CIRP Journal of Manufacturing Science and Technology最新文献

{"title":"Influence mechanism of tool pin profile on heat transfer and material flow behavior in friction stir welding of aluminum alloys","authors":"Fanqi Yu,&nbsp;Shujun Chen,&nbsp;Tao Yuan,&nbsp;He Shan,&nbsp;Pengjing Zhao","doi":"10.1016/j.cirpj.2025.10.001","DOIUrl":"10.1016/j.cirpj.2025.10.001","url":null,"abstract":"<div><div>The design of the tool pin is a critical factor influencing weld quality and material flow behavior in friction stir welding (FSW). This study employs a Coupled Eulerian-Lagrangian (CEL) thermo-mechanical model to systematically investigate the effects of tool pin taper angle on thermal cycles, plastic strain, and material flow during FSW of Al alloys. The model integrates interfacial friction heating, viscoplastic constitutive behavior, and thermomechanical contact conditions. Experimental validation was conducted through thermocouple-based temperature measurements and macrostructural analysis of weld cross-sections. Results indicate that larger taper angles enhance longitudinal thermal gradients and promote lateral heat dissipation, leading to a wider thermomechanically affected zone (TMAZ). A 0° taper angle induces significant adhesive friction and intense material flow, while a 60° taper reduces flow velocity near the pin tip. With increasing taper angle, plastic strain transitions from a uniform distribution to a concentrated region on the advancing side (AS) of the stir zone (SZ), where peak plasticity occurs. Conversely, deformation near the pin root is suppressed. These insights offer a theoretical basis for optimizing tool geometry to control heat distribution and material flow, improving weld quality in engineering applications.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 299-309"},"PeriodicalIF":5.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268938","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}

{"title":"Towards digital twin-enhanced control policies: A knowledge-based classification of release and dispatching policies in manufacturing systems","authors":"Marcello Urgo ,&nbsp;Walter Terkaj ,&nbsp;Lei Liu","doi":"10.1016/j.cirpj.2025.08.006","DOIUrl":"10.1016/j.cirpj.2025.08.006","url":null,"abstract":"<div><div>The management of modern discrete manufacturing systems is challenged by high levels of complexity arising from intricate interdependencies among processes and the need to adapt to frequent internal and external disruptions. In this context, control policies play a pivotal role in managing manufacturing operations, guiding decisions for governing systems and optimising their performance. This study investigates the design and classification of release and dispatching policies based on the type and structure of information they require, with particular emphasis on supporting real-time and adaptive decision-making. This analysis takes advantage of the concept of Digital Twin (DT), tightly integrated with the physical manufacturing system via IIoT technologies, enabling continuous monitoring of operations in a factory, but also forward-looking simulation of system behaviour. The proposed classification leverages an ontology-based data model that formalises the structure of manufacturing knowledge and facilitates the systematic identification of the information required by control policies. The classification scheme incorporates both the informational requirements and the potential role of the DT in supporting their execution and the results provide a structured perspective on how control strategies can be aligned with available data and digital infrastructure to enhance the management of manufacturing systems.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 310-335"},"PeriodicalIF":5.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268930","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}

{"title":"Synergistic effects of ultrasonic vibration and nanofluid-MQL on surface integrity in sustainable machining of Ti-6Al-7Nb alloy","authors":"Erkin Duman ,&nbsp;Yusuf Furkan Yapan ,&nbsp;Alper Uysal","doi":"10.1016/j.cirpj.2025.09.017","DOIUrl":"10.1016/j.cirpj.2025.09.017","url":null,"abstract":"<div><div>Recent trends in the biomedical industry emphasize improving the surface properties of materials for better biocompatibility. Consequently, various surface modification techniques, including machining, are used on titanium bioimplants. This study investigates the impact of sustainable machining on the surface integrity of the Ti-6Al-7Nb biomedical alloy under various cutting conditions including conventional dry cutting, minimum quantity lubrication (MQL), graphene nanofluid-based MQL (N-MQL), and ultrasonic vibration-assisted machining (UVA), encompassing UVA-DRY, UVA-MQL, and UVA-N-MQL. The focus is to analyze the relationship between machining performance and surface integrity. Machining experiments first evaluated cutting forces, cutting temperatures, and chip morphology. Then, surface roughness, texture, microstructural changes, microhardness, and phase transformation were examined to assess surface integrity. The findings reveal that the UVA-N-MQL significantly reduces cutting forces (by up to 6 % for main cutting force and 10.4 % for thrust force) and cutting temperatures (by up to 29 % compared to dry cutting), while enhancing chip breakability. These outcomes stem from the synergistic interaction between the ultrasonic softening effect induced by high-frequency tool oscillations and the enhanced coolant/lubricant penetration enabled by N-MQL lubrication. Additionally, surface roughness was minimized by up to 57 % with UVA-MQL, resulting in the smoothest surface finish. Microstructure analysis also indicated that dry cutting produced the deepest deformation layer (29.5 µm), while UVA-N-MQL achieved the shallowest affected zone (9.5 µm). Subsurface hardness exhibited a notable increase within a depth range of 60–80 µm, with dry cutting demonstrating the most significant work hardening (a 12 % increase), in contrast to UVA-MQL, which experienced the least. Phase transformation analysis revealed a significant increase in the β phase ratio due to machining, with conventional turning exhibiting higher transformation than UVA machining. The UVA-N-MQL method resulted in 10.4 % less phase transformation compared to conventional dry cutting.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 281-298"},"PeriodicalIF":5.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221726","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}

{"title":"Phenomena and mechanisms in plasma-enhanced jet electrochemical machining","authors":"Haowei Zhang,&nbsp;Ningsong Qu","doi":"10.1016/j.cirpj.2025.09.016","DOIUrl":"10.1016/j.cirpj.2025.09.016","url":null,"abstract":"<div><div>This study presents a novel plasma-enhanced jet electrochemical machining (PE-JEM) method designed to improve the electrochemical machining performance while maintaining process stability. In jet electrochemical machining, the electrolyte jet usually exhibits free flow after increasing the inter-electrode gap, which leads to the natural formation of an air film between the electrode end face and the electrolyte. The high-speed imaging reveals the generation process and locations of plasma generation within the air film, with multiple plasma channels appearing simultaneously at different positions. The current and voltage signals demonstrate the periodic enhancement effect of the plasma, with the anode current density increasing approximately 2.7 times during plasma generation. Notably, the plasma generated in this method does not result in material wear at the tool electrode, ensuring process stability. The jet electrochemical machining experiment confirms significant performance improvements, with a 34.7 % increase in material removal rate and a 48 % increase in groove aspect ratio compared to conventional methods. When the electrode end surface was insulated to suppress plasma generation, the material removal rate and groove aspect ratio declined significantly. These findings highlight plasma-enhanced electrochemical machining as a highly efficient and stable technique for precision manufacturing applications.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 265-280"},"PeriodicalIF":5.4,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159331","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}

{"title":"Contribution to the analytical determination of uncut chip thickness for cutting force modelling in milling with refinements for high-feed milling","authors":"Thomas Jacquet,&nbsp;Jean-Baptiste Guyon,&nbsp;Fabien Viprey,&nbsp;Guillaume Fromentin,&nbsp;David Prat","doi":"10.1016/j.cirpj.2025.09.001","DOIUrl":"10.1016/j.cirpj.2025.09.001","url":null,"abstract":"<div><div>In modern manufacturing, accurately predicting cutting forces is essential for the design and control of machining operations. Common mechanistic models of cutting forces rely on a precise description of the local uncut chip area. However, in milling, the specific trajectories of cutting edges create challenges in modelling this quantity. Existing analytical models are typically limited to 2D contexts or assume circular tooth trajectories, which are mostly valid for cylindrical end mills. These assumptions limit their applicability to high-feed milling, especially due to low lead angles and complex insert cutter geometries producing non-circular paths. This article presents a new three-dimensional analytical model for evaluating the local uncut chip thickness in high-feed milling. It relies on closed-form expressions derived from geometric analysis and Taylor expansions to approximate the uncut chip area and cutter-workpiece engagement, even in regions where conventional models fail. The model applies to linear-path milling and accounts for tool run-out and differential pitch. Compared to a Newton–Raphson numerical method, it achieves a relative error below 5% while being 3 to 9 times faster, enabling efficient integration in force models. Beyond its computational efficiency, the explicit formulation enables analysis of geometric influence, such as sensitivity to feed per tooth or tooth count-capabilities not easily accessible with purely numerical approaches. This work contributes a rigorous and interpretable alternative for improving cutting force prediction in high-feed milling.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 240-264"},"PeriodicalIF":5.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159330","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}

{"title":"Dynamic decision-making on the number and selection of measurement markers for stochastic control of overlay errors in photolithography","authors":"Yangmeng Li ,&nbsp;Huidong Zhang ,&nbsp;Noah Graff ,&nbsp;Roberto Dailey ,&nbsp;Dragan Djurdjanovic","doi":"10.1016/j.cirpj.2025.09.008","DOIUrl":"10.1016/j.cirpj.2025.09.008","url":null,"abstract":"<div><div>Accurate multilayer overlay alignment in photolithography is critical for semiconductor manufacturing. It is crucial to use a limited number of measurement markers to ensure the throughput while maintaining the overlay estimation and control accuracy. This work presents a novel optimization framework for dynamically down-selecting overlay measurement markers. The framework employs a stochastic multilayer control algorithm for tractable real-time control and select an optimal subset of markers that maximize overlay error estimation accuracy. The optimal marker number is determined by maximizing an objective that balances production quality and throughput. Industrial evaluation in a 300 mm fab demonstrates substantial cost-benefit improvements over traditional Run-to-Run control, highlighting enhanced process efficiency and yield.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 227-239"},"PeriodicalIF":5.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159467","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}

{"title":"Similarity-based anomaly detection method for turning of multi-material workpieces with varying axially constant blank diameter","authors":"Berend Denkena,&nbsp;Benjamin Bergmann,&nbsp;Henning Buhl,&nbsp;Miriam Handrup","doi":"10.1016/j.cirpj.2025.09.014","DOIUrl":"10.1016/j.cirpj.2025.09.014","url":null,"abstract":"<div><div>Geometry and hardness fluctuations of formed blanks are challenging for process monitoring of the subsequent machining process because they lead to deviating process forces during roughing. Ordinary anomaly detection methods require the forces to be similar. In this work, a similarity-based anomaly detection method is proposed that utilizes Dynamic Time Warping to achieve robustness against blank fluctuations during roughing. It extracts the average signal shape from training signals, scales it individually for each novel process, and uses confidence limits for anomaly detection. The method is tested with multi-material shafts whose blank diameter is axially constant but varies between workpieces.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 205-213"},"PeriodicalIF":5.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159328","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}

{"title":"Free abrasive assisted magnetorheological polishing: Device design and processing performance analysis","authors":"Yakun Yang,&nbsp;Mingming Lu,&nbsp;Jieqiong Lin,&nbsp;Yongsheng Du","doi":"10.1016/j.cirpj.2025.09.015","DOIUrl":"10.1016/j.cirpj.2025.09.015","url":null,"abstract":"<div><div>The processing stability and properties of magnetorheological polishing device (MPD) play a crucial role in the processing of optical materials. In this study, a novel MPD was developed to improve the processing stability and properties. The device uses free abrasives to assist in magnetorheological polishing, and completes the self-sharpening of the abrasives in flexible pad using a dynamic magnetic field. This paper presents the principles and structures design involved. The mechanical characteristics of main components and magnetic field characteristics of a Halbach array were analyzed. Based on the developed device, the stability is studied. The advantages of free abrasive assisted magnetorheological polishing method were investigated. The results indicate that the structural design of the main components is reasonable. A dynamic magnetic field device can achieve greater changes in magnetic field intensity and gradient with fewer magnets. It exhibits excellent magnetic field properties. The results obtained by marathon experiment under the same parameters are all distributed within 95 % confidence interval. The processing stability of the MPD was verified. The method can effectively improve the processing performance and has certain advantages. Compared with the traditional magnetorheological polishing method, the processing efficiency can be improved by more than 29.68 %.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 214-226"},"PeriodicalIF":5.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159329","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}

{"title":"Fatigue failure mechanism of gradient nanostructured materials produced by turning","authors":"Lihua He,&nbsp;Jinhui Zhou,&nbsp;Bokai Lou,&nbsp;Jing Ni,&nbsp;Xiaoping Hu","doi":"10.1016/j.cirpj.2025.09.013","DOIUrl":"10.1016/j.cirpj.2025.09.013","url":null,"abstract":"<div><div>Most safety-critical components and load-bearing structures continue to be manufactured using hard turning, a process that induces gradient nanostructures (GNS) in the surface layer. To investigate the effect of GNS layer on fatigue properties, crystal plasticity finite element model (CPFEM) and ± 0.8 % strain fatigue test were used in this study. The objectives were to investigate the correlation between turning parameters and surface GNS layer of 316 L stainless steel, and to reveal the fatigue failure mechanism of GNS layer from multiple scales. The results show that the turning parameters significantly influence the thickness of the GNS layer, with turning depth having the greatest impact, followed by cutting speed. CPFEM simulations predict stress distribution within the GNS layer across regions with varying grain sizes. stresses in fine-grained regions are primarily concentrated at grain boundaries, whereas stresses in coarse-grained regions are distributed within the grains. The model predictions of fatigue crack locations closely align with stress concentration distributions. Fatigue testing reveals that cracks in the GNS layer primarily propagate intergranular boundaries, while cracks in the coarse-grained (CG) layer exhibit both intergranular and transgranular extensions. This behavior mirrors the damage patterns predicted by simulation, demonstrating the model's high accuracy.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 156-169"},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120889","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}

{"title":"Interpretable generative machine learning model based in-situ process monitoring in robotic wire arc based directed energy deposition of aluminum alloys","authors":"Deepak Kumar,&nbsp;Sunil Jha","doi":"10.1016/j.cirpj.2025.08.010","DOIUrl":"10.1016/j.cirpj.2025.08.010","url":null,"abstract":"<div><div>WA-DED using CMT is emerging as a high-throughput metal AM strategy, yet it remains susceptible to a variety of thermomechanical instabilities and metallurgical discontinuities. In this study, we present an advanced AE based in-situ monitoring utilizing the generative ML framework to robustly detect and characterize anomalous conditions that compromise part integrity. Specifically, we examine five critical fault scenarios which are overcurrent, high travel speed, insufficient shielding gas flow, combination of overcurrent and low shielding gas flow rate and combination of high travel speed and low shielding gas flow rate elucidate their distinct signatures in the acoustic domain. A rigorous selection of time and frequency domain descriptors is leveraged to train the variational autoencoder, enabling accurate reconstruction of normal process states and efficient outlier detection. Microstructural analyses, encompassing FESEM, Micro-CT, and XRD, validate the detrimental influence of these faults on porosity evolution, grain morphology, and mechanical properties such as UTS. The proposed VAE model demonstrated robust performance across multiple defect types, achieving peak detection accuracies of 87% for overcurrent-induced faults, 85% for high travel speed anomalies, 81% for defects caused by insufficient shielding gas flow, 87% for combined effect of overcurrent and low gas flow rate, and 84% for combined effect of high travel speed and low gas flow rate. Overcurrent anomalies induce coarse columnar grains and high porosity content, while high travel speed amplifies geometric irregularities. Low gas flow conditions foster oxidation induced porosity. The proposed approach achieves high fidelity in detection of these defects, underscoring the synergy between data driven reconstruction errors and material characterization. By integrating unsupervised generative deep learning with domain specific interpretability through feature sensitivity analysis, this acoustic monitoring paradigm provides a scalable and cost effective pathway to detect defects and ensure structural reliability in WA-DED manufactured components. The comprehensive experimental validations and multi-physics correlational insights position this framework as a robust framework for in-situ process monitoring in WA-DED.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"63 ","pages":"Pages 185-204"},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120891","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}