Journal of Manufacturing Processes最新文献

{"title":"Influences of impact loading rate on the protective effect of shims on breakage of inserts in intermittent cutting","authors":"Yonglong Liu,&nbsp;Guosheng Su,&nbsp;Yan Xia,&nbsp;Hongxia Zhang,&nbsp;Gaofeng Wei,&nbsp;Yujing Sun,&nbsp;Binxun Li,&nbsp;Peirong Zhang,&nbsp;Jin Du,&nbsp;Bin Fang","doi":"10.1016/j.jmapro.2025.03.096","DOIUrl":"10.1016/j.jmapro.2025.03.096","url":null,"abstract":"<div><div>In high-speed cutting, the shim-insert system is subjected to high-speed impact loads, and different stiffness of the shim-insert system exhibit varying impact responses at different load rates, which in turn affect the wear and damage of the inserts. This paper investigates the effect of load impact rate on the protective performance of weak stiffness shims. A mass-spring vibration model for the shim-insert system is established to analyze the effect of load rate on the inertial forces within the system. Finite element analysis is conducted to explore the influence of impact load rate on the stress distribution at the tool tip for four different shim stiffness levels. Additionally, intermittent cutting experiments using four different stiffness shims are performed to study the impact of load rate on cutting forces, vibration acceleration, and insert fracture under different cutting speeds (load rates). The results show that as the impact load rate increases, the protective effect of weak stiffness shims on the inserts gradually weakens. At low impact load rates, the shim reaction force dominates, and the inertial force of the insert can be neglected. As the load rate increases, the inertial force of the insert increases and becomes dominant, while the shim reaction force gradually diminishes. As the cutting speed increases (from 500 r/min to 900 r/min), the weak stiffness shim's ability to reduce cutting force weakens (from 13.44 % to 4.17 %), the inhibition of vibration acceleration amplitude decreases (from 40.47 % to 9.57 %), and the reduction in rake face damage diminishes (from 75 % to 11 %). Therefore, under high-speed impact, the protective effect of weak stiffness shims weakens, leading to a reduction in tool protection performance.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"143 ","pages":"Pages 1-16"},"PeriodicalIF":6.1,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769195","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":"Single-step precision manufacturing of ZnSe lenses for FLIR thermal imaging: From atomic insights to lab-scale fabrication and integration","authors":"Neha Khatri ,&nbsp;Sonam Berwal ,&nbsp;Bharpoor Singh ,&nbsp;Suman Tewary ,&nbsp;K. Manjunath ,&nbsp;Saurav Goel","doi":"10.1016/j.jmapro.2025.03.082","DOIUrl":"10.1016/j.jmapro.2025.03.082","url":null,"abstract":"<div><div>Zinc selenide (ZnSe) is widely used in optical components, including lenses, mirrors and thermal imaging systems, owing to its medium refractive index and broad infrared transmission range (0.6 to 21 μm). However, its soft-brittle nature presents challenges in achieving the nanometric smooth finishes required for precision manufacturing. This study introduces a single-step precision manufacturing process for ZnSe and demonstrates its application in a plano-convex lens integrated into FLIR thermal imaging systems for heat detection in integrated circuits.</div><div>To explore ZnSe's ductile plasticity, we developed a molecular dynamics (MD) model. Generalized Stacking Fault Energy (GSFE) calculations revealed that ZnSe favours slip on the Shuffle set ⟨110⟩ (111), unlike harder, brittle materials like silicon and silicon carbide, which favour the Glide set ⟨11–2⟩ (111) explaining the soft and brittle nature of ZnSe. The model predicted that a Peierls stress of approximately 0.027 GPa initiates the motion of ½ ⟨110⟩ perfect dislocations along the (111) slip planes, leading to plasticity and dislocation dissociation into 1/6 ⟨112⟩ (Shockley) partial dislocations. Analysis of the cutting region revealed phase transformation from zinc-blende to a hexagonal structure and defects, including intrinsic stacking faults and ∑3 coherent twin boundaries. Additionally, simulations indicated that the (100) orientation requires the least stress for plastic deformation, while the (110) orientation requires the most.</div><div>By shedding light on these mechanisms, this research aims to enhance our understanding of the precision machining of ZnSe, guiding the development of optimised cutting strategies to minimise defects and improve manufacturing outcomes. In sum, it introduces a “Design-to-Manufacture” approach, linking atomic-level insights with the practical integration of ZnSe lenses into thermal imaging applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 468-481"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing manufacturing process accuracy: A multidisciplinary approach integrating computer vision, machine learning, and control systems","authors":"Kaki Ramesh ,&nbsp;Sandip Deshmukh ,&nbsp;Tathagata Ray ,&nbsp;Chandu Parimi","doi":"10.1016/j.jmapro.2025.03.112","DOIUrl":"10.1016/j.jmapro.2025.03.112","url":null,"abstract":"<div><div>Manufacturing industries face significant challenges in producing high-quality, faultless products within limited timeframes. Conventional human-based inspection methods are still prone to errors and cannot guarantee precise component placement, potentially leading to product failures, user hazards, and substantial financial and reputational losses. This research presents a workflow to automate an inspection system that integrates computer vision, machine learning, image processing, and control systems to address these challenges. The proposed system employs a microcontroller and stepper motors to control a highly calibrated camera, enabling precise and efficient product inspection. At its core, the system utilizes the YOLOv5 model for object detection, specifically identifying hole marks and holes on products pre-assembly. This deep learning model was chosen for its real-time detection capabilities and high accuracy, achieving a mean Average Precision (mAP) of 0.95, which surpasses many current industry standards. Following object detection, advanced image processing techniques are applied to determine the precise position of detected features. Our approach achieves a notable error rate of 0.2 %, offering improvements over traditional inspection methods. Our system offers the potential to reduce inspection processing time and improve fault identification accuracy in real-time applications. Our research contributes to the field of industrial automation by introducing a seamless integration of state-of-the-art computer vision techniques with practical control systems. The system's modular design allows for easy adaptation to various manufacturing environments, benefiting industries with complex assembly processes, such as electronics, automotive manufacturing, etc. While the current implementation focuses on hole detection, future work will explore expanding the system's capabilities to identify a broader range of defects and adapt to different product types. This research paves the way for more intelligent and efficient quality control processes in Industry 4.0, promising to enhance product quality, reduce waste, and improve overall manufacturing efficiency.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 453-467"},"PeriodicalIF":6.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760679","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":"Physics-informed experimental design for neural network-based cutting force model in end milling of carbon fiber reinforced polymer composites","authors":"Darshan S. ,&nbsp;K.A. Desai ,&nbsp;Abir Bhattacharyya","doi":"10.1016/j.jmapro.2025.03.100","DOIUrl":"10.1016/j.jmapro.2025.03.100","url":null,"abstract":"<div><div>Neural Network (NN)-based models showed robust capabilities while predicting cutting force during end milling of Carbon Fiber Reinforced Polymer (CFRP) Composites. NN models can effectively handle numerous factors and the inherent nonlinearities associated with the end milling of CFRP composites. However, a systematic approach is necessary to determine the quality and quantity of experimental cutting force data, which is critical for NN model training. This paper presents a physics-informed experimental design or Physics-Informed Advisor (PIA) that systematically determines cutting conditions for end milling experiments to generate training datasets. The PIA recommends the radial depth of cut and fiber orientation angle values to capture the process mechanics adequately and minimize experimental efforts. The cutting constant relationships of the Mechanistic force model are established using two independent Feed Forward Neural Networks (FFNN) trained using datasets from end milling experiments performed at cutting conditions determined using PIA. The predictions of the proposed approach are compared with the traditional Mechanistic force model presented in the literature and experimentally measured values. It is shown that integrating PIA with FFNNs enables an accurate estimation of cutting forces with reduced experimental efforts in generating training datasets.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 440-452"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747043","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":"Magnetic field-induced arc coupling and process stabilization in KTIG-MIG hybrid welding: Mechanism, optimization, and performance enhancement","authors":"Hongchang Zhang ,&nbsp;Yinan Li ,&nbsp;Qian Zhang ,&nbsp;Minghao Chen ,&nbsp;Hongtao Zhang","doi":"10.1016/j.jmapro.2025.03.085","DOIUrl":"10.1016/j.jmapro.2025.03.085","url":null,"abstract":"<div><div>A hybrid welding process (KTIG-MIG) that combines keyhole tungsten inert gas (KTIG) welding and metal inert gas (MIG) welding under the external magnetic field was proposed. It effectively solved the instability and poor quality issues of stainless steel welding under pure argon, and overcame arc repulsion and coupling problems. The arc morphology, droplet transfer, electrical signals, probability density distribution, weld formation and microstructure evolution in KTIG-MIG hybrid welding were studied. The results indicated that the magnetic field had spatially optimized and reconstructed the hybrid arcs. Transverse magnetic fields (0–1.8 mT) enabled dynamic equilibrium between Lorentz forces and arc repulsion, achieving optimal coupling at 1.0 mT with KTIG/MIG currents of 300/220 A. This configuration reduced current/voltage fluctuations by 14.6 %/13.7 % and suppressed peak currents below 450 A (50 A reduction vs. non-magnetic conditions). Magnetic confinement transformed droplet behavior from irregular globular to stable jet transfer. The period and fluctuation of electrical signals decreased. In addition, the average current of the MIG was lower than the set value of 220 A, indicating the existence of a shunt channel between arcs. Electromagnetic stirring generated equiaxed grains (9.6–192.2 μm vs. 12.8–316.3 μm baseline), elevating weld hardness to 234 HV through δ-ferrite redistribution.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 349-367"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747130","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":"Predicting welding deformation of mild steel bead-on-plate joints by means of artificial neural network and inherent strain method","authors":"Zhixu Mao ,&nbsp;Wei Liang ,&nbsp;Feng Yuan ,&nbsp;Dean Deng","doi":"10.1016/j.jmapro.2025.03.110","DOIUrl":"10.1016/j.jmapro.2025.03.110","url":null,"abstract":"<div><div>The inherent strain method (ISM) is a powerful tool for predicting welding deformation. The implementation of ISM requires the acquisition of inherent deformation data in advance. However, when faced with a practical engineering problem, using conventional methods to obtain this data impromptu consumes too much preparing time. To address this issue, we proposed an idea by integrating thermal-elastic-plastic finite element method (TEP FEM), artificial neural network (ANN), and ISM to predict welding deformation efficiently. To implement this idea, Q355 steel bead-on-plate joints were selected as research objects in the current study. TEP FEM was used to compute a series of inherent deformations under the conditions with various heat inputs and plate thicknesses, and some corresponding experimental mock-ups were conducted to verify the simulation accuracy. The simulated results were then used to train and validate an ANN model with the output layer of inherent deformation components. The trained ANN model serves as a dynamic database to provide the required inherent deformation data instantly, and the ANN-ISM approach was applied to predict the welding deformation efficiently. Besides, the influences of heat input and plate thickness on inherent deformations of bead-on-plate joint were investigated. The out-of-plane deformation modes of the joints with different plate thickness were examined.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 424-439"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747042","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":"Chatter detection and spindle speed selection by scanned periodic sampling frequency","authors":"Tony Schmitz ,&nbsp;Junbeom Son ,&nbsp;Michael Gomez","doi":"10.1016/j.jmapro.2025.03.098","DOIUrl":"10.1016/j.jmapro.2025.03.098","url":null,"abstract":"<div><div>This paper proposes and evaluates an approach for chatter detection using periodic sampling of time domain milling signals. In this approach, the periodic sampling frequency is scanned and the sampled values of the time domain milling signal are used to calculate a stability metric based on the normalized sum of the absolute value of differences between adjacent samples for each sampling frequency. It is shown that local minima in the stability metric values occur at the tooth passing frequency (and its subharmonics) for stable behavior, while the local minima occur at/near the chatter frequency (and its subharmonics) for chatter. It is also demonstrated that the chatter frequency identified using the metric value local minimum can be used to update the spindle speed and determine stable operating parameters. Both numerical and experimental results are provided to validate the approach.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 409-423"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747132","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":"Effect of magnetic field on hydrodynamics of MRSTP media flow and material removal modelling of blade tenon","authors":"Shadab Ahmad ,&nbsp;Yebing Tian ,&nbsp;Zhen Ma ,&nbsp;Cheng Qian ,&nbsp;Xiangyu Yuan","doi":"10.1016/j.jmapro.2025.03.104","DOIUrl":"10.1016/j.jmapro.2025.03.104","url":null,"abstract":"<div><div>In industries like aerospace and energy, where precision is critical, the demand for advanced polishing techniques is growing. Yet, achieving precise polishing in complex components like turbine blades is challenging, especially with irregular features like blade tenons. Ineffective finishing can cause vibration and impact turbine performance. Magnetorheological shear thickening polishing (MRSTP) arises as a promising approach to tackle this challenge. In MRSTP, a magnetic field is utilized to exert a gentle force normally on the surface, while the shear thickening effect amplifies the force tangentially, enhancing material removal efficiency. This research presents a new material removal rate (MRR) model, considering Archard's theory of adhesive wear and Rabinowicz's theory of wear particle, which accounts for sliding-induced wear mechanisms. This model integrates computational simulations and wears principles to predict MRR more accurately in polishing processes. It addresses critical gaps in previous approaches, particularly the inability to simulate sliding contact effects in abrasive polishing, offering improved insights into material removal behaviour for complex geometries of turbine blade tenon. To achieve this, a magnetic field generation device was designed and developed to create the requisite polishing environment. By integrating a magnetic field distribution into a computational fluid dynamics (CFD) module, the behaviour of polishing pressure will be scrutinized by exploring various polishing parameters through CFD simulations. This model will provide valuable insights into the underlying mechanisms governing material removal during the MRSTP process. Subsequently, a series of MRSTP experiments were conducted on Inconel 718-made turbine blades, with a specific focus on measuring and analysing surface topographies to align with the proposed mechanisms. MRSTP of the tenon yielded significant improvement in surface quality, with the tenon protrusions' surface roughness (<em>Ra</em>) decreasing from an initial 0.381 μm to 0.086 μm, marking a 77.4 % enhancement. Similarly, the tenon depressions' surface roughness (<em>Ra</em>) decreased from 0.393 μm to 0.132 μm, representing a 66.4 % improvement after MRSTP. Notably, the polishing process successfully eliminated all scratches from the workpiece surface within 90 min. The theoretical findings demonstrated strong agreement with experimental outcomes. The accuracy and validity of the simulated results and MRR model were confirmed, with an average error of 5.93 % between theoretical and experimental results.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 387-408"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747133","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":"The porous Ni-based superalloy manufactured by customized selective electron beam melting strategies: Pore structure, microstructures, performance, and computational thermal fluid dynamics simulation","authors":"Yifan Wang ,&nbsp;Houqin Wang ,&nbsp;He Li ,&nbsp;Guangzhong Li ,&nbsp;Binggang Zhang ,&nbsp;Yuxin Liu","doi":"10.1016/j.jmapro.2025.03.081","DOIUrl":"10.1016/j.jmapro.2025.03.081","url":null,"abstract":"<div><div>In this paper, the potential of selective electron beam melting (SEBM) of Inconel 625 nickel-based superalloy powder was investigated with a focus on achieving controlled fabrication of interconnected porous structures with uniform micrometer-sized dimensions. This is achieved through customized manufacturing strategies, such as focus offset, pulsed scanning, and layer-by-layer rotation, based on the foundational factors of powder particle size, beam spot diameter, and the constraints that form the initial pores. The samples' build-direction (BD) and scan-direction (SD) morphology under varied parameters were demonstrated using optical microscopy (OM), X-ray computed tomography (3D-CT), and other methods. The typical microstructure of the samples consists primarily of dendritic γ-Ni (FCC) and interdendritic phases rich in Nb and Mo. Additionally, three types of prior powder boundaries (PPBs) can be observed, which influence the microstructure and result in distinct features. A whole progress of the SEBM using discrete element/computational thermal fluid dynamics (DEM/CFD) composite simulation was performed to investigate the unique molten pool behavior in porous material SEBM which relies on the flow through pores and to revealed the formation process of PPBs. Practical mesoscopic models of porous materials and equivalent pore network models (PNM) were established to characterize key pore characteristics such as bulk porosity, mask porosity, pore size and distribution, average tortuosity, distribution of equivalent pore spheres, and their mean coordination numbers, and were compared with porous materials of the similar bulk porosity prepared by powder metallurgy (PM). Permeability simulations were implemented. The absolute permeabilities of porous Inconel 625 prepared by SEBM in the BD and SD reach 7.37 d and 6.57 d, respectively, representing an improvement of about 95 % compared to PM samples. The directional dependence of this characteristic was elucidated. Finally, the fracture surfaces and fracture behavior of the samples were analyzed, the evolution mechanism of the microstructure was used to explain the formation of regions with weak mechanical properties. This completes the establishment of the relationship between morphology, pore characteristics, microstructure, liquid permeability, and mechanical properties of porous Inconel 625 alloy fabricated by SEBM. This material exhibits enormous potential as a transpiration cooling material for thermal protection systems, boasting high efficiency and performance.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 277-292"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739836","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":"Development, characterization, and mechanical properties of innovative in-situ high-entropy alloy reinforced magnesium matrix composites via ultrasonic-assisted processing","authors":"Sonika R. Rajoria,&nbsp;Smarajit Punya Kanti,&nbsp;Harsh Soni,&nbsp;B.N. Sahoo","doi":"10.1016/j.jmapro.2025.03.094","DOIUrl":"10.1016/j.jmapro.2025.03.094","url":null,"abstract":"<div><div>Cast magnesium-metal matrix (Mg-MMCs) composites are extensively exploited in aerospace and automotive manufacturing industries because of their excellent strength-to-weight ratio and superior damping characteristics. This research presents an innovative hybrid technique to produce high entropy alloy (HEA) reinforced magnesium matrix composites using an ultrasonic-assisted liquid state processing method. The results indicate that a more uniform distribution of HEA reinforcing phases within Mg matrix is achieved when composite is fabricated with 10 wt% reinforcement, compared to 5 wt% and 15 wt%. The <em>in-situ</em> reaction mechanisms between the HEA and Mg matrix were established both theoretically and experimentally. Homogenization heat treatment was conducted on both the base and composite materials, leading to the suspension of the β-Mg₁₇Al₁₂ secondary phase into the primary α-Mg matrix. This heat treatment significantly improved mechanical properties, enhancing strength and ductility by 38 % and 136 % in base material and by 25 % and 145 % in composite, respectively. The mechanisms underlying these enhancements were elucidated through detailed analysis of fractographs and microstructures, highlighting the potential of homogenized <em>in-situ</em> composites for advanced engineering applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"142 ","pages":"Pages 368-386"},"PeriodicalIF":6.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747131","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}