International Journal of Machine Tools & Manufacture最新文献

{"title":"Micrometric orthogonal cutting can lead to sideway chip flow: Uncovering crystallographic orientation and grain boundary effects","authors":"Shusong Zan,&nbsp;Zhirong Liao,&nbsp;Jose A. Robles Linares,&nbsp;Kieran Winter,&nbsp;Dragos Axinte","doi":"10.1016/j.ijmachtools.2025.104363","DOIUrl":"10.1016/j.ijmachtools.2025.104363","url":null,"abstract":"<div><div>Micrometric cutting has attracted great research interest both in academic and industrial areas due to its vital role in microfabrication. Different from macro-cutting where many grains are involved in the process that averages/minimises the crystallographic effects, in micrometric cutting localised crystallographic deformation mechanisms can highly affect the machining results. However, experimental challenges of micrometric level cutting have confined most investigations to simulations or less-ideal tests (e.g. micro-scratching and single-point diamond turning), leaving the detailed interplay between chip flow and microstructure largely unexplored. In an apparent paradox, in orthogonal micrometric level cutting conditions, expected to yield forward (2D) chip flow, can produce pronounced sideway (3D) chip flow when grain-orientation anisotropy and boundary-induced kinematic constraints dominate; such aspects cannot be captured in macro-cutting. Based on these, when cutting at micrometric level it is important to understand how the slip system of the grains will be activated, what will happen when the grain boundary is encountered, as well as why the specific chip form and flow direction is generated under different conditions of these. To resolve this, grain orientations and boundaries were pre-characterised on a Ni-based superalloy sample, on which micrometric boss features were subsequently fabricated. Orthogonal grain-level cutting tests were then conducted on these structures, effectively isolating the deformation region, eliminating constraints from adjacent material, and allowing the chip to flow freely on both sides. Chip morphology, flow direction, and local deformation mechanisms were examined via advanced material characterisation technologies. Key findings that are specifically manifested at micro level include: The formation of serrated chips is influenced by the Schmid factor, resulting in variations in segment morphology across different crystallographic orientations. Sideway chip flow can be generated in micrometric orthogonal cutting process due to the selective activation of the slip-systems and inclined grain boundary guided sliding. Furthermore, when twin boundary exists, periodic extrusion-shear dominated material deformation cycle can happen in chip formation process due to the alternated stress. Therefore, we reveal for the first time that when cutting at grain levels, although geometrically defined orthogonal cutting was performed, the chip follows crystallographic rules imposed by slip planes and grain boundary conditions. These insights provide a new mechanistic framework for understanding micrometric level cutting anisotropy and the boundary-driven paradox of sideways chips, offering guidelines to optimise micrometric machining strategies in microfabrication applications.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"215 ","pages":"Article 104363"},"PeriodicalIF":18.8,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784995","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}

{"title":"Online time-optimal trajectory planning along parametric toolpaths with strict constraint satisfaction and certifiable feasibility guarantee","authors":"Yunan Wang,&nbsp;Chuxiong Hu,&nbsp;Yuanshenglong Li,&nbsp;Jichuan Yu,&nbsp;Jizhou Yan,&nbsp;Yixuan Liang,&nbsp;Zhao Jin","doi":"10.1016/j.ijmachtools.2025.104355","DOIUrl":"10.1016/j.ijmachtools.2025.104355","url":null,"abstract":"<div><div>As a fundamental technique in computer numerical control (CNC) machining, time-optimal trajectory planning (TOTP) is crucial for enhancing machining efficiency, geometric accuracy, and surface quality. However, it remains challenging to reliably generate smooth time-optimal trajectories online, particularly under complex constraints. This study aims to address the above longstanding challenges which limit the reliability and efficiency of online optimization-based TOTP approaches, thereby unlocking their practical advantages in real-world machining. A TOTP method along parametric toolpaths, namely TOTP-SPLP, is developed. The proposed piecewise linear objective function and sequential procedure improve time-optimality and avoid singularities at zero feedrate compared with existing linear formulations. Complex constraints are strictly satisfied at grid points over the entire toolpath without relying on static approximations, where exceedance between grid points is negligible and theoretically bounded by the grid density based on the developed analytical interpolation. To certifiably guarantee the feasibility during online TOTP, a hierarchical look-ahead windowing (HLAW) framework is established, which achieves a 100% success rate of optimization feasibility for long toolpaths. Simulation and real-world experiments demonstrate that the proposed TOTP-SPLP significantly outperforms existing online TOTP baselines in terms of time-optimality and numerical stability within limited computational cost. Specifically, TOTP-SPLP reduces terminal time by 15.6%–56.0% compared with baselines of lower computational cost, and outperforms more computationally expensive baselines by 9.5%. Comparable performance to our TOTP-SPLP is achieved by offline baselines only when consuming tenfold computational time. For a long toolpath with millions of grid points, the developed HLAW reduces the thousands of infeasibility cases encountered by existing online framework to zero. The strict satisfaction of complex constraints helps suppress vibrations and improve surface quality in real-world machining. In summary, this work fundamentally advances online TOTP by achieving offline-level time-optimality with certifiable feasibility under strict complex constraints, making reliable online optimization-based TOTP possible and practical in CNC machining.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"215 ","pages":"Article 104355"},"PeriodicalIF":18.8,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784998","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}

{"title":"Process-driven microstructure design of 3D-Printed porous magnesium alloy scaffolds with tunable biodegradation kinetics","authors":"Weiyun Xu ,&nbsp;Hualuo Pang ,&nbsp;Haojing Xu ,&nbsp;Jinge Liu ,&nbsp;Yufeng Zheng ,&nbsp;Peng Wen","doi":"10.1016/j.ijmachtools.2025.104362","DOIUrl":"10.1016/j.ijmachtools.2025.104362","url":null,"abstract":"<div><div>3D-printed biodegradable magnesium (Mg) alloy scaffolds are emerging as promising candidates for customized bone implants, offering tailored structure, mechanical performance, and bioactive functions to address diverse bone defects. However, the premature loss of structural integrity remains a critical challenge for clinical applications due to the complex kinetics of biodegradation. This study posits that the tunability of degradation, inherently governed by microstructure, is rooted in the 3D printing and heat treatment processes, which have been underexplored and lack scientific understanding. Using a process-driven microstructural design approach, we investigated how manufacturing influence the corrosion behavior of porous Mg alloy scaffolds. By analyzing the combined effects of layer thickness on microstructural evolution in laser powder bed fusion and high-temperature oxidation heat treatment, it was revealed that the as-printed microstructural features, governed by the printing parameters, exert a critical influence on the biodegradable performance after heat treatment. Comprehensive evaluations of fusion quality, mechanical responses, electrochemical properties, and immersion degradation behavior further indicated that the multi-level heterogeneous microstructure, formed by local elemental migration, anisotropic grain growth, and the development of layered oxide films, was identified as the key factor in regulating degradation. Our findings highlight a synergistic manufacturing-dominant mechanism for tuning biodegradation kinetics through control of microstructure, resulting in porous Mg alloy scaffolds with significantly improved durability. These advancements not only provide a pathway for developing high-performance 3D-printed biodegradable bone implants but also establish a generalized framework for fabricating reactive materials with intricate geometries and tailored functionalities.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"215 ","pages":"Article 104362"},"PeriodicalIF":18.8,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731185","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}

{"title":"Martensitic transformation sensitivity–driven processing roadmap for laser powder bed fusion of NiTi shape memory alloys: Paradigm shift from defect elimination to precise performance control","authors":"Dan Zheng ,&nbsp;Ruidi Li ,&nbsp;Jingtao Kang ,&nbsp;Tiechui Yuan ,&nbsp;Kefu Gan","doi":"10.1016/j.ijmachtools.2025.104352","DOIUrl":"10.1016/j.ijmachtools.2025.104352","url":null,"abstract":"<div><div>Laser powder bed fusion (LPBF) fabricated NiTi shape memory alloys (SMAs) fabricated to comparably high density using different processing parameters can exhibit significant differences in martensitic transformation temperature (MTT) (differing by &gt; 50 °C), altering their functional performance and making precise performance control challenging. Herein, we establish a simple but generalisable law, <strong><em>E</em>_<em>L</em></strong>/<strong><em>v</em></strong> (where <strong><em>E</em>_<em>L</em></strong> and <strong><em>v</em></strong> denote linear energy density and scan velocity, respectively), which governs densification and martensitic transformation behaviours in LPBF-processed Ni-rich NiTi SMAs. MTT sensitivity was introduced as a process evaluation metric, shifting the paradigm from conventional defect-centric frameworks toward performance-oriented optimisation. A parameter-dependent and universal vaporisation model is established by systematically decoupling the roles of energy input in MTT. Results demonstrate that Ni loss and MTT sensitivity depend on <strong><em>E</em>_<em>L</em></strong>/<strong><em>v</em></strong> rather than on <strong><em>E</em>_<em>L</em></strong>, with ∼0.67 at.% Ni loss per kJ·s·m⁻² and a linear increase in the martensite start (<strong><em>M</em>_<em>S</em></strong>) temperature of ∼83 K. Microstructural analyses confirm that <strong><em>E</em>_<em>L</em></strong>/<strong><em>v</em></strong> governs melt pool overlap, mode stability and microstructural and transformational homogeneity. It is revealed that the amount of input energy density (e.g. <strong><em>E</em>_<em>L</em></strong>) dictates melt pool geometry and densification, while the manner of input energy density (e.g. normalised input energy density rate, <strong><em>E</em>_<em>L</em></strong>/<strong><em>v</em></strong>) governs melt pool dynamics, elemental vaporisation and microstructure evolution. This dual-criterion rationalises the <strong><em>M</em>_<em>S</em></strong> temperature variability observed under identical energy densities and enables predictive control of transformation features, residual stress and precipitation. The proposed framework delivers NiTi components with superior tensile elongation (∼22 %), surpassing that of most LPBF-processed Ni-rich counterparts. Moreover, its universality is validated in 304L stainless steel and CuAlMn SMA, underscoring its applicability beyond NiTi SMAs. This study offers mechanistic insights into processing–melt pool dynamics–structure–property interactions and offers a universal roadmap for LPBF parameter design, advancing process optimisation beyond defect mitigation and enabling precise performance control through melt pool management.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"214 ","pages":"Article 104352"},"PeriodicalIF":18.8,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657706","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}

{"title":"Surface and subsurface evolution mechanism in continuous wave laser ablation process of Cf/SiC ceramic matrix composites: A multiscale investigation","authors":"Dongdong Xu ,&nbsp;Tiancheng Ai ,&nbsp;Guojian Yang ,&nbsp;Shusong Zan ,&nbsp;Zhirong Liao","doi":"10.1016/j.ijmachtools.2025.104354","DOIUrl":"10.1016/j.ijmachtools.2025.104354","url":null,"abstract":"<div><div>Due to the excellent material properties, ceramic matrix composites (CMCs) are increasingly favored in aerospace and other high-performance applications. As the industry advances, both the reinforcement and matrix materials tend to be more difficult to machine. Laser-based processing methods are becoming increasingly popular. However, the underlying mechanisms and the formation of surface integrity in such complex materials remain unclear. At present, the overall ablation process of complex CMCs has not been studied. To address these gaps, this study investigates the surface integrity induced by laser ablation and its underlying mechanisms of CMCs. The results reveal that post-ablation surface morphologies vary significantly across different regions of Cf/SiC CMCs—those with vertically oriented fibers, where the height is relatively high, and those with horizontally oriented fibers, where the height is comparatively low. At a scanning speed of 400 mm/min, the laser energy corresponding to a power of 3 kW can be regarded as the threshold between rough and fine machining. It was further clarified that the spherical particles formed on the ablated surface were composed of elemental silicon rather than the commonly assumed oxides. The surface region exhibited a loose four-layer structure consisting of silica, elemental silicon, silicon carbide, and a pyrolytic carbon layer. In addition, a typical multi-layered surface structure—arising from the superior thermal conductivity of the fibers—was also observed on the surfaces of fibers located within the subsurface region of the workpiece. A model of the temperature distribution was established to elucidate how differences in thermal conduction induced by fiber orientation influence the ablated surface morphology of the CMC. Overall, these findings comprehensively explain the ablation process, surface integrity evolution, and underlying mechanisms of CMCs subjected to laser ablation.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"214 ","pages":"Article 104354"},"PeriodicalIF":18.8,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609026","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}

{"title":"Model-based design of strength–toughness synergy for additively manufactured layered heterostructured metallic materials","authors":"Jianglong Wang ,&nbsp;Haihong Huang ,&nbsp;Yu Kong ,&nbsp;Zhifeng Liu","doi":"10.1016/j.ijmachtools.2025.104353","DOIUrl":"10.1016/j.ijmachtools.2025.104353","url":null,"abstract":"<div><div>The inherent contradiction between strength and toughness in additively manufactured metallic materials can be coordinated through a layered heterostructured design, which tailors the distribution of two dissimilar materials. To quantitatively describe the strength and toughness of heterostructured metallic materials, a strength–toughness coupling mechanical model for layered heterostructures was established according to the weight function principle in this research. On this basis, a laser interface remelting (LIR) process was initially developed; then, after evaluating the metallurgical compatibility, the layered heterostructures of IN718/316L bimetallic materials were fabricated by the laser-directed energy deposition (LDED) technology. The results manifested that this LIR process could synthesize composition transition zones in situ, ensuring a controllable bonding quality for the heterostructured interface. The modelling also exhibited that the toughness of heterogeneous metal layered structures decreased with the increase in strength, and there was an emblematic trade-off between strength and toughness. Additionally, the two toughening mechanisms were discussed in terms of hindering crack nucleation and shielding strain spread. Furthermore, it was found that the matching form of the layer thickness with “more hard and less soft” could induce sub-critical cracks on the surface, and activate the extra strengthening potential. Ultimately, a new approach to determining the layer thickness ratio of layered heterostructures by the modelling calculation was proposed, and the process feasibility of additive manufacturing following this model-based design was also confirmed via a case study. This method of synergistic regulation could provide effective guidance for the on-demand optimization of strength–toughness aimed at heterostructured metallic materials.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"214 ","pages":"Article 104353"},"PeriodicalIF":18.8,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145553533","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}

{"title":"AI-powered semiconductor wafer fabrication: A manufacturing paradigm shift","authors":"Guanwei He ,&nbsp;Qingqing Huang ,&nbsp;Xinhao Li ,&nbsp;Libo Zhou ,&nbsp;Miao Yang ,&nbsp;Yadan Luo ,&nbsp;Marian Wiercigroch ,&nbsp;Han Huang","doi":"10.1016/j.ijmachtools.2025.104345","DOIUrl":"10.1016/j.ijmachtools.2025.104345","url":null,"abstract":"<div><div>Artificial intelligence (AI) is reshaping the landscape of modern manufacturing by enabling intelligent, adaptive, and increasingly autonomous production systems. In high-end manufacturing processes, persistent challenges such as complex machine-tool dynamics, variability in equipment performance, and environmental instabilities hinder consistent quality and high efficiency. These challenges are further amplified in advanced manufacturing domains, particularly in semiconductor wafer fabrication, which demands ultra-high precision to be attained. AI offers powerful solutions to these challenges through its capability in real-time decision making, data driving modelling, and predictive analysis of manufacturing processes. By learning from vast datasets generated during manufacturing, AI systems can identify working patterns, optimize process parameters, detect anomalies, and guide autonomous control strategies. These advantages position AI as a key enabler for enhancing process understanding, ensuring quality assurance, and accelerating innovation in fabrication technologies. Semiconductor wafer fabrication is the cornerstone of modern electronics manufacturing, serving as the foundation process for integrated circuits production. This article reviews the transformative role of AI in wafer fabrication, highlighting its principles, applications, and prospects. Key AI technologies such as deep learning, reinforcement learning, and generative algorithms that have been widely adopted in wafer fabrication are surveyed. Special attention is given to their deployment across critical fabrication procedures including crystal growth, ingot slicing and ultraprecision machining. The review further presents state-of-the-art research and industrial implementations of AI in these domains, showcasing how intelligent models can be employed in quality prediction, regime classification, process optimization, and system control. Finally, emerging trends and future perspectives aimed at fostering more practical, deeply integrated, and robust AI applications across the manufacturing ecosystem are discussed, paving the way toward fully autonomous and self-optimizing future manufacturing processes.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"214 ","pages":"Article 104345"},"PeriodicalIF":18.8,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461562","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}

{"title":"Machine learning applications in welding processes: Progresses and opportunities","authors":"Peihao Geng ,&nbsp;Yujun Xia ,&nbsp;Zhiqiao Dong ,&nbsp;Boxuan Men ,&nbsp;Bo Pan ,&nbsp;Chenhui Shao ,&nbsp;Yongbing Li ,&nbsp;Jingjing Li","doi":"10.1016/j.ijmachtools.2025.104344","DOIUrl":"10.1016/j.ijmachtools.2025.104344","url":null,"abstract":"<div><div>The increasing demand for intelligent and autonomous manufacturing has driven the integration of machine learning (ML) into modern welding processes. Owing to its ability to model nonlinear and cross-scale interactions and extract critical features from complex, high-dimensional data, ML is rapidly transforming the design, monitoring, and evaluation of welding processes. Based on this, the paper systematically reviews research progress in ML for four representative welding processes (arc, laser, resistance and friction stir welding) over the past decade. First, typical welding tasks are categorized into three domains: pre-weld design, in-process monitoring, and post-weld quality assessment. It then elaborates on the types of welding data used and their input-output relationships across different tasks and analyzes the architecture and algorithmic characteristics of mainstream ML models. Cross-process comparison reveals that the physical nature of each welding process determines the focus of ML research, model selection, and performance metrics. The study quantitatively compares the task-specific metrics of various models and presents successful industrial application cases. Despite significant progress, challenges persist in constructing high-quality and standardized datasets, improving model interpretability and generalization, and achieving robust real-time control in dynamic industrial environments. Based on the summarized emerging challenges, the perspectives on further development direction of applying ML in intelligent welding are also discussed.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"213 ","pages":"Article 104344"},"PeriodicalIF":18.8,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145434318","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}

{"title":"Insights into the strengthening mechanisms of titanium alloy treated by electropulsing-assisted ultrasonic nanocrystal surface modification: Process, microstructure, and deformation behavior","authors":"Yu Zhang ,&nbsp;Weidong Zhao ,&nbsp;Yixuan Ye ,&nbsp;Xiao Jia ,&nbsp;Yalin Dong ,&nbsp;Han Ding ,&nbsp;Jian Wang ,&nbsp;Chang Ye","doi":"10.1016/j.ijmachtools.2025.104343","DOIUrl":"10.1016/j.ijmachtools.2025.104343","url":null,"abstract":"<div><div>Ultrasonic nanocrystal surface modification (UNSM) properly improves fatigue resistance but shows limited processing efficiency on hard-to-deform alloys such as Ti6Al4V due to their high deformation resistance. This study employs an emerging electropulsing-assisted UNSM (EP-UNSM) approach that integrates pulsed current with conventional UNSM to improve strengthening efficiency and associated surface integrity. However, strain localization-induced nanocrystalline plastic instability may lead to fatigue deterioration under low cycle fatigue regimes. To clarify these aspects, systematic microstructure characterization and mechanical testing were conducted to determine the pathways by which EP-UNSM alters plastic deformation and fatigue strengthening mechanisms. Results reveal that, unlike the planar dislocation slip induced by limited plastic deformation in conventional UNSM, EP-UNSM activates pronounced non-basal dislocations and wavy slip patterns, thereby improving the plasticity and producing a deeper gradient nanostructure layer. Moreover, a dynamic electro-annealing mechanism is proposed that involves the synergistic reconfiguration of metastable dislocations and nanocrystals, forming periodic dislocation cells in EP-UNSM samples, in contrast to the sharp triple-junction grain boundaries observed in conventional UNSM. This microstructure evolution mitigates stress concentration at grain boundaries and enhances compressive residual stress stability, ultimately improving fatigue resistance across all stress regimes. These findings advance understanding of electropulsing-assisted deformation and guide anti-fatigue manufacturing strategies for titanium alloys and other hard-to-deform metals.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"213 ","pages":"Article 104343"},"PeriodicalIF":18.8,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145396509","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}

{"title":"Real-time capable feedrate optimization for laser processes with redundant axes via two-stage regularized linear programming","authors":"Haijia Xu ,&nbsp;Daniel Kurth ,&nbsp;Christoph Hinze ,&nbsp;Claudius Horsch ,&nbsp;David Hecht ,&nbsp;Alexander Verl","doi":"10.1016/j.ijmachtools.2025.104342","DOIUrl":"10.1016/j.ijmachtools.2025.104342","url":null,"abstract":"<div><div>Galvanometer scanners offer high dynamics and precision for laser processes, but are limited in their workspace. To expand the workspace, the galvanometer scanner can be integrated into a larger mechanical motion system with redundant axes, including slow mechanical axes and fast scanner axes. While this configuration provides additional degrees of freedom in feedrate planning, conventional Computerized Numerical Control (CNC)-based laser machining systems cannot exploit them effectively, resulting in suboptimal finishing times. This paper introduces the first real-time capable, optimization-based approach to the minimum-time planning problem under motion redundancy, considering limits in redundant axes and toolpath dynamics up to the third order. This is achieved by decoupling the nonlinear problem into two linear problems and introducing a sequential windowing and adaptive scaling strategy, which allows the toolpath to be scaled to arbitrary lengths. Additionally, a new numerical approximation of the transformation between axis and Cartesian coordinates is introduced. This allows for optimization without arc-length parameterization and simplifies the previous toolpath geometry processing. The constraint feasibility and computational efficiency of the proposed optimization method are validated using spline toolpaths. On a desktop PC with single-core execution, the computation time remains well below the actual processing time at around 10 %, showing linear scalability with respect to toolpath length. Experiments on two different laser machines equipped with redundant axes further validate the planning performance and computational robustness when following freeform contours with up to <span><math><mrow><mn>10</mn><mspace></mspace><mn>000</mn></mrow></math></span> constraint checkpoints. Compared to an industrial CNC-guided solution based on S-curve motion profiles, the proposed optimization algorithm reduces the finishing time by around 30 % in experiments with and without jerk constraints.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"213 ","pages":"Article 104342"},"PeriodicalIF":18.8,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145359368","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}