Pub Date : 2026-02-01Epub Date: 2025-12-08DOI: 10.1016/j.cirpj.2025.12.002
Sofia Catalucci, Enrico Savio
Defect detection is critical in manufacturing processes such as casting, machining, and additive manufacturing, where imperfections can impair part functionality and reliability. This work proposes a deep learning-based methodology for the detection and dimensional inspection of three-dimensional surface defects. The approach integrates deep learning trained on pre-labelled data and applied to two-dimensional deviation maps derived from laser-based measurements, and a skeletonization algorithm to estimate defect dimensions. Accuracy is ensured by metrological validation using reference measurements from a multisensor coordinate measuring machine. Applied to die-cast components, the framework demonstrates robust performance, offering a reliable tool for integration into real-world quality control workflows.
{"title":"Metrological validation of a deep learning pipeline for in-line detection and dimensional quantification of three-dimensional surface defects","authors":"Sofia Catalucci, Enrico Savio","doi":"10.1016/j.cirpj.2025.12.002","DOIUrl":"10.1016/j.cirpj.2025.12.002","url":null,"abstract":"<div><div>Defect detection is critical in manufacturing processes such as casting, machining, and additive manufacturing, where imperfections can impair part functionality and reliability. This work proposes a deep learning-based methodology for the detection and dimensional inspection of three-dimensional surface defects. The approach integrates deep learning trained on pre-labelled data and applied to two-dimensional deviation maps derived from laser-based measurements, and a skeletonization algorithm to estimate defect dimensions. Accuracy is ensured by metrological validation using reference measurements from a multisensor coordinate measuring machine. Applied to die-cast components, the framework demonstrates robust performance, offering a reliable tool for integration into real-world quality control workflows.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 107-119"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748172","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 : 2026-02-01Epub Date: 2025-12-16DOI: 10.1016/j.cirpj.2025.12.010
Samet Can Kaçan, Hakan Çalışkan
This paper presents an Extended Kalman Filter (EKF)-based real-time methodology for in-process modal identification and tool–workpiece engagement detection in milling operations. Unlike conventional offline Experimental Modal Analysis (EMA) and Operational Modal Analysis (OMA) methods, the proposed approach enables online tracking of time-varying modal parameters without requiring external excitation and force measurement. It is proposed to utilize the acceleration measurements occurring between two consecutive tooth-workpiece engagements, for that purpose an EKF, based on the free vibration response model is constructed. The angular tool position is not measured, to identify the onset of free vibration, a robust engagement detection algorithm is developed, which remains effective under spindle speed variations and geometric inaccuracies. The complete framework consists of three stages: (i) recursive estimation of dominant modal parameters — natural frequency, damping ratio, and amplitude — using the EKF; (ii) adaptive engagement detection through thresholding of the mean absolute scaled error (MASE); and (iii) refinement of the estimated modal parameters via median and Kalman filtering to suppress Bernoulli and Gaussian noise. The proposed method is experimentally validated on a thin wall cantilever workpiece during end-milling where results are compared with conventional hammer-test EMA results. The identified modal parameters closely match the EMA results demonstrating the method’s potential in monitoring machining processes.
{"title":"Integrated framework for in-process modal analysis and tool–workpiece engagement detection","authors":"Samet Can Kaçan, Hakan Çalışkan","doi":"10.1016/j.cirpj.2025.12.010","DOIUrl":"10.1016/j.cirpj.2025.12.010","url":null,"abstract":"<div><div>This paper presents an Extended Kalman Filter (EKF)-based real-time methodology for in-process modal identification and tool–workpiece engagement detection in milling operations. Unlike conventional offline Experimental Modal Analysis (EMA) and Operational Modal Analysis (OMA) methods, the proposed approach enables online tracking of time-varying modal parameters without requiring external excitation and force measurement. It is proposed to utilize the acceleration measurements occurring between two consecutive tooth-workpiece engagements, for that purpose an EKF, based on the free vibration response model is constructed. The angular tool position is not measured, to identify the onset of free vibration, a robust engagement detection algorithm is developed, which remains effective under spindle speed variations and geometric inaccuracies. The complete framework consists of three stages: (i) recursive estimation of dominant modal parameters — natural frequency, damping ratio, and amplitude — using the EKF; (ii) adaptive engagement detection through thresholding of the mean absolute scaled error (MASE); and (iii) refinement of the estimated modal parameters via median and Kalman filtering to suppress Bernoulli and Gaussian noise. The proposed method is experimentally validated on a thin wall cantilever workpiece during end-milling where results are compared with conventional hammer-test EMA results. The identified modal parameters closely match the EMA results demonstrating the method’s potential in monitoring machining processes.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 160-170"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797323","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 : 2026-02-01Epub Date: 2025-12-19DOI: 10.1016/j.cirpj.2025.12.008
Shuo Wang , Hongchao Wang , Rutie Zeng , Lin Wan , Gang Che
To effectively control the springback of agricultural tractor mudguards, this paper proposes an optimized design framework for springback control. The framework centers on stress path control and geometric reverse compensation, integrating process parameter optimization, theoretical modeling, auxiliary structure design, and geometric reverse mold compensation. This approach transitions from a single-method strategy to a combined approach of “process parameter control – drawbead setting – geometric reverse compensation”. The results indicate a significant correlation between the thickness, blank holder force, stamping speed, friction coefficient, and die clearance with the springback amount. The semi-analytical model and response surface model developed have coefficients of determination of 0.921 and 0.917, respectively. A complex non-linear relationship exists between each parameter and the springback, with distinct mathematical variation curves observed. The primary and secondary effects of the parameters are ranked as follows: blank holder force, die clearance, thickness, friction coefficient, and stamping speed. By employing the “process parameter control – drawbead setting – geometric reverse compensation” strategy, the springback can be controlled to 5.37 °. Moreover, experimental validation yields a springback of 5.14 °, which results in a 0.23 °. This study provides a solid theoretical foundation and reliable numerical basis for the practical production and processing of mudguards.
{"title":"Mudguard stamping springback control for agricultural tractors: Collaborative multi-strategy approach and experimental verification","authors":"Shuo Wang , Hongchao Wang , Rutie Zeng , Lin Wan , Gang Che","doi":"10.1016/j.cirpj.2025.12.008","DOIUrl":"10.1016/j.cirpj.2025.12.008","url":null,"abstract":"<div><div>To effectively control the springback of agricultural tractor mudguards, this paper proposes an optimized design framework for springback control. The framework centers on stress path control and geometric reverse compensation, integrating process parameter optimization, theoretical modeling, auxiliary structure design, and geometric reverse mold compensation. This approach transitions from a single-method strategy to a combined approach of “process parameter control – drawbead setting – geometric reverse compensation”. The results indicate a significant correlation between the thickness, blank holder force, stamping speed, friction coefficient, and die clearance with the springback amount. The semi-analytical model and response surface model developed have coefficients of determination of 0.921 and 0.917, respectively. A complex non-linear relationship exists between each parameter and the springback, with distinct mathematical variation curves observed. The primary and secondary effects of the parameters are ranked as follows: blank holder force, die clearance, thickness, friction coefficient, and stamping speed. By employing the “process parameter control – drawbead setting – geometric reverse compensation” strategy, the springback can be controlled to 5.37 °. Moreover, experimental validation yields a springback of 5.14 °, which results in a 0.23 °. This study provides a solid theoretical foundation and reliable numerical basis for the practical production and processing of mudguards.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 187-202"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797324","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 : 2026-02-01Epub Date: 2025-12-03DOI: 10.1016/j.cirpj.2025.11.008
James Wainwright , David Rico Sierra , Alec Davis , Stewart Williams , Jialuo Ding
This study investigates the applicability of a novel laser-arc multi-energy deposition of Ti-6Al-4V with independent control of bead geometry and thermal input. A plasma transferred arc is used to generate an initial melt pool and melt wire feedstock, before controlled lateral elongation of the melt pool via a fiber laser and galvo scanner. The applicability to Ti-6Al-4V was first investigated using deposition parameters previously identified. Once successful bead geometry control was achieved, process parameters more conducive to wire directed energy deposition were investigated. This included investigation of the energy per unit area required to achieve accurate deposition of Ti-6Al-4V with minimal penetration and investigation into scanning strategy. In each case, optical microscopy was conducted and analysis of the bead geometry, penetration and heat-affected zone considered to determine the effect of each parameter change. The results demonstrated that independent control of bead geometry and thermal input could be achieved, allowing deposition of Ti-6Al-4V at a desired scan width and layer height and providing a framework for future multi-energy source directed energy deposition of Ti-6Al-4V.
{"title":"Melt pool geometry control of Ti-6Al-4V utilizing multi-energy source laser-arc + wire directed energy deposition","authors":"James Wainwright , David Rico Sierra , Alec Davis , Stewart Williams , Jialuo Ding","doi":"10.1016/j.cirpj.2025.11.008","DOIUrl":"10.1016/j.cirpj.2025.11.008","url":null,"abstract":"<div><div>This study investigates the applicability of a novel laser-arc multi-energy deposition of Ti-6Al-4V with independent control of bead geometry and thermal input. A plasma transferred arc is used to generate an initial melt pool and melt wire feedstock, before controlled lateral elongation of the melt pool via a fiber laser and galvo scanner. The applicability to Ti-6Al-4V was first investigated using deposition parameters previously identified. Once successful bead geometry control was achieved, process parameters more conducive to wire directed energy deposition were investigated. This included investigation of the energy per unit area required to achieve accurate deposition of Ti-6Al-4V with minimal penetration and investigation into scanning strategy. In each case, optical microscopy was conducted and analysis of the bead geometry, penetration and heat-affected zone considered to determine the effect of each parameter change. The results demonstrated that independent control of bead geometry and thermal input could be achieved, allowing deposition of Ti-6Al-4V at a desired scan width and layer height and providing a framework for future multi-energy source directed energy deposition of Ti-6Al-4V.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 79-91"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694414","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 : 2026-02-01Epub Date: 2025-11-29DOI: 10.1016/j.cirpj.2025.11.011
Zhenghui Lu, Xiaoliang Jin
During carbon fiber-reinforced polymer (CFRP) machining, the cutting forces of a multi-directional (MD) laminate can be significantly higher or lower than the superposed cutting forces from unidirectional (UD) laminates for different fiber orientation (FO) combinations, with the underlying mechanism remained unclear. This study proposes a new analytical cutting mechanics model for MD CFRP with ply-constraining effect. The constrained ply in-situ strengths in MD CFRP are derived by determining the onset of crack propagation by fracture mechanics. The cutting strain rate as well as stress for a constrained UD ply with changing FOs are modeled. Then, by strain rate-dependent physics-based failure criteria with in-situ strengths, the material failure of each ply during chip formation is determined. With the model, the failure stress and failure mode of each constrained UD ply with varying FOs are simulated, bringing forth the cutting force prediction for the whole MD laminate. The model-simulated cutting forces agree with experimental values for a series of MD CFRP workpieces with different FO combinations. Distinct ply-constraining effects within different FO ranges are identified and analyzed, which explain the different situations of the cutting force variation from UD laminates to MD laminates for the first time. The study contributes to a new understanding for chip formation and cutting force generation of MD laminates with various FO combinations.
{"title":"Modeling multi-directional CFRP cutting mechanics with ply-constraining effect","authors":"Zhenghui Lu, Xiaoliang Jin","doi":"10.1016/j.cirpj.2025.11.011","DOIUrl":"10.1016/j.cirpj.2025.11.011","url":null,"abstract":"<div><div>During carbon fiber-reinforced polymer (CFRP) machining, the cutting forces of a multi-directional (MD) laminate can be significantly higher or lower than the superposed cutting forces from unidirectional (UD) laminates for different fiber orientation (FO) combinations, with the underlying mechanism remained unclear. This study proposes a new analytical cutting mechanics model for MD CFRP with ply-constraining effect. The constrained ply in-situ strengths in MD CFRP are derived by determining the onset of crack propagation by fracture mechanics. The cutting strain rate as well as stress for a constrained UD ply with changing FOs are modeled. Then, by strain rate-dependent physics-based failure criteria with in-situ strengths, the material failure of each ply during chip formation is determined. With the model, the failure stress and failure mode of each constrained UD ply with varying FOs are simulated, bringing forth the cutting force prediction for the whole MD laminate. The model-simulated cutting forces agree with experimental values for a series of MD CFRP workpieces with different FO combinations. Distinct ply-constraining effects within different FO ranges are identified and analyzed, which explain the different situations of the cutting force variation from UD laminates to MD laminates for the first time. The study contributes to a new understanding for chip formation and cutting force generation of MD laminates with various FO combinations.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 46-64"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694440","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 paper introduces a prediction model for the three-dimensional (3D) geometry of multi-layer single-track (wall-deposition) workpieces in Wire Arc Additive Manufacturing (WAAM), enabling accurate predictions with minimal experimental effort. The model extends a prior single-bead prediction model by incorporating four key enhancements: (1) using multiple cross-sections to capture the full wall geometry, (2) integration of additional input parameters to account for thermal history and deposition sequence, (3) development of an improved geometric-characterization function for better representation of wall geometry, and (4) employing a hybrid dataset composed of synthetic and experimental datasets acquired without specialized equipment, such as in-process geometry measurement systems, thereby simplifying the data collection process. A two-step transfer learning strategy was employed to pretrain the model on a synthetic dataset and subsequently train it using an experimental dataset. This approach enables accurate predictions, even when only a limited amount of experimental data is available. Compared with baseline models without transfer learning, the developed model achieved a substantial reduction in prediction errors, averaging improvements between 5–30 %. Specifically, it attained an error of approximately 10 % for height predictions and 15 % for width predictions. These contributions enhance the adaptability and scalability of the WAAM processes, thereby enabling more efficient and precise manufacturing.
{"title":"3D geometry prediction for wall deposition using transfer learning in wire arc additive manufacturing","authors":"Hayato Kitagawa , Talash Malek , Daisuke Kono , Berend Denkena","doi":"10.1016/j.cirpj.2025.11.007","DOIUrl":"10.1016/j.cirpj.2025.11.007","url":null,"abstract":"<div><div>This paper introduces a prediction model for the three-dimensional (3D) geometry of multi-layer single-track (wall-deposition) workpieces in Wire Arc Additive Manufacturing (WAAM), enabling accurate predictions with minimal experimental effort. The model extends a prior single-bead prediction model by incorporating four key enhancements: (1) using multiple cross-sections to capture the full wall geometry, (2) integration of additional input parameters to account for thermal history and deposition sequence, (3) development of an improved geometric-characterization function for better representation of wall geometry, and (4) employing a hybrid dataset composed of synthetic and experimental datasets acquired without specialized equipment, such as in-process geometry measurement systems, thereby simplifying the data collection process. A two-step transfer learning strategy was employed to pretrain the model on a synthetic dataset and subsequently train it using an experimental dataset. This approach enables accurate predictions, even when only a limited amount of experimental data is available. Compared with baseline models without transfer learning, the developed model achieved a substantial reduction in prediction errors, averaging improvements between 5–30 %. Specifically, it attained an error of approximately 10 % for height predictions and 15 % for width predictions. These contributions enhance the adaptability and scalability of the WAAM processes, thereby enabling more efficient and precise manufacturing.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 1-14"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600531","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 : 2026-02-01Epub Date: 2025-11-28DOI: 10.1016/j.cirpj.2025.11.012
Hagen Klippel , Matthias Röthlin , Mohamadreza Afrasiabi , Michal Kuffa , Konrad Wegener
Determining material properties for machining simulations is challenging because direct measurement methods cannot reproduce the conditions of machining. Instead, an inverse parameter identification is used in this work to determine the material parameters for the Johnson-Cook model for Ti6Al4V (3.7165, Grade 5). A numerical simulation model using the smoothed particle hydrodynamics code mfree_iwf is used to recalculate an orthogonal cutting experiment. Due to GPU-acceleration the computational time is less than 5 min per simulation. Three different optimization algorithms (Simplex, Bayes, Differential Evolution) are used for the identification of the material parameters by minimizing the process force errors between experiment and simulation. Best results are obtained with the Differential Evolution algorithm. The sensitivity of material model parameters to the computed process force errors are shown and reveal for some of the material parameters adverse effects on these errors. Recomputations of experiments at different process conditions with the identified material parameters show good agreements in terms of process forces and the chip segmentation behaviour can be reproduced in high resolution simulations.
{"title":"Inverse identification of Johnson–Cook flow stress parameters for Ti6Al4V","authors":"Hagen Klippel , Matthias Röthlin , Mohamadreza Afrasiabi , Michal Kuffa , Konrad Wegener","doi":"10.1016/j.cirpj.2025.11.012","DOIUrl":"10.1016/j.cirpj.2025.11.012","url":null,"abstract":"<div><div>Determining material properties for machining simulations is challenging because direct measurement methods cannot reproduce the conditions of machining. Instead, an inverse parameter identification is used in this work to determine the material parameters for the Johnson-Cook model for Ti6Al4V (3.7165, Grade 5). A numerical simulation model using the smoothed particle hydrodynamics code <span><span>mfree_iwf</span><svg><path></path></svg></span> is used to recalculate an orthogonal cutting experiment. Due to GPU-acceleration the computational time is less than 5 min per simulation. Three different optimization algorithms (Simplex, Bayes, Differential Evolution) are used for the identification of the material parameters by minimizing the process force errors between experiment and simulation. Best results are obtained with the Differential Evolution algorithm. The sensitivity of material model parameters to the computed process force errors are shown and reveal for some of the material parameters adverse effects on these errors. Recomputations of experiments at different process conditions with the identified material parameters show good agreements in terms of process forces and the chip segmentation behaviour can be reproduced in high resolution simulations.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 15-31"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625225","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 : 2026-02-01Epub Date: 2025-12-13DOI: 10.1016/j.cirpj.2025.12.005
Edoardo Ghinatti , Toushiqul Islam , Shuaihang Pan , Rachele Bertolini , Stefania Bruschi
This study examines the influence of laser powder bed fusion (LPBF) layer thickness on the machinability of AlSi7Mg aluminum alloy. Samples fabricated with layer thicknesses of 20, 25, and 30 µm were heat-treated and then turned under fixed cutting parameters. The machinability was assessed in terms of cutting forces, surface roughness, and surface defects. Results showed that decreasing the layer thickness increased cutting forces and surface roughness, with the samples produced with a 20 µm layer thickness exhibiting the poorest machinability. The explanation of the lower machinability with decreasing layer thickness was associated with the microstructural and mechanical features characterizing the samples. At lower layer thickness, the microstructure is more anisotropic and ductile, leading to higher cutting forces and rougher surfaces. Contrarily, at greater layer thicknesses, the more uniform and less tough microstructure results in lower cutting forces and smoother surfaces. The presence of different Fe-rich intermetallics at different layer thicknesses also influences the morphology of the defects found on the machined surfaces. The findings highlight the importance of optimizing layer thickness to enhance the machinability of LPBF AlSi7Mg parts.
{"title":"Effect of layer thickness on the microstructure and machinability of AlSi7Mg processed by laser powder bed fusion","authors":"Edoardo Ghinatti , Toushiqul Islam , Shuaihang Pan , Rachele Bertolini , Stefania Bruschi","doi":"10.1016/j.cirpj.2025.12.005","DOIUrl":"10.1016/j.cirpj.2025.12.005","url":null,"abstract":"<div><div>This study examines the influence of laser powder bed fusion (LPBF) layer thickness on the machinability of AlSi7Mg aluminum alloy. Samples fabricated with layer thicknesses of 20, 25, and 30 µm were heat-treated and then turned under fixed cutting parameters. The machinability was assessed in terms of cutting forces, surface roughness, and surface defects. Results showed that decreasing the layer thickness increased cutting forces and surface roughness, with the samples produced with a 20 µm layer thickness exhibiting the poorest machinability. The explanation of the lower machinability with decreasing layer thickness was associated with the microstructural and mechanical features characterizing the samples. At lower layer thickness, the microstructure is more anisotropic and ductile, leading to higher cutting forces and rougher surfaces. Contrarily, at greater layer thicknesses, the more uniform and less tough microstructure results in lower cutting forces and smoother surfaces. The presence of different Fe-rich intermetallics at different layer thicknesses also influences the morphology of the defects found on the machined surfaces. The findings highlight the importance of optimizing layer thickness to enhance the machinability of LPBF AlSi7Mg parts.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 137-148"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748170","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 : 2026-02-01Epub Date: 2025-12-11DOI: 10.1016/j.cirpj.2025.12.003
Yusuf Altintas (Editor-in-Chief)
{"title":"Reviewers for CIRP journal of manufacturing science and technology, 2025","authors":"Yusuf Altintas (Editor-in-Chief)","doi":"10.1016/j.cirpj.2025.12.003","DOIUrl":"10.1016/j.cirpj.2025.12.003","url":null,"abstract":"","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Page 242"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884040","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 : 2026-02-01Epub Date: 2025-12-05DOI: 10.1016/j.cirpj.2025.12.001
Martina Panico , Ersilia Cozzolino , Antonello Astarita , Eva Begemann , Andreas Gebhardt , Luca Boccarusso
In the last decade improving the sustainability of manufacturing processes has become a primary objective to tackle the goals for sustainable development as defined by UN. In this context, the Life Cycle Assessment (LCA) is finding increasing use as a method to measure the environmental impacts of processes and as a tool to support decisions when a choice between different processing routes is required. The present study lies in this context: a detailed LCA analysis has been carried out to compare the environmental footprint of different drilling strategies, the quality of the drilled holes has also been considered to provide reliable guidelines to people interested in drilling operations. In particular, this study investigates the environmental impacts of different drilling strategies applied to CFRP/AA7075-T6 stacks, which are commonly used in structural aerospace assemblies. A cradle-to-gate LCA was performed to compare two main approaches: separate drilling of CFRP laminates and aluminium alloy sheets before their assembly, and one-shot drilling of pre-assembled stacks. A strength of this study, conversely to the others available in the literature, is that the analysis relies on experimental data for energy consumption, drilling forces and hole quality, enabling a high-fidelity environmental assessment. The results show that the drilling strategies significantly affect both the environmental indicators, process performance and hole quality, highlighting a trade-off between energy efficiency and hole characteristics. Findings offer new insight to guide sustainable decision-making in aerospace manufacturing.
{"title":"Towards sustainability in the aerospace industry: Environmental impact of different drilling strategies for CFRP/Aluminium stacks","authors":"Martina Panico , Ersilia Cozzolino , Antonello Astarita , Eva Begemann , Andreas Gebhardt , Luca Boccarusso","doi":"10.1016/j.cirpj.2025.12.001","DOIUrl":"10.1016/j.cirpj.2025.12.001","url":null,"abstract":"<div><div>In the last decade improving the sustainability of manufacturing processes has become a primary objective to tackle the goals for sustainable development as defined by UN. In this context, the Life Cycle Assessment (LCA) is finding increasing use as a method to measure the environmental impacts of processes and as a tool to support decisions when a choice between different processing routes is required. The present study lies in this context: a detailed LCA analysis has been carried out to compare the environmental footprint of different drilling strategies, the quality of the drilled holes has also been considered to provide reliable guidelines to people interested in drilling operations. In particular, this study investigates the environmental impacts of different drilling strategies applied to CFRP/AA7075-T6 stacks, which are commonly used in structural aerospace assemblies. A cradle-to-gate LCA was performed to compare two main approaches: separate drilling of CFRP laminates and aluminium alloy sheets before their assembly, and one-shot drilling of pre-assembled stacks. A strength of this study, conversely to the others available in the literature, is that the analysis relies on experimental data for energy consumption, drilling forces and hole quality, enabling a high-fidelity environmental assessment. The results show that the drilling strategies significantly affect both the environmental indicators, process performance and hole quality, highlighting a trade-off between energy efficiency and hole characteristics. Findings offer new insight to guide sustainable decision-making in aerospace manufacturing.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"64 ","pages":"Pages 92-106"},"PeriodicalIF":5.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694415","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}
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