Pub Date : 2025-08-06DOI: 10.1016/j.cirpj.2025.07.008
Meysam Norouzi-Inallu , Ilkka Poutiainen , Kari Ullakko
This study examines the fabrication of 316 L stainless steel (SS316L) thin-walled structures using the laser powder bed fusion (LPBF) process, with a focus on the influence of wall thickness and post-processing heat treatment on microstructural evolution and mechanical properties. As-built samples exhibited consistent epitaxial growth of the columnar grain structures aligned with the build direction in narrow dimensions. Thinner samples (0.6 mm wall thickness) showed more significant heat accumulation and slower cooling rates than thicker samples (1.0 mm wall thickness), with the former exhibiting substantial longitudinal grain growth, reduced residual stress, and lower tensile strength. Additionally, the thinner samples developed a stronger < 111 > texture, aligning with the build direction, which contributed to a decrease in microhardness and dislocation density. The high-temperature homogenization treatments refined the microstructure, leading to oriented coarse-grain structures with distinct crystallographic orientations. The post-processing reduced the microhardness by 36.60 % for the thicker sample and 19.83 % for the thinner sample. Furthermore, mechanical properties such as strength, hardness, ductility, and microhardness were closely linked to the observed crystallographic and grain structures. These findings highlight the significant impact of sample thickness, thermal history, and post-processing on the structural and mechanical properties of SS316L components manufactured using LPBF.
{"title":"Study of the wall thickness effect on the solidification and mechanical properties of thin-walled SS316L built via LPBF additive manufacturing","authors":"Meysam Norouzi-Inallu , Ilkka Poutiainen , Kari Ullakko","doi":"10.1016/j.cirpj.2025.07.008","DOIUrl":"10.1016/j.cirpj.2025.07.008","url":null,"abstract":"<div><div>This study examines the fabrication of 316 L stainless steel (SS316L) thin-walled structures using the laser powder bed fusion (LPBF) process, with a focus on the influence of wall thickness and post-processing heat treatment on microstructural evolution and mechanical properties. As-built samples exhibited consistent epitaxial growth of the columnar grain structures aligned with the build direction in narrow dimensions. Thinner samples (0.6 mm wall thickness) showed more significant heat accumulation and slower cooling rates than thicker samples (1.0 mm wall thickness), with the former exhibiting substantial longitudinal grain growth, reduced residual stress, and lower tensile strength. Additionally, the thinner samples developed a stronger < 111 > texture, aligning with the build direction, which contributed to a decrease in microhardness and dislocation density. The high-temperature homogenization treatments refined the microstructure, leading to oriented coarse-grain structures with distinct crystallographic orientations. The post-processing reduced the microhardness by 36.60 % for the thicker sample and 19.83 % for the thinner sample. Furthermore, mechanical properties such as strength, hardness, ductility, and microhardness were closely linked to the observed crystallographic and grain structures. These findings highlight the significant impact of sample thickness, thermal history, and post-processing on the structural and mechanical properties of SS316L components manufactured using LPBF.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 542-553"},"PeriodicalIF":5.4,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781000","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}
Pub Date : 2025-08-06DOI: 10.1016/j.cirpj.2025.07.010
Kaan Bahtiyar, Burak Sencer
Thanks to its high productivity, milling is a key subtractive process in modern metals manufacturing. Nevertheless, like other machining processes, it suffers from vibrations appearing in the form of forced and self-excited chatter. These vibrations deteriorate the surface finish quality, shorten tool life, and damage the machine components, limiting the attainable productivity. This paper presents a model-free adaptive spindle speed regulation strategy that aims to minimize overall machining vibrations in milling. The presented spindle-speed adaptation strategy is based on the model-free extremum seeking control (ESC) framework that searches the parameter space to minimize a desired cost function. The cost function is designed to penalize overall machining vibrations in the time-domain, and its gradient (search direction) is determined data-based by making use of the vibratory data collected during the machining operation. The stability of the proposed algorithm and its tuning guidance is provided to the end-users. The effectiveness of the proposed controller on minimizing overall machining vibrations is demonstrated in simulations and validated in machining tests. Results demonstrate significant reduction in RMS vibration level and lowered surface location errors (SLE) as compared to the conventional approach.
{"title":"Model-free optimal spindle speed control for real-time vibration mitigation in milling","authors":"Kaan Bahtiyar, Burak Sencer","doi":"10.1016/j.cirpj.2025.07.010","DOIUrl":"10.1016/j.cirpj.2025.07.010","url":null,"abstract":"<div><div>Thanks to its high productivity, milling is a key subtractive process in modern metals manufacturing. Nevertheless, like other machining processes, it suffers from vibrations appearing in the form of forced and self-excited chatter. These vibrations deteriorate the surface finish quality, shorten tool life, and damage the machine components, limiting the attainable productivity. This paper presents a model-free adaptive spindle speed regulation strategy that aims to minimize overall machining vibrations in milling. The presented spindle-speed adaptation strategy is based on the model-free extremum seeking control (ESC) framework that searches the parameter space to minimize a desired cost function. The cost function is designed to penalize overall machining vibrations in the time-domain, and its gradient (search direction) is determined data-based by making use of the vibratory data collected during the machining operation. The stability of the proposed algorithm and its tuning guidance is provided to the end-users. The effectiveness of the proposed controller on minimizing overall machining vibrations is demonstrated in simulations and validated in machining tests. Results demonstrate significant reduction in RMS vibration level and lowered surface location errors (SLE) as compared to the conventional approach.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 554-571"},"PeriodicalIF":5.4,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781001","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}
Pub Date : 2025-08-05DOI: 10.1016/j.cirpj.2025.07.009
Fei Lou , Hengbo Li , Yijie Wu
Local smoothing stands as the most prevalent technique for optimizing linear toolpaths in CNC machining. Nevertheless, its performance deteriorates markedly when applied to consecutive short segments, severely impacting machining efficiency. This paper proposes a real-time local smoothing and interpolation algorithm, in which a post-processing toolpath smoothing based on a second-order sliding convolution window is implemented to achieve continuity of the interpolated path while simultaneously satisfying constraints of tool tip and rotation smoothing errors. For consecutive short linear segments, convolution-based smoothing enables cross-segment optimization with enhanced geometric consistency, whereas linear regions in long segments are preserved which do not require an additional establishment of synchronization with the smooth region. Preceding the smoothing process, the jerk-limited feedrate scheduling operates at the level of primitive linear segments as the sole minimal unit, thereby circumventing challenges inherent in blended-path (linear and spline segments) interpolation. With adhering to the geometric constraints of the trajectory profile and the machine tool’s kinematic capabilities, this algorithm effectively enhances the scheduled feedrate by identifying the motion-limited axis of each segment. The effectiveness of the proposed algorithm is verified through simulations and experiments.
{"title":"A real-time interpolation algorithm for five-axis linear toolpaths with convolution-based local smoothing considering consecutive short segments","authors":"Fei Lou , Hengbo Li , Yijie Wu","doi":"10.1016/j.cirpj.2025.07.009","DOIUrl":"10.1016/j.cirpj.2025.07.009","url":null,"abstract":"<div><div>Local smoothing stands as the most prevalent technique for optimizing linear toolpaths in CNC machining. Nevertheless, its performance deteriorates markedly when applied to consecutive short segments, severely impacting machining efficiency. This paper proposes a real-time local smoothing and interpolation algorithm, in which a post-processing toolpath smoothing based on a second-order sliding convolution window is implemented to achieve <span><math><msup><mrow><mi>C</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> continuity of the interpolated path while simultaneously satisfying constraints of tool tip and rotation smoothing errors. For consecutive short linear segments, convolution-based smoothing enables cross-segment optimization with enhanced geometric consistency, whereas linear regions in long segments are preserved which do not require an additional establishment of synchronization with the smooth region. Preceding the smoothing process, the jerk-limited feedrate scheduling operates at the level of primitive linear segments as the sole minimal unit, thereby circumventing challenges inherent in blended-path (linear and spline segments) interpolation. With adhering to the geometric constraints of the trajectory profile and the machine tool’s kinematic capabilities, this algorithm effectively enhances the scheduled feedrate by identifying the motion-limited axis of each segment. The effectiveness of the proposed algorithm is verified through simulations and experiments.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 513-523"},"PeriodicalIF":5.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144780998","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}
Resistance spot welding (RSW) of three-layer steel sheets with unequal thicknesses presents significant challenges in accurately simulating weld nugget formation and process signal behavior. This paper proposes a hybrid approach that combines deep learning and multi-objective optimization to improve simulation accuracy. A 1D convolutional neural network (1DCNN), bidirectional long short-term memory (BiLSTM), and attention mechanism are integrated to predict dynamic resistance curves from process parameters. These predicted curves are then used as benchmarks in an ANSGA-II and Bayesian optimization framework to calibrate thermal-electrical contact parameters in a finite element model. Experimental results demonstrate that the optimized simulations closely match measured data, achieving a mean absolute error (MAE) of 0.132, a root mean square error (RMSE) of 0.156, and an value of 0.91. The calibrated model reduces resistance prediction error by over 30% and improves nugget diameter and weld depth prediction accuracy across multiple thickness configurations. This integrated framework offers a practical and data-efficient solution for enhancing RSW simulations in complex multi-layer welding scenarios.
{"title":"Experiments on resistance spot welding of three layers of unequal thickness steel based on deep learning and multi-objective optimization","authors":"Haofeng Deng , Pengyu Gao , Honggang Xiong , Xiangdong Gao","doi":"10.1016/j.cirpj.2025.07.005","DOIUrl":"10.1016/j.cirpj.2025.07.005","url":null,"abstract":"<div><div>Resistance spot welding (RSW) of three-layer steel sheets with unequal thicknesses presents significant challenges in accurately simulating weld nugget formation and process signal behavior. This paper proposes a hybrid approach that combines deep learning and multi-objective optimization to improve simulation accuracy. A 1D convolutional neural network (1DCNN), bidirectional long short-term memory (BiLSTM), and attention mechanism are integrated to predict dynamic resistance curves from process parameters. These predicted curves are then used as benchmarks in an ANSGA-II and Bayesian optimization framework to calibrate thermal-electrical contact parameters in a finite element model. Experimental results demonstrate that the optimized simulations closely match measured data, achieving a mean absolute error (MAE) of 0.132, a root mean square error (RMSE) of 0.156, and an <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> value of 0.91. The calibrated model reduces resistance prediction error by over 30% and improves nugget diameter and weld depth prediction accuracy across multiple thickness configurations. This integrated framework offers a practical and data-efficient solution for enhancing RSW simulations in complex multi-layer welding scenarios.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 497-512"},"PeriodicalIF":5.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144770728","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}
Pub Date : 2025-07-29DOI: 10.1016/j.cirpj.2025.07.006
S. Emami , G. Buffa , M. Adnan , B. Särnerblom , V. Patel , L. Fratini
Friction stir extrusion (FSE), as a promising solid-state chip recycling technique, was employed to produce recycled wires from AA 6082 aluminum chips. Al2O3 reinforced and unreinforced wires with different tool rotations and vertical downforce were produced. The microstructure and texture evolution were studied using the electron backscattered diffraction (EBSD) technique. EBSD orientation maps showed that the microstructures developed a bimodal grain structure including fine recrystallized and non-recrystallized elongated grains. Grain orientation spread (GOS) EBSD maps demonstrated that the recrystallization was promoted in the presence of alumina second-phase nanoparticles. The resultant point-to-point and point-to-origin misorientation angle histograms indicated trivial misorientation differences proving the geometric dynamic recrystallization (GDRX) occurrence. The presence of loose high-angle grain boundaries (HAGBs) and accumulative misorientation angle inside the individual grains confirmed the continuous dynamic recrystallization (CDRX) occurrence. Moreover, grain boundary bulging was also visible through the microstructure, proving the activation of discontinuous dynamic recrystallization (DDRX). Texture analysis showed that simple a shear texture were introduced in the microstructure of the produced wires. The intensity of the obtained textures from the orientation distribution function (ODF) suggested that the application of the alumina particles improved the material flow during recycling. Micro-hardness measurements revealed that the addition of the alumina particles increased the hardness from 90 HV to 119 HV. Tensile testing showed a 20 % higher UTS for wires with alumina powders.
{"title":"On the effect of nanosized Al2O3 on the mechanical properties and microstructural evolution during friction stir extrusion of AA 6082 aluminum chips","authors":"S. Emami , G. Buffa , M. Adnan , B. Särnerblom , V. Patel , L. Fratini","doi":"10.1016/j.cirpj.2025.07.006","DOIUrl":"10.1016/j.cirpj.2025.07.006","url":null,"abstract":"<div><div>Friction stir extrusion (FSE), as a promising solid-state chip recycling technique, was employed to produce recycled wires from AA 6082 aluminum chips. Al<sub>2</sub>O<sub>3</sub> reinforced and unreinforced wires with different tool rotations and vertical downforce were produced. The microstructure and texture evolution were studied using the electron backscattered diffraction (EBSD) technique. EBSD orientation maps showed that the microstructures developed a bimodal grain structure including fine recrystallized and non-recrystallized elongated grains. Grain orientation spread (GOS) EBSD maps demonstrated that the recrystallization was promoted in the presence of alumina second-phase nanoparticles. The resultant point-to-point and point-to-origin misorientation angle histograms indicated trivial misorientation differences proving the geometric dynamic recrystallization (GDRX) occurrence. The presence of loose high-angle grain boundaries (HAGBs) and accumulative misorientation angle inside the individual grains confirmed the continuous dynamic recrystallization (CDRX) occurrence. Moreover, grain boundary bulging was also visible through the microstructure, proving the activation of discontinuous dynamic recrystallization (DDRX). Texture analysis showed that simple a shear texture were introduced in the microstructure of the produced wires. The intensity of the obtained textures from the orientation distribution function (ODF) suggested that the application of the alumina particles improved the material flow during recycling. Micro-hardness measurements revealed that the addition of the alumina particles increased the hardness from 90 HV to 119 HV. Tensile testing showed a 20 % higher UTS for wires with alumina powders.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 485-496"},"PeriodicalIF":5.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721798","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}
Current research on additive manufacturing predominantly focuses on the structural and parameter levels, with relatively limited exploration on the functional level. This study investigates the construction process of the functional period in additive manufacturing by adapting the analysis and problem-solving tools from TRIZ theory at the functional level. First, the cyclic behavior of the additive manufacturing process is elucidated, followed by an analysis of the functional period embedded within the process. A classification method for complexity is introduced and the role of the functional period in transforming types of complexity is explained. Second, the analytic tools and problem-solving tools within TRIZ theory that are applicable to the additive manufacturing process have been summarized, leading to the establishment of functional solution acquisition paths specific to the additive manufacturing process. Third, based on these functional solution acquisition paths, a process model for constructing the functional period in additive manufacturing is proposed. Finally, the proposed functional period construction process model is applied to the porosity control of tin bronze samples. Experimental results demonstrate that the density of the tin bronze sample increased by over 4 %, confirming the feasibility of the TRIZ-assisted functional period construction process in additive manufacturing.
{"title":"The research of TRIZ-assisted additive manufacturing functional period construction process","authors":"Yunpeng Su, Guiru Wu, Zhen Liao, Xiaomeng Yan, Lanxin Jiang, Huan Qi","doi":"10.1016/j.cirpj.2025.07.007","DOIUrl":"10.1016/j.cirpj.2025.07.007","url":null,"abstract":"<div><div>Current research on additive manufacturing predominantly focuses on the structural and parameter levels, with relatively limited exploration on the functional level. This study investigates the construction process of the functional period in additive manufacturing by adapting the analysis and problem-solving tools from TRIZ theory at the functional level. First, the cyclic behavior of the additive manufacturing process is elucidated, followed by an analysis of the functional period embedded within the process. A classification method for complexity is introduced and the role of the functional period in transforming types of complexity is explained. Second, the analytic tools and problem-solving tools within TRIZ theory that are applicable to the additive manufacturing process have been summarized, leading to the establishment of functional solution acquisition paths specific to the additive manufacturing process. Third, based on these functional solution acquisition paths, a process model for constructing the functional period in additive manufacturing is proposed. Finally, the proposed functional period construction process model is applied to the porosity control of tin bronze samples. Experimental results demonstrate that the density of the tin bronze sample increased by over 4 %, confirming the feasibility of the TRIZ-assisted functional period construction process in additive manufacturing.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 474-484"},"PeriodicalIF":4.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711101","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}
The formation of castings depends on numerous process parameters, making traditional casting process design heavily reliant on experience and complex calculations. Efficiently retrieving similar parts from a case library for process reuse can significantly enhance design efficiency. This study has proposed a tailored retrieval scheme for casting parts, ensuring that retrieved parts provide valuable references for process design. First, the study has introduced the concept of process constraint values to quantify the impact of differences in key semantic information—material, casting method, and production batch size—on the applicability and effective transferability of existing processes. These constraint values are incorporated as conditions in subsequent similarity calculations, ensuring that the retrieved parts offer practical reference value for casting process design. For geometric similarity measurement, simulation experiments and flowability analyses are conducted to evaluate the influence of volume and modulus on similarity computation. Considering the characteristics of casting production, shape-structure features are extracted from both the external solid model and internal cavity models. These features are then integrated into a combined encoding, providing a parametric representation of the part’s geometric characteristics. Finally, the overall geometric similarity between parts is simultaneously measured based on volume, modulus, and shape-structure feature encoding. The effectiveness of the proposed retrieval algorithm was validated using Expected Reciprocal Rank (ERR) and F1-score. Results indicate that the first highly similar part appeared at the 1.23th position in the ranked retrieval sequence, allowing users to efficiently find relevant parts at the top of the retrieval rankings. Furthermore, separating the feature extraction and similarity calculation of the external solid and internal cavity improves retrieval performance compared to direct feature extraction from the original part model, especially in high-relevance scenarios with few candidate results.
{"title":"Casting parts retrieval driven by the integration of process constraints and geometric features","authors":"Chuhao Zhou , Shuren Guo , Dong Xiang, Xuanpu Dong, Huatang Cao","doi":"10.1016/j.cirpj.2025.07.003","DOIUrl":"10.1016/j.cirpj.2025.07.003","url":null,"abstract":"<div><div>The formation of castings depends on numerous process parameters, making traditional casting process design heavily reliant on experience and complex calculations. Efficiently retrieving similar parts from a case library for process reuse can significantly enhance design efficiency. This study has proposed a tailored retrieval scheme for casting parts, ensuring that retrieved parts provide valuable references for process design. First, the study has introduced the concept of process constraint values to quantify the impact of differences in key semantic information—material, casting method, and production batch size—on the applicability and effective transferability of existing processes. These constraint values are incorporated as conditions in subsequent similarity calculations, ensuring that the retrieved parts offer practical reference value for casting process design. For geometric similarity measurement, simulation experiments and flowability analyses are conducted to evaluate the influence of volume and modulus on similarity computation. Considering the characteristics of casting production, shape-structure features are extracted from both the external solid model and internal cavity models. These features are then integrated into a combined encoding, providing a parametric representation of the part’s geometric characteristics. Finally, the overall geometric similarity between parts is simultaneously measured based on volume, modulus, and shape-structure feature encoding. The effectiveness of the proposed retrieval algorithm was validated using Expected Reciprocal Rank (ERR) and F1-score. Results indicate that the first highly similar part appeared at the 1.23th position in the ranked retrieval sequence, allowing users to efficiently find relevant parts at the top of the retrieval rankings. Furthermore, separating the feature extraction and similarity calculation of the external solid and internal cavity improves retrieval performance compared to direct feature extraction from the original part model, especially in high-relevance scenarios with few candidate results.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 443-462"},"PeriodicalIF":4.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687096","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}
This study investigates the synergistic effects of laser-assisted ultrasonic nanocrystal surface modification (LA-UNSM) on the surface integrity and microstructural evolution of 3D-printed Ti6Al4V alloy. By integrating localized laser heating (optimal power of 23 W) with ultrasonic peening, LA-UNSM significantly enhances material plasticity during treatment. As a result, compared to conventional UNSM, the process markedly improves surface finish, hardness, and compressive residual stress. Detailed analyses show that LA-UNSM refines the surface microstructure by reducing roughness (from 17.8 µm in as-fabricated samples to approximately 3.2 µm) and increasing hardness (from 359.5 HV to over 487.5 HV). Additionally, LA-UNSM promotes deeper plastic deformation, effectively reducing surface porosity and refining the grain size from an average of 1.1 µm to 0.53 µm. The treatment further modifies the crystallographic texture and slip behavior by favoring pyramidal 〈c+a〉 slip, which enhances strain accommodation and reinforces the compressive residual stress field. These findings demonstrate that LA-UNSM is a transformative, energy-efficient post-processing technique that substantially enhances the performance of additively manufactured Ti6Al4V alloys.
{"title":"The effects of laser assisted ultrasonic nanocrystal surface modification on 3D-printed Ti6Al4V alloy","authors":"Hao Zhang , Yu Zhang , Chang Ye , Giovanna Rotella , Domenico Umbrello","doi":"10.1016/j.cirpj.2025.07.004","DOIUrl":"10.1016/j.cirpj.2025.07.004","url":null,"abstract":"<div><div>This study investigates the synergistic effects of laser-assisted ultrasonic nanocrystal surface modification (LA-UNSM) on the surface integrity and microstructural evolution of 3D-printed Ti6Al4V alloy. By integrating localized laser heating (optimal power of 23 W) with ultrasonic peening, LA-UNSM significantly enhances material plasticity during treatment. As a result, compared to conventional UNSM, the process markedly improves surface finish, hardness, and compressive residual stress. Detailed analyses show that LA-UNSM refines the surface microstructure by reducing roughness (from 17.8 µm in as-fabricated samples to approximately 3.2 µm) and increasing hardness (from 359.5 HV to over 487.5 HV). Additionally, LA-UNSM promotes deeper plastic deformation, effectively reducing surface porosity and refining the grain size from an average of 1.1 µm to 0.53 µm. The treatment further modifies the crystallographic texture and slip behavior by favoring pyramidal 〈c+a〉 slip, which enhances strain accommodation and reinforces the compressive residual stress field. These findings demonstrate that LA-UNSM is a transformative, energy-efficient post-processing technique that substantially enhances the performance of additively manufactured Ti6Al4V alloys.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 463-473"},"PeriodicalIF":4.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687097","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}
Pub Date : 2025-07-19DOI: 10.1016/j.cirpj.2025.06.009
Yuning Zhang, Tong Xiao, Jinting Xu, Yuwen Sun
Traditional reverse engineering (RE) often involves complicated and time-consuming CAD model reconstruction, which can be inefficient or unnecessary in practical scenarios focused on rapid shape replication and design validation. Therefore, a method is proposed in this paper for generating contour-parallel tool paths directly from point clouds, bypassing CAD model reconstruction, and it is particularly suited for parts with holes or island features. In this method, boundary points are first extracted and sequenced, and then boundaries are employed as initial tool paths to generate subsequent tool paths through successively offsetting. In the tool path offsetting, a novel point projection-based offsetting strategy is presented to calculate accurate cutter contact (CC) points in the neighbouring tool path, and the self-intersections appearing in offset CC paths are eliminated simultaneously. To simplify the offsetting operations, a simple merging strategy between the inner boundary and the generated offset tool path is presented to remove the undesired intra-intersections. Case studies demonstrate that the proposed method can nicely generate continuous and boundary conformal contour-parallel tool paths directly on point clouds with and without holes. Different from traditional CAD modelling, the proposed method provides a fast and efficient alternative for shape-oriented RE tasks.
{"title":"Point projection-based contour-parallel tool path from point cloud","authors":"Yuning Zhang, Tong Xiao, Jinting Xu, Yuwen Sun","doi":"10.1016/j.cirpj.2025.06.009","DOIUrl":"10.1016/j.cirpj.2025.06.009","url":null,"abstract":"<div><div>Traditional reverse engineering (RE) often involves complicated and time-consuming CAD model reconstruction, which can be inefficient or unnecessary in practical scenarios focused on rapid shape replication and design validation. Therefore, a method is proposed in this paper for generating contour-parallel tool paths directly from point clouds, bypassing CAD model reconstruction, and it is particularly suited for parts with holes or island features. In this method, boundary points are first extracted and sequenced, and then boundaries are employed as initial tool paths to generate subsequent tool paths through successively offsetting. In the tool path offsetting, a novel point projection-based offsetting strategy is presented to calculate accurate cutter contact (CC) points in the neighbouring tool path, and the self-intersections appearing in offset CC paths are eliminated simultaneously. To simplify the offsetting operations, a simple merging strategy between the inner boundary and the generated offset tool path is presented to remove the undesired intra-intersections. Case studies demonstrate that the proposed method can nicely generate continuous and boundary conformal contour-parallel tool paths directly on point clouds with and without holes. Different from traditional CAD modelling, the proposed method provides a fast and efficient alternative for shape-oriented RE tasks.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 427-442"},"PeriodicalIF":4.6,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663519","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}
Toroidal involute worm (TI worm) exhibits high load-bearing capacity and transmission efficiency. However, its complex spatial geometry complicates machining processes and limits mass production. This study combines the enveloping principle of the TI worm with the internal whirling technique. A novel method is developed for enveloping the TI worm via internal whirling. The influence of tool offsets and mounting angles on the tooth surface deviations between internal whirling-enveloped TI worm and standard TI worm is investigated. The results indicate that the tooth surface of the internal whirling-enveloped TI worm closely approximates that of modified standard TI worm. The amount and position of the modification can be effectively controlled through tool offset and mounting angle adjustments. Experimental measurements reveal a maximum tooth surface deviation below 0.04 mm. The machined worm meshes in the middle of the involute helical gear, reducing offset load risks. Comparative tests confirm comparable transmission performance between machined worm and standard TI worm. This study establishes theoretical and experimental foundations for mass production of TI worm via internal whirling to meet industrial demands.
{"title":"Investigations on the tooth surface deviations of internal whirling-enveloped TI worm","authors":"Zhenglin Yang, Yonghong Chen, Diao Chen, Wenjun Luo, Bingkui Chen","doi":"10.1016/j.cirpj.2025.07.002","DOIUrl":"10.1016/j.cirpj.2025.07.002","url":null,"abstract":"<div><div>Toroidal involute worm (TI worm) exhibits high load-bearing capacity and transmission efficiency. However, its complex spatial geometry complicates machining processes and limits mass production. This study combines the enveloping principle of the TI worm with the internal whirling technique. A novel method is developed for enveloping the TI worm via internal whirling. The influence of tool offsets and mounting angles on the tooth surface deviations between internal whirling-enveloped TI worm and standard TI worm is investigated. The results indicate that the tooth surface of the internal whirling-enveloped TI worm closely approximates that of modified standard TI worm. The amount and position of the modification can be effectively controlled through tool offset and mounting angle adjustments. Experimental measurements reveal a maximum tooth surface deviation below 0.04 mm. The machined worm meshes in the middle of the involute helical gear, reducing offset load risks. Comparative tests confirm comparable transmission performance between machined worm and standard TI worm. This study establishes theoretical and experimental foundations for mass production of TI worm via internal whirling to meet industrial demands.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"61 ","pages":"Pages 410-426"},"PeriodicalIF":4.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653404","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}