Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue feat...Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.展开更多
Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)t...Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)technologies use high-power lasers to melt metallic materials,which then solidify to form parts.However,it inherently induces self-equilibrating residual stress during fabrication due to thermal loads and plastic deformation.These residual stresses can cause defects such as delamination,cracking,and distortion,as well as premature failure under service conditions,necessitating mitigation.While post-treatment methods can reduce residual stresses,they are often costly and time-consuming.Therefore,tuning the fabrication process parameters presents a more feasible approach.Accordingly,in addition to providing a comprehensive view of residual stress by their classification,formation mechanisms,measurement methods,and common post-treatment,this paper reviews and compares the studies conducted on the effect of key parameters of the LAM process on the resulting residual stresses.This review focuses on proactively adjusting LAM process parameters as a strategic approach to mitigate residual stress formation.It provides a result of the various parameters influencing residual stress outcomes,such as laser power,scanning speed,beam diameter,hatch spacing,and scanning strategies.Finally,the paper identifies existing research gaps and proposes future studies needed to deepen understanding of the relationship between process parameters and residual stress mitigation in LAM.展开更多
As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social syste...As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social systems(CPSSs)with a human-centric focus.These technologies are organized by the system-wide approach of Industry 5.0,in order to empower the manufacturing industry to achieve broader societal goals of job creation,economic growth,and green production.This survey first provides a general framework of smart manufacturing in the context of Industry 5.0.Wherein,the embodied agents,like robots,sensors,and actuators,are the carriers for Ind AI,facilitating the development of the self-learning intelligence in individual entities,the collaborative intelligence in production lines and factories(smart systems),and the swarm intelligence within industrial clusters(systems of smart systems).Through the framework of CPSSs,the key technologies and their possible applications for supporting the single-agent,multi-agent and swarm-agent embodied Ind AI have been reviewed,such as the embodied perception,interaction,scheduling,multi-mode large language models,and collaborative training.Finally,to stimulate future research in this area,the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed.The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner,thereby fostering an intelligent,sustainable,and resilient industrial landscape.展开更多
Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design o...Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.展开更多
The feasibility of manufacturing Ti-6Al-4V samples through a combination of laser-aided additive manufacturing with powder(LAAM_(p))and wire(LAAM_(w))was explored.A process study was first conducted to successfully ci...The feasibility of manufacturing Ti-6Al-4V samples through a combination of laser-aided additive manufacturing with powder(LAAM_(p))and wire(LAAM_(w))was explored.A process study was first conducted to successfully circumvent defects in Ti-6Al-4V deposits for LAAM_(p) and LAAM_(w),respectively.With the optimized process parameters,robust interfaces were achieved between powder/wire deposits and the forged substrate,as well as between powder and wire deposits.Microstructure characterization results revealed the epitaxial prior β grains in the deposited Ti-6Al-4V,wherein the powder deposit was dominated by a finerα′microstructure and the wire deposit was characterized by lamellar α phases.The mechanisms of microstructure formation and correlation with mechanical behavior were analyzed and discussed.The mechanical properties of the interfacial samples can meet the requirements of the relevant Aerospace Material Specifications(AMS 6932)even without post heat treatment.No fracture occurred within the interfacial area,further suggesting the robust interface.The findings of this study highlighted the feasibility of combining LAAM_(p) and LAAM_(w) in the direct manufacturing of Ti-6Al-4V parts in accordance with the required dimensional resolution and deposition rate,together with sound strength and ductility balance in the as-built condition.展开更多
In this review,we propose a comprehensive overview of additive manufacturing(AM)technologies and design possibilities in manufacturing metamaterials for various applications in the biomedical field,of which many are i...In this review,we propose a comprehensive overview of additive manufacturing(AM)technologies and design possibilities in manufacturing metamaterials for various applications in the biomedical field,of which many are inspired by nature itself.It describes how new AM technologies(e.g.continuous liquid interface production and multiphoton polymerization,etc)and recent developments in more mature AM technologies(e.g.powder bed fusion,stereolithography,and extrusion-based bioprinting(EBB),etc)lead to more precise,efficient,and personalized biomedical components.EBB is a revolutionary topic creating intricate models with remarkable mechanical compatibility of metamaterials,for instance,stress elimination for tissue engineering and regenerative medicine,negative or zero Poisson’s ratio.By exploiting the designs of porous structures(e.g.truss,triply periodic minimal surface,plant/animal-inspired,and functionally graded lattices,etc),AM-made bioactive bone implants,artificial tissues,and organs are made for tissue replacement.The material palette of the AM metamaterials has high diversity nowadays,ranging from alloys and metals(e.g.cobalt-chromium alloys and titanium,etc)to polymers(e.g.biodegradable polycaprolactone and polymethyl methacrylate,etc),which could be even integrated within bioactive ceramics.These advancements are driving the progress of the biomedical field,improving human health and quality of life.展开更多
This study examines a curriculum system developed at the College of Aviation Manufacturing Industry at Nanchang Hangkong University through Industry-Education Integration(I-E Integration).Drawing on engineering educat...This study examines a curriculum system developed at the College of Aviation Manufacturing Industry at Nanchang Hangkong University through Industry-Education Integration(I-E Integration).Drawing on engineering education principles and reforms in the Mechanical Design,Manufacturing,and Automation program,it aligns course design with industry needs,integrates technological advancements,and embeds production processes.The approach restructures modular course content based on aviation manufacturing technologies,implements project-based learning via a university-enterprise"factory-in-school"training base,and adopts an Outcome-Based Education(OBE)system for evaluation and improvement.This replicable model provides practical insights for industry-focused curriculum development.展开更多
As a follow-up to the successful International Conference on Biomaterials,Bio-Design and Manufacturing(BDMC)held at the National University of Singapore in 2023[1]and at the University of Tokyo in 2024[2],BDMC2025 too...As a follow-up to the successful International Conference on Biomaterials,Bio-Design and Manufacturing(BDMC)held at the National University of Singapore in 2023[1]and at the University of Tokyo in 2024[2],BDMC2025 took place at the University of Oxford in the UK from August 8th to August 10th this year.After the meeting,a participant from the University of Cambridge described his experience of attending BDMC2025 on the social media platform LinkedIn in the following terms:“Many thanks to the organizers for a fantastic event bringing together nearly everyone at the interface of Biofabrication,Materials Science,and Biomedical Engineering”[3].The conference was held on the campus of the University of Oxford and 190 researchers from 55 academic institutions across 10 countries and regions attended(Fig.1).展开更多
Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative techn...Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.展开更多
Machine learning(ML)has recently enabled many modeling tasks in design,manufacturing,and condition monitoring due to its unparalleled learning ability using existing data.Data have become the limiting factor when impl...Machine learning(ML)has recently enabled many modeling tasks in design,manufacturing,and condition monitoring due to its unparalleled learning ability using existing data.Data have become the limiting factor when implementing ML in industry.However,there is no systematic investigation on how data quality can be assessed and improved for ML-based design and manufacturing.The aim of this survey is to uncover the data challenges in this domain and review the techniques used to resolve them.To establish the background for the subsequent analysis,crucial data terminologies in ML-based modeling are reviewed and categorized into data acquisition,management,analysis,and utilization.Thereafter,the concepts and frameworks established to evaluate data quality and imbalance,including data quality assessment,data readiness,information quality,data biases,fairness,and diversity,are further investigated.The root causes and types of data challenges,including human factors,complex systems,complicated relationships,lack of data quality,data heterogeneity,data imbalance,and data scarcity,are identified and summarized.Methods to improve data quality and mitigate data imbalance and their applications in this domain are reviewed.This literature review focuses on two promising methods:data augmentation and active learning.The strengths,limitations,and applicability of the surveyed techniques are illustrated.The trends of data augmentation and active learning are discussed with respect to their applications,data types,and approaches.Based on this discussion,future directions for data quality improvement and data imbalance mitigation in this domain are identified.展开更多
Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to c...Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to control noise efficiently in real-life applications.In this study,a novel optimization-driven design scheme is developed to obtain lightweight acoustic metamaterials with a strong sound insulation capability for additive manufacturing.In the proposed design scheme,a topology optimization method for an acoustic metamaterial in the acoustic-solid interaction system is implemented to obtain an initial cross-sectional topology of the acoustic microstructure during the conceptual design phase.Then,in the detailed design phase,the parametric model for a higher-dimensional design is formulated based on the topology optimization result.An adaptive Kriging interpolation approach is proposed to accurately reformulate a much easier surrogate model from the original parameterization formulation to avoid repeating calls for nonlinear analyses in the 3D acoustic-structure interaction system.A surrogate model was used to optimize a ready-to-print acoustic metamaterial with improved noise reduction performance.Experimental verification based on an impedance tube is implemented.Results demonstrate characteristics of the devised metamaterial as well as the proposed method.展开更多
Military missions in hostile environments are often costly and unpredictable,with squadrons sometimes facing isolation and resource scarcity.In such scenarios,critical components in vehicles,drones,and energy generato...Military missions in hostile environments are often costly and unpredictable,with squadrons sometimes facing isolation and resource scarcity.In such scenarios,critical components in vehicles,drones,and energy generators may require structural reinforcement or repair due to damage.This paper proposes a portable,on-site production method for molds under challenging conditions,where material supply is limited.The method utilizes large format additive manufacturing(LFAM)with recycled composite materials,sourced from end-of-life components and waste,as feedstock.The study investigates the microstructural effects of recycling through shredding techniques,using microscopic imaging.Three potential defense-sector applications are explored,specifically in the aerospace,automotive,and energy industries.Additionally,the influence of key printing parameters,particularly nonparallel plane deposition at a 45-degree angle,on the mechanical behavior of ABS reinforced with 20%glass fiber(GF)is examined.The results demonstrate the feasibility of this manufacturing approach,highlighting reductions in waste material and production times compared to traditional methods.Shorter layer times were found to reduce thermal gradients between layers,thereby improving layer adhesion.While 45-degree deposition enhanced Young's modulus,it slightly reduced interlayer adhesion quality.Furthermore,recycling-induced fiber length reduction led to material degradation,aligning with findings from previous studies.Challenges encountered during implementation included weak part adherence to the print bed and local excess material deposition.Overall,the proposed methodology offers a cost-effective alternative to traditional CNC machining for mold production,demonstrating its potential for on-demand manufacturing in resource-constrained environments.展开更多
As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for s...As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for solving FJSP in the literature are population-based evolutionary algorithms,which are complex and time-consuming.In this paper,we propose a fast effective singlesolution based local search algorithm with an innovative adaptive weighting-based local search(AWLS)technique for solving FJSP.The adaptive weighting technique assigns weights to each operation and adaptively updates them during the exploration.AWLS integrates a Tabu Search strategy and the adaptive weighting technique to smooth the landscape of the search space and enhance the exploration diversity.Computational experiments on 313 well-known benchmark instances demonstrate that AWLS is highly competitive with state-of-the-art algorithms in terms of both solution quality and computational efficiency,despite of its simplicity.Specifically,AWLS improves the previous best-known results in the literature on 33 instances and match the best-known results on the remaining ones except for only one under the same time limit of up to 300 s.As a strongly non-deterministic polynomia(NP)-hard problem which has been extensively studied for nearly half a century,breaking the records on these classic instances is an arduous task.Nevertheless,AWLS establishes new records on 8 challenging instances whose previous best records were established by a state-of-the-art meta-heuristic algorithm and a famous industrial solver.展开更多
Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection met...Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection methods during manufacturing is critical yet challenging.This study introduces a deep learning-based method for detecting lithium-plating-type defects using formation and capacity grading data,enabling accurate identification of defective batteries without additional equipment.First,lithiumplating-type defect batteries with various types and area ratios are fabricated.Formation and capacity grading data from 154 batteries(48 defective,106 normal)are collected to construct a dataset.Subsequently,a dual-task deep learning model is then developed,where the reconstruction task learns latent representations from the features,while the classification task identifies the defective batteries.Shapley value analysis further quantifies feature importance,revealing that defective batteries exhibit reduced coulombic efficiency(attributed to irreversible lithium loss)and elevated open-circuit voltage/K-values(linked to self-equalization effects).These findings align with the electrochemical mechanisms of lithium plating,enhancing the model's interpretability.Validated on statistically robust samples shows that the framework achieves a recall of 97.14%for defective batteries and an overall accuracy of 97.42%.This deep learning-driven solution provides a scalable and cost-effective quality control strategy for battery manufacturing.展开更多
Additive manufacturing(AM),with its high flexibility,cost-effectiveness,and customization,significantly accelerates the advancement of nanogenerators,contributing to sustainable energy solutions and the Internet of Th...Additive manufacturing(AM),with its high flexibility,cost-effectiveness,and customization,significantly accelerates the advancement of nanogenerators,contributing to sustainable energy solutions and the Internet of Things.In this review,an in-depth analysis of AM for piezoelectric and triboelectric nanogenerators is presented from the perspectives of fundamental mechanisms,recent advancements,and future prospects.It highlights AM-enabled advantages of versatility across materials,structural topology optimization,microstructure design,and integrated printing,which enhance critical performance indicators of nanogenerators,such as surface charge density and piezoelectric constant,thereby improving device performance compared to conventional fabrication.Common AM techniques for nanogenerators,including fused deposition modeling,direct ink writing,stereolithography,and digital light processing,are systematically examined in terms of their working principles,improved metrics(output voltage/current,power density),theoretical explanation,and application scopes.Hierarchical relationships connecting AM technologies with performance optimization and applications of nanogenerators are elucidated,providing a solid foundation for advancements in energy harvesting,self-powered sensors,wearable devices,and human-machine interaction.Furthermore,the challenges related to fabrication quality,cross-scale manufacturing,processing efficiency,and industrial deployment are critically discussed.Finally,the future prospects of AM for nanogenerators are explored,aiming to foster continuous progress and innovation in this field.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising technique for producing large-scale metal components,favoured by high deposition rates,flexibility and low cost.Despite its potential,the complexity of W...Wire arc additive manufacturing(WAAM)has emerged as a promising technique for producing large-scale metal components,favoured by high deposition rates,flexibility and low cost.Despite its potential,the complexity of WAAM processes,which involves intricate thermal dynamics,phase transitions,and metallurgical,mechanical,and chemical interactions,presents considerable challenges in final product qualities.Simulation technologies in WAAM have proven invaluable,providing accurate predictions in key areas such as material properties,defect identification,deposit morphology,and residual stress.These predictions play a critical role in optimising manufacturing strategies for the final product.This paper provides a comprehensive review of the simulation techniques applied in WAAM,tracing developments from 2013 to 2023.Initially,it analyses the current challenges faced by simulation methods in three main areas.Subsequently,the review explores the current modelling approaches and the applications of these simulations.Following this,the paper discusses the present state of WAAM simulation,identifying specific issues inherent to WAAM simulation itself.Finally,through a thorough review of existing literature and related analysis,the paper offers future perspectives on potential advancements in WAAM simulation strategies.展开更多
The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numer...The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numerous sensors to realize high levels of perception,precision,safety,adaptability,and intelligence.Triboelectric and piezoelectric sensors address these needs by providing high sensitivity,flexibility,and the capability of self-powered sensing,leveraging the revolutionary nature of nanogenerators to convert mechanical energy into electrical energy on basis of Maxwell’s displacement current.These sensors surpass externally powered passive sensors by offering continuous operation,reduced maintenance,and the capability to function in remote or harsh environments.The integration of EAI with advanced nanogenerators sensors could position robotics to perform autonomously,efficiently,and safely,paving the way for innovative applications in various domains such as industrial automation,environmental monitoring,healthcare,and smart homes.In this paper,the fundamental theories,design,manufacturing,and applications of nanogenerators are comprehensively reviewed as afoundation of the advanced sensors for intelligent robotics in the new era,with three major application fields:sensing(including human–robot interaction,exteroceptive sensing and proprioceptive sensing),computing and actuating.Perspectives are addressed for nanogenerators systems in future development.展开更多
Hetero-deformation induced(HDI) strengthening generally yields a weak effect on the mechanical property improvement of particle-reinforced metal matrix composites(MMCs). In the present work, a novel strategy was repor...Hetero-deformation induced(HDI) strengthening generally yields a weak effect on the mechanical property improvement of particle-reinforced metal matrix composites(MMCs). In the present work, a novel strategy was reported to induce remarkable HDI strengthening in MMCs by selecting a reinforcing material with excellent geometrically necessary dislocation(GND) storage ability. The viability of the proposed strategy was tested on additively manufactured nickel matrix composites consisting of Inconel 625 alloy(IN625) as the matrix and high-entropy alloy VNbMoTa as the reinforcing material. It was found that the average grain size and dislocation density of the additively manufactured MMCs gradually decreased with the increase in the additional amount of VNbMoTa. All the samples possessed a similar two-layer VNbMoTa-matrix interface structure containing a high-entropy alloy layer and a Laves phase layer;however, the interface width varied. This two-layer interface could hold GND pile-ups without breaking to ensure a good load transfer effect, and ductile VNbMoTa particles demonstrated excellent GND storage capacity to induce significant HDI stress. The HDI stress for the IN625-(10 wt%)VNbMoTa sample was approximately 200 MPa higher than that for the pure IN625 alloy, resulting in an excellent strength-ductility synergy. The yield strength and elongation of the IN625-(10 wt%)VNbMoTa sample reached(1 032.5 ± 18.8)MPa and(11.8 ± 1.2)%, respectively. In addition, the IN625-(10 wt%)VNbMoTa composite also demonstrated superior mechanical properties at 650℃ that were comparable to those at room temperature, implying that VNbMoTa addition remarkably limited strength reduction caused by temperature. Deformable VNbMoTa particles effectively alleviated the stress concentration, delayed the crack initiation, generated more dislocations and pile-ups, and, in turn, improved the overall high-temperature strength of composites.展开更多
Additive manufacturing(AM)offers the unique capability of directly creating three-dimensional complicated ceramic components with high process flexibility and outstanding geometry controllability.However,current ceram...Additive manufacturing(AM)offers the unique capability of directly creating three-dimensional complicated ceramic components with high process flexibility and outstanding geometry controllability.However,current ceramic AM technology is mainly limited to the creation of a single material,which falls short of meeting the multiple functional requirements under increasingly harsh service circumstances.Ceramic multi-material additive manufacturing(MMAM)technology has great potential for integrally producing multi-dimensional multi-functional components,allowing for point-by-point precision manufacturing of programmable performance/functions.However,there is a huge gap between the capabilities of the existing ceramic MMAM technology and the requirements for industrial application.In this review,we discuss and summarize the research status of ceramic MMAM technology from the perspectives of feedstock selection,printing process,post-processing,component performance,and application.Throughout the discussion,the challenges associated with ceramic MMAM such as heterogeneous material coupled printing,heterogeneous interfacial bonding,and co-sintering densification have been put forward.This review aims to bridge the gap between AM technologies and the requirements for multifunctional ceramic components by analyzing the existing limitations in ceramic MMAM and pointing out future needs.展开更多
Additive manufacturing has emerged as a transformative technology for producing biomedical metals and implants,offering the potential to revolutionize patient care and treatment outcomes.This article reviews the recen...Additive manufacturing has emerged as a transformative technology for producing biomedical metals and implants,offering the potential to revolutionize patient care and treatment outcomes.This article reviews the recent advances in additive manufacturing(AM)of biomedical metal implants,especially load-bearing biomedical alloys,biodegradable alloys,novel metals,and 4D printing,whose properties are systematically assessed to facilitate material selection for specific medical applications.The applications of the most cutting-edge artificial intelligence in AM and surface functional modification are also presented.This article also explores the application of AM in various medical specialties,such as orthopedics,dentistry,cardiology,and neurosurgery,demonstrating its potential to solve complex clinical challenges and advance patient-centered healthcare solutions.Furthermore,it highlights the critical roles of AM in shaping the future of medical implant manufacturing.The optimistic outlook on the bright future of AM in medical metals delivers personalized,high-performance medical implants that improve patient treatment outcomes and well-being.展开更多
文摘Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.
文摘Additive manufacturing(AM)has emerged as one of the most utilized processes in manufacturing due to its ability to produce complex geometries with minimal material waste and greater design freedom.Laser-based AM(LAM)technologies use high-power lasers to melt metallic materials,which then solidify to form parts.However,it inherently induces self-equilibrating residual stress during fabrication due to thermal loads and plastic deformation.These residual stresses can cause defects such as delamination,cracking,and distortion,as well as premature failure under service conditions,necessitating mitigation.While post-treatment methods can reduce residual stresses,they are often costly and time-consuming.Therefore,tuning the fabrication process parameters presents a more feasible approach.Accordingly,in addition to providing a comprehensive view of residual stress by their classification,formation mechanisms,measurement methods,and common post-treatment,this paper reviews and compares the studies conducted on the effect of key parameters of the LAM process on the resulting residual stresses.This review focuses on proactively adjusting LAM process parameters as a strategic approach to mitigate residual stress formation.It provides a result of the various parameters influencing residual stress outcomes,such as laser power,scanning speed,beam diameter,hatch spacing,and scanning strategies.Finally,the paper identifies existing research gaps and proposes future studies needed to deepen understanding of the relationship between process parameters and residual stress mitigation in LAM.
基金supported by the National Key Research and Development Program of China(2021YFB1714300)the National Natural Science Foundation of China(62233005,U2441245,62173141)+3 种基金CNPC Innovation Found(2024DQ02-0507)Shanghai Natural Science(24ZR1416400)Shanghai Baiyu Lan Talent Program Pujiang Project(24PJD020)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)(B17017)
文摘As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social systems(CPSSs)with a human-centric focus.These technologies are organized by the system-wide approach of Industry 5.0,in order to empower the manufacturing industry to achieve broader societal goals of job creation,economic growth,and green production.This survey first provides a general framework of smart manufacturing in the context of Industry 5.0.Wherein,the embodied agents,like robots,sensors,and actuators,are the carriers for Ind AI,facilitating the development of the self-learning intelligence in individual entities,the collaborative intelligence in production lines and factories(smart systems),and the swarm intelligence within industrial clusters(systems of smart systems).Through the framework of CPSSs,the key technologies and their possible applications for supporting the single-agent,multi-agent and swarm-agent embodied Ind AI have been reviewed,such as the embodied perception,interaction,scheduling,multi-mode large language models,and collaborative training.Finally,to stimulate future research in this area,the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed.The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner,thereby fostering an intelligent,sustainable,and resilient industrial landscape.
基金supports for this research were provided by the National Natural Science Foundation of China(No.12272301,12002278,U1906233)the Guangdong Basic and Applied Basic Research Foundation,China(Nos.2023A1515011970,2024A1515010256)+1 种基金the Dalian City Supports Innovation and Entrepreneurship Projects for High-Level Talents,China(2021RD16)the Key R&D Project of CSCEC,China(No.CSCEC-2020-Z-4).
文摘Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.
基金financially supported by the Agency for Science,Technology and Research(A*Star),Republic of Singapore,under the Aerospace Consortium Cycle 12“Characterization of the Effect of Wire and Powder Deposited Materials”(No.A1815a0078)。
文摘The feasibility of manufacturing Ti-6Al-4V samples through a combination of laser-aided additive manufacturing with powder(LAAM_(p))and wire(LAAM_(w))was explored.A process study was first conducted to successfully circumvent defects in Ti-6Al-4V deposits for LAAM_(p) and LAAM_(w),respectively.With the optimized process parameters,robust interfaces were achieved between powder/wire deposits and the forged substrate,as well as between powder and wire deposits.Microstructure characterization results revealed the epitaxial prior β grains in the deposited Ti-6Al-4V,wherein the powder deposit was dominated by a finerα′microstructure and the wire deposit was characterized by lamellar α phases.The mechanisms of microstructure formation and correlation with mechanical behavior were analyzed and discussed.The mechanical properties of the interfacial samples can meet the requirements of the relevant Aerospace Material Specifications(AMS 6932)even without post heat treatment.No fracture occurred within the interfacial area,further suggesting the robust interface.The findings of this study highlighted the feasibility of combining LAAM_(p) and LAAM_(w) in the direct manufacturing of Ti-6Al-4V parts in accordance with the required dimensional resolution and deposition rate,together with sound strength and ductility balance in the as-built condition.
基金sponsored by the Science and Technology Program of Hubei Province,China(2022EHB020,2023BBB096)support provided by Centre of the Excellence in Production Research(XPRES)at KTH。
文摘In this review,we propose a comprehensive overview of additive manufacturing(AM)technologies and design possibilities in manufacturing metamaterials for various applications in the biomedical field,of which many are inspired by nature itself.It describes how new AM technologies(e.g.continuous liquid interface production and multiphoton polymerization,etc)and recent developments in more mature AM technologies(e.g.powder bed fusion,stereolithography,and extrusion-based bioprinting(EBB),etc)lead to more precise,efficient,and personalized biomedical components.EBB is a revolutionary topic creating intricate models with remarkable mechanical compatibility of metamaterials,for instance,stress elimination for tissue engineering and regenerative medicine,negative or zero Poisson’s ratio.By exploiting the designs of porous structures(e.g.truss,triply periodic minimal surface,plant/animal-inspired,and functionally graded lattices,etc),AM-made bioactive bone implants,artificial tissues,and organs are made for tissue replacement.The material palette of the AM metamaterials has high diversity nowadays,ranging from alloys and metals(e.g.cobalt-chromium alloys and titanium,etc)to polymers(e.g.biodegradable polycaprolactone and polymethyl methacrylate,etc),which could be even integrated within bioactive ceramics.These advancements are driving the progress of the biomedical field,improving human health and quality of life.
基金supported by the China Machinery Industry Education Association 2024 Industry-Education-Research Integration Project(Project No.:ZJJX24CY099)。
文摘This study examines a curriculum system developed at the College of Aviation Manufacturing Industry at Nanchang Hangkong University through Industry-Education Integration(I-E Integration).Drawing on engineering education principles and reforms in the Mechanical Design,Manufacturing,and Automation program,it aligns course design with industry needs,integrates technological advancements,and embeds production processes.The approach restructures modular course content based on aviation manufacturing technologies,implements project-based learning via a university-enterprise"factory-in-school"training base,and adopts an Outcome-Based Education(OBE)system for evaluation and improvement.This replicable model provides practical insights for industry-focused curriculum development.
文摘As a follow-up to the successful International Conference on Biomaterials,Bio-Design and Manufacturing(BDMC)held at the National University of Singapore in 2023[1]and at the University of Tokyo in 2024[2],BDMC2025 took place at the University of Oxford in the UK from August 8th to August 10th this year.After the meeting,a participant from the University of Cambridge described his experience of attending BDMC2025 on the social media platform LinkedIn in the following terms:“Many thanks to the organizers for a fantastic event bringing together nearly everyone at the interface of Biofabrication,Materials Science,and Biomedical Engineering”[3].The conference was held on the campus of the University of Oxford and 190 researchers from 55 academic institutions across 10 countries and regions attended(Fig.1).
文摘Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.
基金funded by the McGill University Graduate Excellence Fellowship Award(00157)the Mitacs Accelerate Program(IT13369)the McGill Engineering Doctoral Award(MEDA).
文摘Machine learning(ML)has recently enabled many modeling tasks in design,manufacturing,and condition monitoring due to its unparalleled learning ability using existing data.Data have become the limiting factor when implementing ML in industry.However,there is no systematic investigation on how data quality can be assessed and improved for ML-based design and manufacturing.The aim of this survey is to uncover the data challenges in this domain and review the techniques used to resolve them.To establish the background for the subsequent analysis,crucial data terminologies in ML-based modeling are reviewed and categorized into data acquisition,management,analysis,and utilization.Thereafter,the concepts and frameworks established to evaluate data quality and imbalance,including data quality assessment,data readiness,information quality,data biases,fairness,and diversity,are further investigated.The root causes and types of data challenges,including human factors,complex systems,complicated relationships,lack of data quality,data heterogeneity,data imbalance,and data scarcity,are identified and summarized.Methods to improve data quality and mitigate data imbalance and their applications in this domain are reviewed.This literature review focuses on two promising methods:data augmentation and active learning.The strengths,limitations,and applicability of the surveyed techniques are illustrated.The trends of data augmentation and active learning are discussed with respect to their applications,data types,and approaches.Based on this discussion,future directions for data quality improvement and data imbalance mitigation in this domain are identified.
基金supported by the National Key Research and Development Program of China(No.2023YFB4604800)the National Natural Science Foundation of China(No.52075195)the Inelligent Manufacturing Equipment and Technology Open Foundation(No.IMETKF2023016).
文摘Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to control noise efficiently in real-life applications.In this study,a novel optimization-driven design scheme is developed to obtain lightweight acoustic metamaterials with a strong sound insulation capability for additive manufacturing.In the proposed design scheme,a topology optimization method for an acoustic metamaterial in the acoustic-solid interaction system is implemented to obtain an initial cross-sectional topology of the acoustic microstructure during the conceptual design phase.Then,in the detailed design phase,the parametric model for a higher-dimensional design is formulated based on the topology optimization result.An adaptive Kriging interpolation approach is proposed to accurately reformulate a much easier surrogate model from the original parameterization formulation to avoid repeating calls for nonlinear analyses in the 3D acoustic-structure interaction system.A surrogate model was used to optimize a ready-to-print acoustic metamaterial with improved noise reduction performance.Experimental verification based on an impedance tube is implemented.Results demonstrate characteristics of the devised metamaterial as well as the proposed method.
基金Generalitat Valenciana(GVA)and Spanish Ministry of Science and Innovation(Grant Nos.TED2021-130879 B-C21,CIACIF/2021/286,PID2023-151110OB-I00,and CIPROM/2022/3)to provide funds for conducting experiments and software licensessupported by the National Research Foundation,Prime Minister's Office,Singapore under its Campus for Research Excellence and Technological Enterprise(CREATE)programme。
文摘Military missions in hostile environments are often costly and unpredictable,with squadrons sometimes facing isolation and resource scarcity.In such scenarios,critical components in vehicles,drones,and energy generators may require structural reinforcement or repair due to damage.This paper proposes a portable,on-site production method for molds under challenging conditions,where material supply is limited.The method utilizes large format additive manufacturing(LFAM)with recycled composite materials,sourced from end-of-life components and waste,as feedstock.The study investigates the microstructural effects of recycling through shredding techniques,using microscopic imaging.Three potential defense-sector applications are explored,specifically in the aerospace,automotive,and energy industries.Additionally,the influence of key printing parameters,particularly nonparallel plane deposition at a 45-degree angle,on the mechanical behavior of ABS reinforced with 20%glass fiber(GF)is examined.The results demonstrate the feasibility of this manufacturing approach,highlighting reductions in waste material and production times compared to traditional methods.Shorter layer times were found to reduce thermal gradients between layers,thereby improving layer adhesion.While 45-degree deposition enhanced Young's modulus,it slightly reduced interlayer adhesion quality.Furthermore,recycling-induced fiber length reduction led to material degradation,aligning with findings from previous studies.Challenges encountered during implementation included weak part adherence to the print bed and local excess material deposition.Overall,the proposed methodology offers a cost-effective alternative to traditional CNC machining for mold production,demonstrating its potential for on-demand manufacturing in resource-constrained environments.
基金supported in part by the National Natural Science Foundation of China(NSFC)(62202192 and 72101094)the National Science Fund for Distinguished Young Scholars of China(51825502).
文摘As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for solving FJSP in the literature are population-based evolutionary algorithms,which are complex and time-consuming.In this paper,we propose a fast effective singlesolution based local search algorithm with an innovative adaptive weighting-based local search(AWLS)technique for solving FJSP.The adaptive weighting technique assigns weights to each operation and adaptively updates them during the exploration.AWLS integrates a Tabu Search strategy and the adaptive weighting technique to smooth the landscape of the search space and enhance the exploration diversity.Computational experiments on 313 well-known benchmark instances demonstrate that AWLS is highly competitive with state-of-the-art algorithms in terms of both solution quality and computational efficiency,despite of its simplicity.Specifically,AWLS improves the previous best-known results in the literature on 33 instances and match the best-known results on the remaining ones except for only one under the same time limit of up to 300 s.As a strongly non-deterministic polynomia(NP)-hard problem which has been extensively studied for nearly half a century,breaking the records on these classic instances is an arduous task.Nevertheless,AWLS establishes new records on 8 challenging instances whose previous best records were established by a state-of-the-art meta-heuristic algorithm and a famous industrial solver.
基金supported by the National Natural Science Foundation of China(NSFC,52277223 and 51977131)the Shanghai Pujiang Programme(23PJD062)。
文摘Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection methods during manufacturing is critical yet challenging.This study introduces a deep learning-based method for detecting lithium-plating-type defects using formation and capacity grading data,enabling accurate identification of defective batteries without additional equipment.First,lithiumplating-type defect batteries with various types and area ratios are fabricated.Formation and capacity grading data from 154 batteries(48 defective,106 normal)are collected to construct a dataset.Subsequently,a dual-task deep learning model is then developed,where the reconstruction task learns latent representations from the features,while the classification task identifies the defective batteries.Shapley value analysis further quantifies feature importance,revealing that defective batteries exhibit reduced coulombic efficiency(attributed to irreversible lithium loss)and elevated open-circuit voltage/K-values(linked to self-equalization effects).These findings align with the electrochemical mechanisms of lithium plating,enhancing the model's interpretability.Validated on statistically robust samples shows that the framework achieves a recall of 97.14%for defective batteries and an overall accuracy of 97.42%.This deep learning-driven solution provides a scalable and cost-effective quality control strategy for battery manufacturing.
基金support from the Research Committee of The Hong Kong Polytechnic University(Project codes:RMJK and 4-ZZSJ)supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.PolyU15212523).
文摘Additive manufacturing(AM),with its high flexibility,cost-effectiveness,and customization,significantly accelerates the advancement of nanogenerators,contributing to sustainable energy solutions and the Internet of Things.In this review,an in-depth analysis of AM for piezoelectric and triboelectric nanogenerators is presented from the perspectives of fundamental mechanisms,recent advancements,and future prospects.It highlights AM-enabled advantages of versatility across materials,structural topology optimization,microstructure design,and integrated printing,which enhance critical performance indicators of nanogenerators,such as surface charge density and piezoelectric constant,thereby improving device performance compared to conventional fabrication.Common AM techniques for nanogenerators,including fused deposition modeling,direct ink writing,stereolithography,and digital light processing,are systematically examined in terms of their working principles,improved metrics(output voltage/current,power density),theoretical explanation,and application scopes.Hierarchical relationships connecting AM technologies with performance optimization and applications of nanogenerators are elucidated,providing a solid foundation for advancements in energy harvesting,self-powered sensors,wearable devices,and human-machine interaction.Furthermore,the challenges related to fabrication quality,cross-scale manufacturing,processing efficiency,and industrial deployment are critically discussed.Finally,the future prospects of AM for nanogenerators are explored,aiming to foster continuous progress and innovation in this field.
基金supported in part by China Scholarship Council under Grant 202208200010。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising technique for producing large-scale metal components,favoured by high deposition rates,flexibility and low cost.Despite its potential,the complexity of WAAM processes,which involves intricate thermal dynamics,phase transitions,and metallurgical,mechanical,and chemical interactions,presents considerable challenges in final product qualities.Simulation technologies in WAAM have proven invaluable,providing accurate predictions in key areas such as material properties,defect identification,deposit morphology,and residual stress.These predictions play a critical role in optimising manufacturing strategies for the final product.This paper provides a comprehensive review of the simulation techniques applied in WAAM,tracing developments from 2013 to 2023.Initially,it analyses the current challenges faced by simulation methods in three main areas.Subsequently,the review explores the current modelling approaches and the applications of these simulations.Following this,the paper discusses the present state of WAAM simulation,identifying specific issues inherent to WAAM simulation itself.Finally,through a thorough review of existing literature and related analysis,the paper offers future perspectives on potential advancements in WAAM simulation strategies.
基金supported by the National Natural Science Foundation of China(Grants Nos.62104125and 62311530102)Shenzhen Science and Technology Program(Grant Nos.JCYJ20220530143013030 and JCYJ20240813111910014)+1 种基金Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2021ZT09L197)Tsinghua Shenzhen International Graduate School-Shenzhen Pengrui Young Faculty Program of Shenzhen Pengrui Foundation(Grant No.SZPR2023005)。
文摘The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numerous sensors to realize high levels of perception,precision,safety,adaptability,and intelligence.Triboelectric and piezoelectric sensors address these needs by providing high sensitivity,flexibility,and the capability of self-powered sensing,leveraging the revolutionary nature of nanogenerators to convert mechanical energy into electrical energy on basis of Maxwell’s displacement current.These sensors surpass externally powered passive sensors by offering continuous operation,reduced maintenance,and the capability to function in remote or harsh environments.The integration of EAI with advanced nanogenerators sensors could position robotics to perform autonomously,efficiently,and safely,paving the way for innovative applications in various domains such as industrial automation,environmental monitoring,healthcare,and smart homes.In this paper,the fundamental theories,design,manufacturing,and applications of nanogenerators are comprehensively reviewed as afoundation of the advanced sensors for intelligent robotics in the new era,with three major application fields:sensing(including human–robot interaction,exteroceptive sensing and proprioceptive sensing),computing and actuating.Perspectives are addressed for nanogenerators systems in future development.
基金supported by National Natural Science Foundation of China(Grant No.52305419)Aeronautical Science Foundation Funded by Chinese Aeronautical Establishment(Grant No.2022Z0490T6001)+5 种基金Research Start-up Project of Xi’an University of Technology(Grant No.101-256082204)Technology Foundation for Selected Overseas Chinese Scholar(Grant No.2023-010)International Science and Technology Cooperation Program of Shaanxi Province(Grant No.2023-GHZD-50)Projects of Major Innovation Platforms for Scientific and Technological and Local Transformation of Scientific and Technological Achievements of Xi’an(Grant No.20GXSF0003)Higher Education Institution Discipline Innovation and Intelligence Base of Shaanxi Provincial(Grant No.S2021-ZCGXYZ-0011)Natural Science Basic Research Program of Shaanxi(Grant No.2023-JC-YB-412).
文摘Hetero-deformation induced(HDI) strengthening generally yields a weak effect on the mechanical property improvement of particle-reinforced metal matrix composites(MMCs). In the present work, a novel strategy was reported to induce remarkable HDI strengthening in MMCs by selecting a reinforcing material with excellent geometrically necessary dislocation(GND) storage ability. The viability of the proposed strategy was tested on additively manufactured nickel matrix composites consisting of Inconel 625 alloy(IN625) as the matrix and high-entropy alloy VNbMoTa as the reinforcing material. It was found that the average grain size and dislocation density of the additively manufactured MMCs gradually decreased with the increase in the additional amount of VNbMoTa. All the samples possessed a similar two-layer VNbMoTa-matrix interface structure containing a high-entropy alloy layer and a Laves phase layer;however, the interface width varied. This two-layer interface could hold GND pile-ups without breaking to ensure a good load transfer effect, and ductile VNbMoTa particles demonstrated excellent GND storage capacity to induce significant HDI stress. The HDI stress for the IN625-(10 wt%)VNbMoTa sample was approximately 200 MPa higher than that for the pure IN625 alloy, resulting in an excellent strength-ductility synergy. The yield strength and elongation of the IN625-(10 wt%)VNbMoTa sample reached(1 032.5 ± 18.8)MPa and(11.8 ± 1.2)%, respectively. In addition, the IN625-(10 wt%)VNbMoTa composite also demonstrated superior mechanical properties at 650℃ that were comparable to those at room temperature, implying that VNbMoTa addition remarkably limited strength reduction caused by temperature. Deformable VNbMoTa particles effectively alleviated the stress concentration, delayed the crack initiation, generated more dislocations and pile-ups, and, in turn, improved the overall high-temperature strength of composites.
基金supported by Grants from the National Natural Science Foundation of China(Nos.52205363,52235008 and U2037203)Fundamental Research Funds for the Central Universities(Nos.2019kfyRCPY044 and 2021GCRC002)+1 种基金Program for HUST Academic Frontier Youth Team(No.2018QYTD04)the Program for Innovative Research Team of the Ministry of Education(No.IRT1244)。
文摘Additive manufacturing(AM)offers the unique capability of directly creating three-dimensional complicated ceramic components with high process flexibility and outstanding geometry controllability.However,current ceramic AM technology is mainly limited to the creation of a single material,which falls short of meeting the multiple functional requirements under increasingly harsh service circumstances.Ceramic multi-material additive manufacturing(MMAM)technology has great potential for integrally producing multi-dimensional multi-functional components,allowing for point-by-point precision manufacturing of programmable performance/functions.However,there is a huge gap between the capabilities of the existing ceramic MMAM technology and the requirements for industrial application.In this review,we discuss and summarize the research status of ceramic MMAM technology from the perspectives of feedstock selection,printing process,post-processing,component performance,and application.Throughout the discussion,the challenges associated with ceramic MMAM such as heterogeneous material coupled printing,heterogeneous interfacial bonding,and co-sintering densification have been put forward.This review aims to bridge the gap between AM technologies and the requirements for multifunctional ceramic components by analyzing the existing limitations in ceramic MMAM and pointing out future needs.
基金the financial supports from the ECU industrial Grant(No.G1006320)ECU DVC strategic research support fund(Grant Number 23965)National Natural Science Foundation of China under Grant Nos.52404382,52274387 and 52311530772。
文摘Additive manufacturing has emerged as a transformative technology for producing biomedical metals and implants,offering the potential to revolutionize patient care and treatment outcomes.This article reviews the recent advances in additive manufacturing(AM)of biomedical metal implants,especially load-bearing biomedical alloys,biodegradable alloys,novel metals,and 4D printing,whose properties are systematically assessed to facilitate material selection for specific medical applications.The applications of the most cutting-edge artificial intelligence in AM and surface functional modification are also presented.This article also explores the application of AM in various medical specialties,such as orthopedics,dentistry,cardiology,and neurosurgery,demonstrating its potential to solve complex clinical challenges and advance patient-centered healthcare solutions.Furthermore,it highlights the critical roles of AM in shaping the future of medical implant manufacturing.The optimistic outlook on the bright future of AM in medical metals delivers personalized,high-performance medical implants that improve patient treatment outcomes and well-being.
