Journal of Manufacturing Processes最新文献

{"title":"Data-driven artificial intelligence methods for real-time welding defect diagnosis: A critical review and future outlook","authors":"Mingming Zhang ,&nbsp;Xun Xu ,&nbsp;Jan Polzer ,&nbsp;Qunfeng Liu ,&nbsp;XuFan Chen ,&nbsp;XiaoQi Chen","doi":"10.1016/j.jmapro.2026.01.101","DOIUrl":"10.1016/j.jmapro.2026.01.101","url":null,"abstract":"<div><div>This review provides a detailed analysis of real time welding defect detection systems focusing on the critical integration of advanced sensing technologies with artificial intelligence to enhance welding quality assurance. Traditional post process inspection methods are time consuming costly and fundamentally incompatible with the modern automated manufacturing requirement for real time quality control. This necessitates a shift toward in process monitoring systems that detect defects during the welding operation enabling immediate corrective action. The study evaluates the effectiveness of various sensor technologies including optical electrical acoustic thermal and radiographic sensors in identifying diverse welding defects. It then examines the application of advanced AI techniques for welding defect diagnosis covering specialized models such as convolutional and recurrent neural networks transformer and generative models transfer learning multimodal data fusion and hybrid approaches. The review also discusses key challenges such as data quality acquisition scarcity computational resource limitations and system integration complexity. Finally it highlights promising future research directions including lightweight AI models sophisticated multi sensor fusion strategies and digital twin technologies. These advancements have the potential to improve diagnosis accuracy and truly enable real time defect detection during the welding operation ultimately increasing manufacturing efficiency reducing waste and ensuring the production of safer and more reliable welded structures in critical industrial sectors.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 49-63"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190296","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":"Performance prediction and multi-objective optimization of 17-4PH stainless steel prepared by selective laser melting","authors":"Bo Chen ,&nbsp;Kelu Wang ,&nbsp;Cuiyuan Lu ,&nbsp;Hao Yang ,&nbsp;Shiqiang Lu ,&nbsp;Xin Li ,&nbsp;Quan Yao","doi":"10.1016/j.jmapro.2026.01.081","DOIUrl":"10.1016/j.jmapro.2026.01.081","url":null,"abstract":"<div><div>Selective laser melting (SLM) process parameters critically influence the properties of fabricated components. However, establishing optimal parameters experimentally is challenging due to the complex nonlinear relationship between parameters and quality. To address this, this study proposes an intelligent parameter design method for 17-4PH stainless steel, integrating optimal Latin hypercube sampling (OLHS), machine learning, and multi-objective optimization. The variables considered are laser power, scanning speed, and scanning pitch. Comparisons with Newton-Raphson-based optimization (NBRO), Particle Swarm Optimization (PSO), and Gray Wolf Optimization (GWO) algorithms reveal that NBRO demonstrates superior predictive performance and convergence accuracy when automatically searching for optimal XGBoost hyperparameters. Its test set R² improved by 15.63%, 17.79%, and 16.38% for relative density, surface roughness, and microhardness predictions, respectively, compared to pre-optimization. Based on this, NSGA-III is employed for multi-objective optimization, combined with CRITIC-TOPSIS decision-making to obtain optimal process parameters. Experimental validation demonstrates that the prediction errors for relative density, surface roughness, and microhardness of the optimized specimens are only 0.20%, 5.45%, and 0.29%, respectively. This method significantly enhances process exploration efficiency and accuracy, providing a reliable solution for automated process design in additive manufacturing of high-performance material systems.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 79-100"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191477","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":"Computational thermal analysis of large-format additive manufacturing for CF/PAEK with integrated localized heating","authors":"Jiajia Shen,&nbsp;Kai Wang,&nbsp;Richard Davies,&nbsp;Ken E. Evans,&nbsp;Oana Ghita","doi":"10.1016/j.jmapro.2026.01.090","DOIUrl":"10.1016/j.jmapro.2026.01.090","url":null,"abstract":"<div><div>Large-format additive manufacturing (LFAM) of high-performance polymers like carbon fibre-reinforced polyaryletherketone (CF/PAEK) faces significant thermal management challenges, where uncontrolled cooling rates and thermal gradients can compromise interlayer bonding and are key drivers for residual stress development. While localized heating has emerged as a promising strategy to modulate thermal histories, predictive models capable of capturing its coupled effects with deposition dynamics in LFAM remain underdeveloped. This study presents a high-fidelity finite element framework to simulate the transient thermal behaviour in LFAM with integrated localized heating. Using the <span>Abaqus</span> AM module, the model incorporates a moving double-ellipsoid heat source to represent pre-deposition heating, sequential element activation for material deposition, and dynamic cooling boundaries. The framework is employed to systematically investigate the influence of critical process parameters-including localized heating power, nozzle-to-heater distance, layer thickness, and printing speed–on the thermal profile at a representative interfacial location. Results demonstrate that localized heating effectively elevates the thermal baseline, reduces cooling rates, and extends the dwell time above the glass transition temperature, thereby promoting conditions favourable for interlayer diffusion. The analysis reveals a strong, non-linear coupling between heating power and printing speed in setting the pre-deposition interface temperature. Furthermore, an optimal balance between layer thickness and heater penetration depth is identified to maximize thermal build-up while avoiding geometric instability. This computational work elucidates the thermal mechanisms governing LFAM with auxiliary heating and provides a validated foundation for optimizing thermal management strategies. The developed framework paves the way for implementing digital twins and physics-informed surrogate models to accelerate the development of robust, high-quality LFAM processes for advanced thermoplastic composites.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 136-151"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190298","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":"Flow mechanisms and machine learning-based formation optimization on ultrasonic-assisted friction stir channeling of cast aluminum alloys","authors":"Shengnan Hu ,&nbsp;Yuming Xie ,&nbsp;Xiangchen Meng ,&nbsp;Yilong Han ,&nbsp;Shenglong Wang ,&nbsp;Cheng Shan ,&nbsp;Yongxian Huang","doi":"10.1016/j.jmapro.2026.01.085","DOIUrl":"10.1016/j.jmapro.2026.01.085","url":null,"abstract":"<div><div>Friction stir channeling (FSC) forms internal flow channels within single pass by extracting plasticized materials to the surface with a profiled tool, enabling monolithic cold-plate structures for electric-vehicle battery thermal management. Cast aluminum alloys used in battery housings, however, exhibit limited flowability that leads to irregular geometry and rough inner walls. We reported an ultrasonic-assisted FSC (UaFSC) route for ZL114 cast aluminum alloys that leverages acoustic softening to reduce flow stress, promote upward material flow, and regularize the channel. Rather than exhaustive orthogonal trials, a compact “random seed→neural network→adversarial refinement” workflow learned the multi-parameter process window and yielded high-accuracy predictions of rectangularity, width, height, and a surface-quality index. The model across validation sets achieved 100% accuracy for cover-surface grades and &gt; 80% for geometric metrics. Pareto analysis showed ultrasound increases mean channel height by ∼26% and expanded feasible windows. A coupled Eulerian-Lagrangian finite-element model ascribed these improvements to reduced stress, lower temperature rise, and higher void fractions. Tracer-based kinematics revealed a periodic, probe-entrained flow in UaFSC that recovered wall-normal displacements and smoothed the advancing side, cutting inner-wall roughness. The results clarified the formation mechanisms and provided a data-efficient pathway to robust process design for compact thermal devices.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 152-169"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190302","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":"Mechanical precision forming and force analysis in truing of arc-shaped diamond grinding wheel using tantalum rod","authors":"Bing Chen ,&nbsp;Guangye Qing ,&nbsp;Wenzhang Yang ,&nbsp;Jun Yi ,&nbsp;Jimin Ge ,&nbsp;Bing Guo ,&nbsp;Zhaohui Deng","doi":"10.1016/j.jmapro.2026.01.038","DOIUrl":"10.1016/j.jmapro.2026.01.038","url":null,"abstract":"<div><div>Arc-shaped diamond grinding wheels, as ultra-precision machining tools, offer significant advantages in the processing of spherical, aspherical, and free-form optical components due to their unique arc profiles. However, owing to the elevated hardness and comparatively inferior fracture toughness of these optical components, inevitable wear of grinding wheels occurs during grinding, leading to loss of their precise geometry and thus affecting the machining quality of the components. Therefore, in this paper, tantalum metal is used as dresser for arc-shaped wheels, and the dressed wheels are applied to the processing of axially symmetric spherical optical components. First, using planar wheel dressing as an example, the force signals collected during the dressing process with green silicon carbide (GC) and tantalum blocks are detected and analyzed. The results show that although tantalum generates relatively large dressing forces, the force in the stable stage are more uniform and stable with reduced fluctuations, contributing to the geometric stability of the grinding wheel. Tantalum dressing outperforms GC blocks in terms of roundness error and three-dimensional roughness index. Finally, the efficacy of tantalum utilization in ultra-precision grinding is ultimately demonstrated through its use in dressing arc-shaped wheels, followed by a comparative analysis of the results obtained with GC grinding rods. The experimental findings indicate that the arc contour error of following tantalum dressing is 9.4 μm, while the run-out error is 8.7 μm. When grinding K9 optical glass with spherical surface, the surface roughness reaches 0.4032 μm, and the surface accuracy is 724.4224 nm. A comparison of the two methods reveals that tantalum dressing decreases form and run-out errors by 54.81% and 37.41%, respectively. At the same time, surface roughness and accuracy of the processed workpiece are improved by 38.15% and 55.80%, respectively. These results show that the use of tantalum can not only improve grinding wheels' shape accuracy (such as plane and arc-shaped wheels), but also further improve the workpiece quality.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 101-114"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190286","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":"A 3D anomaly detection method based on multiscale point features for defects in vehicle stamped parts","authors":"Yi Liu ,&nbsp;Changsheng Zhang ,&nbsp;Xingjun Dong ,&nbsp;Yufei Yang","doi":"10.1016/j.jmapro.2026.01.102","DOIUrl":"10.1016/j.jmapro.2026.01.102","url":null,"abstract":"<div><div>In the production process of vehicle stamped parts, local deviations from the nominal geometry of stamped metal sheet, i.e. defects, may occur. The recognizability of these defects is affected by illuminations, and image-based anomaly detection methods cannot effectively detect abnormal vehicle stamped parts. To solve the effect of illuminations, this paper takes the three-dimensional (3D) point cloud of stamped parts as the research object, and proposes a <strong>M</strong>ultiscale <strong>P</strong>oint feature-based <strong>3D</strong> anomaly detection method (<strong>MP3D</strong>). To extract multiscale point features, this paper proposes a local aggregation module. Local aggregation module realizes feature aggregation of disordered points, and the aggregated point features have a larger receptive field. Features of different receptive fields are aggregated for multiscale anomaly detection. In addition, this paper designs a 3D anomaly generation strategy, which generates diverse abnormal samples by constructing local defects. Since the anomaly detection task requires classifying every point of the sample, there is an imbalance in the number of normal points and abnormal points. This paper improves the cross entropy loss for the anomaly detection task. To evaluate the performance of the proposed MP3D, this paper conducts extensive experiments on the MVTec 3D Anomaly Detection (MVTec3D-AD) dataset and a real stamped part dataset. Experimental results demonstrate that MP3D achieves effective anomaly detection performance at both the sample and point levels.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 64-78"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190295","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":"Joint enhancement in LDED joining SLM-fabricated AlSi10Mg: A combined strategy based on ultrasonic vibration assistance, filling material and heat treatment","authors":"Zhiguo Wang ,&nbsp;Tianqi Zhao ,&nbsp;Yingwei Zhang ,&nbsp;Zhenfeng He ,&nbsp;Yuhui Zhao ,&nbsp;Jibin Zhao ,&nbsp;Qiwei Wang","doi":"10.1016/j.jmapro.2026.01.082","DOIUrl":"10.1016/j.jmapro.2026.01.082","url":null,"abstract":"<div><div>The high-performance joining of selective laser melted aluminum alloy by laser direct energy deposition presents a significant challenge owing to the obvious interfacial micro-performance valley, pores and microstructural differences between the joint region and base. A combined strategy based on three aspects is adopted, which includes ultrasonic vibration assistance (UVA), filling material and heat treatment. The joint microstructure evolution, defect distribution, microhardness and tensile performance of the different strategies were discussed in detail. The results showed that the joining of samples with UVA and changing the filling material strategy improved the microhardness of most areas in the joint and eliminated the pores distributed at the interface. However, the decrease in the interfacial microhardness mainly caused by eutectic silicon aggregation at the fusion line still restricted the joint strength. Fortunately, adding a post T6 heat treatment could significantly improve the weakness in the interface performance. For the high-performance laser deposition energy joining of SLM-built AlSi10Mg, each of the three regulation aspects is essential. The combined strategy based on three aspects can realize that the ultimate tensile strength of the joining samples increased to a maximum of 303 MPa, and the elongation improved to 5.7%, which was closely related to the formation of nanoscale (AlₓSi₁₋ₓ)₃(Sc,Zr) precipitates, nanoscale Si precipitates, Mg solution strengthening and low porosity. Our study offers a novel method for future high-strength welding of SLMed aluminum and the fabrication of large-sized parts via a hybrid additive manufacturing process.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 115-135"},"PeriodicalIF":6.8,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190299","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 topography control in CoCrMo alloy additive manufacturing through laser powder bed fusion process","authors":"Anup Kumar Maurya ,&nbsp;G. Sivakumar ,&nbsp;Murugaiyan Amirthalingam ,&nbsp;M. Kamaraj","doi":"10.1016/j.jmapro.2026.01.091","DOIUrl":"10.1016/j.jmapro.2026.01.091","url":null,"abstract":"<div><div>Laser powder bed fusion (LPBF) enables precise fabrication of CoCrMo alloy components for biomedical applications; however, achieving optimal surface properties for orthopedic implants remains challenging. Surface engineering plays a pivotal role in enhancing both biological and tribological responses, particularly in improving the adhesion of bioactive coatings. This study integrates LPBFed surface optimization with atmospheric plasma-sprayed (APS) hydroxyapatite (HAp) coatings to enhance interfacial bonding strength. LPBF process parameters were systematically optimized to tailor surface roughness, followed by APS deposition of HAp coatings on the optimized CoCrMo substrates. In this study, LPBF process parameters were varied to fabricate CoCrMo samples, and specimens were evaluated based on microhardness (320–375 ± 12 HV_0.5), porosity (&lt;1.1%), relative density (~98.9%), and surface roughness (R_a: 3–13 μm). Based on these criteria, three representative samples were selected for in-depth microstructural and mechanical characterization. Microstructural analysis revealed a dual-phase γ-FCC + ε-HCP (~14.4 vol%) matrix with cellular substructures, columnar grains, and oxide inclusions. Transmission electron microscopy (TEM) analysis revealed nano-sized chromium-rich oxides (~50 nm) and (Co, Mo, W)₂Si Laves phases along grain boundaries, which act as dislocation barriers and contribute to enhanced strength, strain hardening, and microstructural stability. The optimized LPBFed CoCrMo alloy exhibited a yield strength of ~800 ± 15 MPa and elongation of 8 ± 0.5%, attributed to the refined cellular structure, planar defects, and solid-solution strengthening. Following HAp deposition via APS, adhesion strength measurements revealed significantly enhanced interfacial bonding (~45 MPa) in a sample with optimized surface morphology. Scanning electron microscope observations confirmed reduced tensile cracking and improved coating cohesion. Nanoindentation further demonstrated superior hardness and elastic modulus, indicating dense and mechanically stable coatings. These results confirm that LPBF combined with parameter optimization and surface engineering can significantly improve the mechanical integrity and adhesion strength of bioactive coatings for advanced orthopedic implants.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 14-33"},"PeriodicalIF":6.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081616","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":"Resistance spot welding between aluminum and steel: A review of process mechanisms and advancement strategies for enhanced joint performance","authors":"Kang Zhou ,&nbsp;Baokai Ren ,&nbsp;Juntao Shen ,&nbsp;Ping Yao","doi":"10.1016/j.jmapro.2025.09.053","DOIUrl":"10.1016/j.jmapro.2025.09.053","url":null,"abstract":"<div><div>In this paper, recent advances in resistance spot welding (RSW) process between aluminum and steel are comprehensively reviewed. Aluminum and steel are important materials to achieve lightweight manufacturing in automobile and related industrial occasions. However, it is difficult to use conventional RSW process to join these two types of metal sheets, because the large difference in metallurgical properties between aluminum and steel can induce various welding defects, such as hard and brittle intermetallic compounds (IMCs), which significantly deteriorate welding quality during the process. The paper first considers research related to interfacial phenomena and bonding mechanisms, which focused on fundamental studies of the process such as temperature field and stress variation, double nugget evolution and IMC formation and distribution. Then the work on advances in various Al/steel RSW process optimization methods is comprehensively considered, which include using optimized electrode methods, adding auxiliary materials or using external energy field to assist the Al/steel RSW process and also introducing some hybrid optimization methods which combined other welding or joining processes. Some representative and remarkable works were presented in detail, and corresponding statistic and comparative information of different works using the same type of optimization methods were also provided. In addition, the comprehensive performances of the methods, which include some important criteria, are listed in detail. Although these works can provide optimization approaches to obtain Al/steel spot welded joint with satisfactory quality, the reliable implementation of these methods in high-volume industrial application requires further developments in process robustness and cost reduction. In these various improvement methods, the external energy field assisted method is a promising solution for practical applications because it does not require pre-treatment of the parent metal sheets and may allow convenient online adjustment and control. This paper also pays attention to the quality evaluation and process parameter optimization of the process, and provides a prediction about future trends in these aspects by combining advanced artificial intelligent methods based on a review and comprehensive analysis of some relative works. Furthermore, concluding remarks and suggestions for the future works are provided. This work is expected to provide references and insights for academic research and actual industrial application of Al/steel dissimilar metal RSW related areas.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"158 ","pages":"Pages 414-436"},"PeriodicalIF":6.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090387","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":"Experimental investigation and numerical validation of drilling machinability in FDM-printed PLA parts","authors":"Uğur Köklü ,&nbsp;Levent Urtekin ,&nbsp;Erkin Akdoğan ,&nbsp;Faik Yılan ,&nbsp;Murat Demiral","doi":"10.1016/j.jmapro.2026.01.079","DOIUrl":"10.1016/j.jmapro.2026.01.079","url":null,"abstract":"<div><div>Fused Deposition Modeling (FDM) is a widely used additive manufacturing technique that fabricates components through layer-by-layer deposition of thermoplastic materials. Due to its biodegradability, dimensional stability, and favorable flow behavior, polylactic acid (PLA) has become one of the most commonly employed polymers in extrusion-based printing. This study investigates the influence of extrusion temperature, infill pattern, and infill density on the mechanical performance and drilling machinability of FDM-printed PLA components. Tensile tests and hardness measurements were conducted to evaluate mechanical behavior, while drilling machinability was assessed through thrust force measurements and digital microscopy. In parallel, a three-dimensional finite element model was developed using ABAQUS/Explicit to capture damage initiation and interfacial degradation, providing numerical validation of the experimental results. The findings demonstrate that infill density is the dominant parameter, with higher densities leading to significant improvements in tensile strength, elastic modulus, and surface hardness. The grid infill at full density and elevated extrusion temperature yielded the highest mechanical performance, achieving a tensile strength of 40.3 MPa and a modulus of 3050 MPa. In contrast, the hexagonal infill pattern offered a favorable balance between mechanical strength and drilling performance, exhibiting reduced thrust force and improved damage resistance. Optimal drilling conditions were identified at 3000 rpm and 150 mm/min, minimizing delamination, burr formation, and thermal damage. Overall, this work highlights the strong coupling between process parameters, internal architecture, and numerical modeling in governing the structural integrity and machinability of FDM-fabricated PLA parts.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"161 ","pages":"Pages 34-48"},"PeriodicalIF":6.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190297","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}