or nozzle clogging. The model, based on deep unsupervised learning, identifies temperature deviations that correlate with faults in the cold spray process. Experimental results show that ThermoAnoNet effectively detects anomalies with 90% accuracy, demonstrating its potential for real-time monitoring, minimizing defects, and enhancing the reliability of the cold spray process.
{"title":"Thermal imaging based non-destructive testing for fault detection in cold spray additive manufacturing","authors":"Rohit Bokade, Sinan Müftü, Ozan Çağatay Özdemir, Xiaoning Jin","doi":"10.1016/j.jmapro.2024.12.065","DOIUrl":"10.1016/j.jmapro.2024.12.065","url":null,"abstract":"<div><div>Cold spray is an advanced additive manufacturing technique where spray particles are accelerated through a supersonic nozzle for deposition onto a substrate. Variations in gas properties (e.g., temperature, pressure, mass flow rate) or nozzle conditions (e.g., wear or clogging) can lead to faults that affect the powder feed rate and deposition quality. These changes are reflected in the substrate’s temperature profile, which are monitored using thermal imaging. This study introduces ThermoAnoNet, a thermal image-based non-destructive testing (NDT) framework for detecting anomalies related to changes in gas dynamics or nozzle conditions. ThermoAnoNet forecasts the substrate’s temperature profile under normal conditions and detects anomalies by identifying deviations that indicate faults, such as increased deposition rates or nozzle clogging. The model, based on deep unsupervised learning, identifies temperature deviations that correlate with faults in the cold spray process. Experimental results show that ThermoAnoNet effectively detects anomalies with 90% accuracy, demonstrating its potential for real-time monitoring, minimizing defects, and enhancing the reliability of the cold spray process.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 1057-1068"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.034
Zhimin Liang , Zheng Ren , Yuzhong Rao , Kehong Wang , Liwei Wang , Xiaopeng Wang
Laser cladding is a material deposition process that involves melting and solidifying powders to form a coating. During the cladding process, unmelted powders can be observed flowing on the surface of the molten pool. This study aims to utilize these powders as tracer particles to calculate the velocity and vorticity fields of the molten pool surface. This information is crucial for understanding, analyzing, monitoring, and controlling the laser cladding process, particularly the dynamic correlations between cladding parameters, molten pool behavior, and cladding quality. However, this fundamental relationship has not been fully explored, and the lack of effective quantitative analysis methods for the molten pool flow field remains a significant challenge. With the development of optoelectronic devices, the molten pool can be imaged more effectively. However, challenges still exist due to the noise caused by pool oscillations and reflections, as well as the opacity of high-temperature liquid metal. While deep learning offers a promising solution, the small size, high interference, and low pixel proportion of powders in the images pose significant challenges for accurate segmentation. To address this challenge, an improved network that can extract unmelted powders from the molten pool image and reduce noise is proposed. This network is specifically designed based on the characteristics of the molten pool. First, a Molten Pool Network (MPNet) module is proposed to help the network focus on the important features of powders and ignore irrelevant features, thereby improving the performance of powder segmentation tasks. Subsequently, to solve the overfitting problem during network training, the transfer learning method is used to train the network. Experimental results verify that this method can accurately characterize the molten pool flow field even under high noise and oscillation conditions.
{"title":"Study on the visualization of laser cladding molten pool flow field based on attention mechanism","authors":"Zhimin Liang , Zheng Ren , Yuzhong Rao , Kehong Wang , Liwei Wang , Xiaopeng Wang","doi":"10.1016/j.jmapro.2024.12.034","DOIUrl":"10.1016/j.jmapro.2024.12.034","url":null,"abstract":"<div><div>Laser cladding is a material deposition process that involves melting and solidifying powders to form a coating. During the cladding process, unmelted powders can be observed flowing on the surface of the molten pool. This study aims to utilize these powders as tracer particles to calculate the velocity and vorticity fields of the molten pool surface. This information is crucial for understanding, analyzing, monitoring, and controlling the laser cladding process, particularly the dynamic correlations between cladding parameters, molten pool behavior, and cladding quality. However, this fundamental relationship has not been fully explored, and the lack of effective quantitative analysis methods for the molten pool flow field remains a significant challenge. With the development of optoelectronic devices, the molten pool can be imaged more effectively. However, challenges still exist due to the noise caused by pool oscillations and reflections, as well as the opacity of high-temperature liquid metal. While deep learning offers a promising solution, the small size, high interference, and low pixel proportion of powders in the images pose significant challenges for accurate segmentation. To address this challenge, an improved network that can extract unmelted powders from the molten pool image and reduce noise is proposed. This network is specifically designed based on the characteristics of the molten pool. First, a Molten Pool Network (MPNet) module is proposed to help the network focus on the important features of powders and ignore irrelevant features, thereby improving the performance of powder segmentation tasks. Subsequently, to solve the overfitting problem during network training, the transfer learning method is used to train the network. Experimental results verify that this method can accurately characterize the molten pool flow field even under high noise and oscillation conditions.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 337-347"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2025.01.001
Antonio Cañadilla , Ana Romero , Gloria P. Rodríguez , Grzegorz Matula , Łukasz Krzemiński , Błażej Tomiczek
Additive manufacturing (AM) makes it possible to produce parts with complex and customized shapes (internal channels or lattice structures), optimizing their physical, mechanical and/or thermal properties. The application of Concentrated Solar Energy (CSE) in an innovative Printing-Debinding-Solar Sintering (PDSS) methodology has been shown to be an effective and efficient way to produce dense copper parts with competitive mechanical, thermal, and electrical performance. The use of CSE in the sintering stage lowers treatment temperatures and shortens manufacturing times thanks to the activator effect of solar radiation in diffusion processes, reducing total costs and environmental footprint. However, further research is required into its application in the fabrication of complex functional metal components. This study addresses the design of a heat sink and a cylindrical catalyst for the first time, as well as its manufacturing via the PDSS methodology, establishing the optimal processing parameters and evaluating the properties of the final parts. Density measurements, scanning electron microscopy and computed tomography analysis were carried out at the different stages of the processing in order to evaluate the porosity and properties of as-printed, washed, brown and final parts. Complex geometry copper parts were successfully manufactured using a PDSS technique in shorter times (1 h) and with lower sintering temperatures (950 °C) than those required by conventional electric furnaces (∼25 h, 1075 °C), improving the sustainability and technical applications of this methodology. Furthermore, solar sintered copper components achieved competitive relative density properties up to ≈95 %, as well as adequate dimensional accuracy and deviation.
{"title":"Manufacturing copper complex parts using an innovative Printing-Debinding-Solar Sintering (PDSS) process","authors":"Antonio Cañadilla , Ana Romero , Gloria P. Rodríguez , Grzegorz Matula , Łukasz Krzemiński , Błażej Tomiczek","doi":"10.1016/j.jmapro.2025.01.001","DOIUrl":"10.1016/j.jmapro.2025.01.001","url":null,"abstract":"<div><div>Additive manufacturing (AM) makes it possible to produce parts with complex and customized shapes (internal channels or lattice structures), optimizing their physical, mechanical and/or thermal properties. The application of Concentrated Solar Energy (CSE) in an innovative Printing-Debinding-Solar Sintering (PDSS) methodology has been shown to be an effective and efficient way to produce dense copper parts with competitive mechanical, thermal, and electrical performance. The use of CSE in the sintering stage lowers treatment temperatures and shortens manufacturing times thanks to the activator effect of solar radiation in diffusion processes, reducing total costs and environmental footprint. However, further research is required into its application in the fabrication of complex functional metal components. This study addresses the design of a heat sink and a cylindrical catalyst for the first time, as well as its manufacturing via the PDSS methodology, establishing the optimal processing parameters and evaluating the properties of the final parts. Density measurements, scanning electron microscopy and computed tomography analysis were carried out at the different stages of the processing in order to evaluate the porosity and properties of as-printed, washed, brown and final parts. Complex geometry copper parts were successfully manufactured using a PDSS technique in shorter times (1 h) and with lower sintering temperatures (950 °C) than those required by conventional electric furnaces (∼25 h, 1075 °C), improving the sustainability and technical applications of this methodology. Furthermore, solar sintered copper components achieved competitive relative density properties up to ≈95 %, as well as adequate dimensional accuracy and deviation.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 851-865"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2025.01.008
Huapan Xiao , Shenxin Yin , Piao Zhou , Heng Wu
The selection of appropriate processing parameters is essential for achieving high-quality grinding of hard-brittle materials. This paper presents a prediction method of grinding parameters (grinding depth, feed rate, and wheel speed) to achieve specific surface integrity parameters (surface roughness, chipping layer depth, and subsurface damage depth). The method integrates the Optimum Latin hypercube design, a surface integrity model, and a genetic algorithm back propagation neural network (GA-BPNN) model. The surface integrity model considers the inclination effect of subsurface cracks and the elastic recovery of workpiece material. The GA-BPNN model is developed for constructing the relationship between grinding parameters and surface integrity parameters. To validate the prediction method, grinding experiments are performed on fused silica samples. The elastic recovery of fused silica is determined by indentation experiments. The surface roughness, chipping layer depth, and subsurface damage depth of the ground samples are measured. The results show that the surface integrity model has an average relative error below 7.5%, and the regression correlation coefficient for the GA-BPNN model exceeds 0.8. The prediction method achieves a maximum relative error of less than 6.5%. The influences of grinding parameters and material elastic recovery on the subsurface crack inclination and surface integrity parameters are investigated theoretically. The results show that increasing the grinding depth or feed rate, or decreasing the wheel speed or elastic recovery coefficient, leads to an increase in the maximum instantaneous inclination angle. The instantaneous inclination angle decreases while the instantaneous peak-valley value, chipping layer depth, or subsurface damage depth remains nearly unchanged with an increase in the elastic recovery coefficient. The research is conducive to evaluating the ground surface integrity and optimizing the grinding process to achieve efficient and low-damage machining of brittle materials.
{"title":"Prediction of grinding parameters based on specific surface integrity of hard-brittle materials","authors":"Huapan Xiao , Shenxin Yin , Piao Zhou , Heng Wu","doi":"10.1016/j.jmapro.2025.01.008","DOIUrl":"10.1016/j.jmapro.2025.01.008","url":null,"abstract":"<div><div>The selection of appropriate processing parameters is essential for achieving high-quality grinding of hard-brittle materials. This paper presents a prediction method of grinding parameters (grinding depth, feed rate, and wheel speed) to achieve specific surface integrity parameters (surface roughness, chipping layer depth, and subsurface damage depth). The method integrates the Optimum Latin hypercube design, a surface integrity model, and a genetic algorithm back propagation neural network (GA-BPNN) model. The surface integrity model considers the inclination effect of subsurface cracks and the elastic recovery of workpiece material. The GA-BPNN model is developed for constructing the relationship between grinding parameters and surface integrity parameters. To validate the prediction method, grinding experiments are performed on fused silica samples. The elastic recovery of fused silica is determined by indentation experiments. The surface roughness, chipping layer depth, and subsurface damage depth of the ground samples are measured. The results show that the surface integrity model has an average relative error below 7.5%, and the regression correlation coefficient for the GA-BPNN model exceeds 0.8. The prediction method achieves a maximum relative error of less than 6.5%. The influences of grinding parameters and material elastic recovery on the subsurface crack inclination and surface integrity parameters are investigated theoretically. The results show that increasing the grinding depth or feed rate, or decreasing the wheel speed or elastic recovery coefficient, leads to an increase in the maximum instantaneous inclination angle. The instantaneous inclination angle decreases while the instantaneous peak-valley value, chipping layer depth, or subsurface damage depth remains nearly unchanged with an increase in the elastic recovery coefficient. The research is conducive to evaluating the ground surface integrity and optimizing the grinding process to achieve efficient and low-damage machining of brittle materials.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 659-679"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.053
Miao Shang , Yan Li , Mingshun Yang , Qilong Yuan , Yongming Ding , Long Li
Single point incremental forming (SPIF) is a promising, dieless, rapid forming technology with great potential for forming complex thin-walled parts. However, in SPIF without turning sheets, the forming of convex features is limited by the features of die-less forming, especially the forming of complex concave-convex parts. To address this issue, a new process integrating the SPIF with hydraulic forming was proposed. Concave-convex feature parts are obtained by plastic deformation and elastic deformation of SPIF, hydraulic bulging, and hydraulic support. Then, three forming strategies are proposed based on the forming sequence of SPIF, hydraulic bulging, and hydraulic support. The geometric accuracy, thickness distribution, strain distribution and forming force of different forming strategies are studied separately. In addition, a new theoretical model is proposed to predict the thickness of concave-convex parts. Both FE simulation and experimental results show that concave-convex parts can be successfully formed either by adopting the strategy of bulging first and then SPIF or by bulging first and then hydrostatic support SPIF. Hydrostatic support with appropriate pressure is more conducive to improving the forming accuracy, and the theoretical model can accurately predict the forming thickness of complex parts. The new process is expected to manufacture complex concave-convex parts that are difficult to form in traditional SPIF at low cost, high efficiency, and high quality in one clamping.
{"title":"Investigation of formability and deformation behavior for forming concave-convex parts in single point incremental hydraulic forming","authors":"Miao Shang , Yan Li , Mingshun Yang , Qilong Yuan , Yongming Ding , Long Li","doi":"10.1016/j.jmapro.2024.12.053","DOIUrl":"10.1016/j.jmapro.2024.12.053","url":null,"abstract":"<div><div>Single point incremental forming (SPIF) is a promising, dieless, rapid forming technology with great potential for forming complex thin-walled parts. However, in SPIF without turning sheets, the forming of convex features is limited by the features of die-less forming, especially the forming of complex concave-convex parts. To address this issue, a new process integrating the SPIF with hydraulic forming was proposed. Concave-convex feature parts are obtained by plastic deformation and elastic deformation of SPIF, hydraulic bulging, and hydraulic support. Then, three forming strategies are proposed based on the forming sequence of SPIF, hydraulic bulging, and hydraulic support. The geometric accuracy, thickness distribution, strain distribution and forming force of different forming strategies are studied separately. In addition, a new theoretical model is proposed to predict the thickness of concave-convex parts. Both FE simulation and experimental results show that concave-convex parts can be successfully formed either by adopting the strategy of bulging first and then SPIF or by bulging first and then hydrostatic support SPIF. Hydrostatic support with appropriate pressure is more conducive to improving the forming accuracy, and the theoretical model can accurately predict the forming thickness of complex parts. The new process is expected to manufacture complex concave-convex parts that are difficult to form in traditional SPIF at low cost, high efficiency, and high quality in one clamping.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 648-658"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2024.12.071
Xianshi Jia , Jiawei Lin , Zhou Li , Chengaonan Wang , Kai Li , Cong Wang , Ji'an Duan
The low laser absorption of ceramic materials makes continuous wave (CW) laser ablation require high peak power densities, however craters on the material surface have been shown to significantly improve its absorption, which opens new possibilities for CW laser processing of ceramic materials. In our experiments, we noticed that under long focusing condition (focal length of 500 mm, diameter of 170 μm, average power of 100–700 W), the CW laser power density, even after being reduced to 1 % (from 9 × 107 W/cm2 to 9 × 105 W/cm2), was still able to achieve highly efficient ablation to alumina ceramic with the aid of craters prepared by the ablation of carbon particles on the material surface. More interestingly, 3 mm thick alumina ceramic could be transiently penetrated by the CW laser within an irradiation time of 20 ms, which showed a completely different ablation efficiency and mechanism from the conventional CW processing of ceramic materials. To this end, we comprehensively revealed the ablation characteristics and intrinsic mechanism of alumina ceramics under the ablation of the long focal condition CW laser through systematic process comparison experiments, high-speed shadow imaging, and theoretical simulation. The results can help to guide the CW laser processing of ceramic materials, such as high depth-width ratio hole processing, welding, etc., and also provide theoretical guidance for the design of ceramic-based high-energy laser protection materials.
{"title":"Continuous wave laser ablation of alumina ceramics under long focusing condition","authors":"Xianshi Jia , Jiawei Lin , Zhou Li , Chengaonan Wang , Kai Li , Cong Wang , Ji'an Duan","doi":"10.1016/j.jmapro.2024.12.071","DOIUrl":"10.1016/j.jmapro.2024.12.071","url":null,"abstract":"<div><div>The low laser absorption of ceramic materials makes continuous wave (CW) laser ablation require high peak power densities, however craters on the material surface have been shown to significantly improve its absorption, which opens new possibilities for CW laser processing of ceramic materials. In our experiments, we noticed that under long focusing condition (focal length of 500 mm, diameter of 170 μm, average power of 100–700 W), the CW laser power density, even after being reduced to 1 % (from 9 × 10<sup>7</sup> W/cm<sup>2</sup> to 9 × 10<sup>5</sup> W/cm<sup>2</sup>), was still able to achieve highly efficient ablation to alumina ceramic with the aid of craters prepared by the ablation of carbon particles on the material surface. More interestingly, 3 mm thick alumina ceramic could be transiently penetrated by the CW laser within an irradiation time of 20 ms, which showed a completely different ablation efficiency and mechanism from the conventional CW processing of ceramic materials. To this end, we comprehensively revealed the ablation characteristics and intrinsic mechanism of alumina ceramics under the ablation of the long focal condition CW laser through systematic process comparison experiments, high-speed shadow imaging, and theoretical simulation. The results can help to guide the CW laser processing of ceramic materials, such as high depth-width ratio hole processing, welding, etc., and also provide theoretical guidance for the design of ceramic-based high-energy laser protection materials.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 530-546"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jmapro.2025.01.012
Shiwei Deng , Yancheng Wang , Yangjian Li , Deqing Mei
With the rapid development of semiconductor industry, large-sized silicon wafers with high flatness and uniform nanotopography are generally required. Final-touch polishing (FP) is the final process in silicon wafer production, it can effectively clean the wafer's surface and control its surface geometry. The distribution of thermal field during final-touch polishing process is challenging to measure and predict, it greatly affects the characteristics and non-uniformity of material removal profile in both mechanical and chemical aspects. This study develops a numerical model to study the thermal field distribution and material removal, and used to predict the thermal characteristics and material removal profile of silicon wafer during final-touch polishing. For validation, an infrared camera and infrared sensor were applied to measure the surface temperature during polishing, and the surface material removal profile was examined and compared with model predictions. The surface material removal profile was also performed to investigate the effects of polishing parameters, including slurry flow rate, rotational speed and applied pressure. By obtaining optimal polishing parameters, final-touch polishing experiments were conducted on 12-inch silicon wafers. The experimental results showed that the polished silicon wafer has a highly flat surface with flatness of site front least square range was 23.06 nm and edge site front least square range was 23.77 nm, and the nanotopography threshold values of 2 × 2 mm2 area and 10 × 10 mm2 area (THA2 & THA10) for polished silicon wafer were 7.21 nm and 17.72 nm can be achieved, respectively.
{"title":"Numerical modeling and experimental study of thermal field and material removal for silicon wafer in final-touch polishing","authors":"Shiwei Deng , Yancheng Wang , Yangjian Li , Deqing Mei","doi":"10.1016/j.jmapro.2025.01.012","DOIUrl":"10.1016/j.jmapro.2025.01.012","url":null,"abstract":"<div><div>With the rapid development of semiconductor industry, large-sized silicon wafers with high flatness and uniform nanotopography are generally required. Final-touch polishing (FP) is the final process in silicon wafer production, it can effectively clean the wafer's surface and control its surface geometry. The distribution of thermal field during final-touch polishing process is challenging to measure and predict, it greatly affects the characteristics and non-uniformity of material removal profile in both mechanical and chemical aspects. This study develops a numerical model to study the thermal field distribution and material removal, and used to predict the thermal characteristics and material removal profile of silicon wafer during final-touch polishing. For validation, an infrared camera and infrared sensor were applied to measure the surface temperature during polishing, and the surface material removal profile was examined and compared with model predictions. The surface material removal profile was also performed to investigate the effects of polishing parameters, including slurry flow rate, rotational speed and applied pressure. By obtaining optimal polishing parameters, final-touch polishing experiments were conducted on 12-inch silicon wafers. The experimental results showed that the polished silicon wafer has a highly flat surface with flatness of site front least square range was 23.06 nm and edge site front least square range was 23.77 nm, and the nanotopography threshold values of 2 × 2 mm<sup>2</sup> area and 10 × 10 mm<sup>2</sup> area (THA2 & THA10) for polished silicon wafer were 7.21 nm and 17.72 nm can be achieved, respectively.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"134 ","pages":"Pages 709-720"},"PeriodicalIF":6.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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