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
SiC is a wave-absorbing material with good dielectric properties,high-temperature resistance,and corrosion resistance,which has great potential for development in the field of high-temperature wave-absorbing.However,S...SiC is a wave-absorbing material with good dielectric properties,high-temperature resistance,and corrosion resistance,which has great potential for development in the field of high-temperature wave-absorbing.However,SiC is limited by its low impedance-matching performance and single wave-absorbing mechanism.Therefore,compatible metamaterial technologies are required to enhance its wave-absorbing performance further.The electromagnetic wave(EMW)absorbing metamaterials can realize perfect absorption of EMWs in specific frequency bands and precise regulation of EMW phase,propagation mode,and absorption frequency bands through structural changes.However,the traditional molding methods for manufacturing complex geometric shapes require expensive molds,involve process complexity,and have poor molding accuracy and other limitations.Therefore,additive manufacturing(AM)technology,through material layered stacking to achieve the processing of materials,is a comprehensive multidisciplinary advanced manufacturing technology and has become the core technology for manufacturing metamaterials.This review introduces the principles and applications of different AM technologies for SiC and related materials,discusses the current status and development trends of various AM technologies for fabricating silicon-carbon-based wave-absorbing metamaterials,summarizes the limitations and technological shortcomings of existing AM technologies for fabricating silicon-carbon-based wave-absorbing metamaterials,and provides an outlook for the future development of related AM technologies.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
The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a block...The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a blockchain-enabled manufacturing collaboration framework is proposed,with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P)collaboration.First,a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain.Second,an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants.Third,a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information.It facilitates automation of the matching process while protecting users'privacy via blockchainbased smart contracts.Finally,simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4%compared to the Bayesian game-based approach,makes all participants profitable,and achieves 90%fairness of enterprises.展开更多
Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,re...Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.展开更多
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye...At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.展开更多
The functionally graded materials(FGMs)are obtained by various processes.Although a few FGMs are obtained naturally,such as oyster,pearl,and bamboo,additive manufacturing(AM),known as 3D printing,is a net-shaped manuf...The functionally graded materials(FGMs)are obtained by various processes.Although a few FGMs are obtained naturally,such as oyster,pearl,and bamboo,additive manufacturing(AM),known as 3D printing,is a net-shaped manufacturing process employed to manufacture complex 3D objects without tools,molds,assembly,and joining.Currently,commercial AM techniques mostly use homogeneous composition with simplified geometric descriptions,employing a single material across the entire component to achieve functional graded additive manufacturing(FGAM),in contrast to multi-material FGAM with heterogeneous structures.FGMs are widely used in various fields due to their mechanical property advantages.Because FGM plays a significant role in the industrial production,the characteristics and mechanical behaviour of FGMs prepared by AM were reviewed.In this review,the research on FGMs and AM over the past 30 years was reviewed,suggesting that future researchers should focus on the application of artificial intelligence and machine learning technologies in industry to optimize the process parameters of different gradient systems.展开更多
Friction rolling additive manufacturing(FRAM)is a solid-state additive manufacturing technology that plasticizes the feed and deposits a material using frictional heat generated by the tool head.The thermal efficiency...Friction rolling additive manufacturing(FRAM)is a solid-state additive manufacturing technology that plasticizes the feed and deposits a material using frictional heat generated by the tool head.The thermal efficiency of FRAM,which depends only on friction to generate heat,is low,and the thermal-accumulation effect of the deposition process must be addressed.An FRAM heat-balance-control method that combines plasma-arc preheating and instant water cooling(PC-FRAM)is devised in this study,and a temperature field featuring rapidly increasing and decreasing temperature is constructed around the tool head.Additionally,2195-T87 Al-Li alloy is used as the feed material,and the effects of heating and cooling rates on the microstructure and mechanical properties are investigated.The results show that water cooling significantly improves heat accumulation during the deposition process.The cooling rate increases by 11.7 times,and the high-temperature residence time decreases by more than 50%.The grain size of the PC-FRAM sample is the smallest,i.e.,3.77±1.03μm,its dislocation density is the highest,and the number density of precipitates is the highest,the size of precipitates is the smallest,which shows the best precipitation-strengthening effect.The hardness test results are consistent with the precipitation distribution.The ultimate tensile strength,yield strength and elongation of the PC-FRAM samples are the highest(351±15.6 MPa,251.3±15.8 MPa and 16.25%±1.25%,respectively)among the samples investigated.The preheating and water-cooling-assisted deposition simultaneously increases the tensile strength and elongation of the deposited samples.The combination of preheating and instant cooling improves the deposition efficiency of FRAM and weakens the thermal-softening effect.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
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose s...The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose significant challenges for battery development.These conditions drive the need for specialized designs in deep-sea batteries,incorporating critical aspects of power generation,protection,distribution,and management.Over time,deep-sea battery technology has evolved through multiple generations,with lithium(Li)batteries emerging in recent decades as the preferred power source due to their high energy and reduced operational risks.Although the rapid progress of Li batteries has notably advanced the capabilities of underwater vehicles,critical technical issues remain unresolved.This review first systematically presents the whole picture of deep-sea battery manufacturing,focusing on Li batteries as the current mainstream solution for underwater power.It examines the key aspects of deep-sea Li battery development,including materials selection informed by electro-chemo-mechanics models,component modification and testing,and battery management systems specialized in software and hardware.Finally,it discusses the main challenges limiting the utilization of deep-sea batteries and outlines promising directions for future development.Based on the systematic reflection on deep-sea batteries and discussion on deep-sea Li batteries,this review aims to provide a research foundation for developing underwater power tailored for extreme environmental exploration.展开更多
To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and l...To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.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
A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are ...A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.展开更多
Intelligent manufacturing is a crucial path for promoting the transformation and upgrading of the manufacturing industr y. St andardization, connecting innovation, production, market s and ser v ices, plays an indispe...Intelligent manufacturing is a crucial path for promoting the transformation and upgrading of the manufacturing industr y. St andardization, connecting innovation, production, market s and ser v ices, plays an indispensable role in the development of intelligent manufacturing. This paper aims to explore the mechanism by which standardization aids in the high-quality development of the manufacturing industry in three aspects: standards are useful tools to identify the intelligent shortcomings of manufacturing enterprises;standards provide intelligent solutions for manufacturing enterprises;standards system guides the development of manufacturing industry. It is expected to provide insights for enterprises to facilitate their intelligent construction via standards, thereby boosting the intelligent development of the industry.展开更多
As the demand for intelligent and flexible production in the automotive manufacturing industry continues to intensify,industrial automation enterprises are gaining ever-greater market opportunities and competitive adv...As the demand for intelligent and flexible production in the automotive manufacturing industry continues to intensify,industrial automation enterprises are gaining ever-greater market opportunities and competitive advantages in this field.Based on a literature review and representative case studies,this paper constructs a theoretical framework for growth strategies and systematically analyzes the current application status and growth paths of automation enterprises in both complete vehicle and component production.The research finds that different growth strategies(such as vertical integration,horizontal diversification,and digital service transformation)exhibit varying applicability across upstream and downstream segments of automotive manufacturing,while simultaneously facing challenges related to technology integration,business models,and organizational change.In response to these issues,this paper proposes countermeasures such as optimizing R&D and customer relationship management,improving branding and after-sales service systems,and strengthening policy and industry environment support,thereby offering guidance for sustainable growth of industrial automation enterprises in the automotive manufacturing sector.展开更多
The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are ...The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are difficult to achieve efficient and real-time production management under dynamic disturbance.In order to improve the intelligence and adaptability of production scheduler,a novel distributed scheduling architecture is proposed,which has the ability to autonomously allocate tasks and handle disturbances.All production tasks are scheduled through autonomous collaboration and decision-making between intelligent machines.Firstly,the multi-agent technology is applied to build a self-organizing manufacturing system,enabling each machine to be equipped with the ability of active information interaction and joint-action execution.Secondly,various self-organizing collaboration strategies are designed to effectively facilitate cooperation and competition among multiple agents,thereby flexibly achieving global perception of environmental state.To ensure the adaptability and superiority of production decisions in dynamic environment,deep reinforcement learning is applied to build a smart production scheduler:Based on the perceived environment state,the scheduler intelligently generates the optimal production strategy to guide the task allocation and resource configuration.The feasibility and effectiveness of the proposed method are verified through three experimental scenarios using a discrete manufacturing workshop as the test bed.Compared to heuristic dispatching rules,the proposed method achieves an average performance improvement of 34.0%in three scenarios in terms of order tardiness.The proposed system can provide a new reference for the design of smart manufacturing systems.展开更多
This paper focuses on the roles of smart manufacturing and digital economy integration in driving the transformation and upgrading of the manufacturing industry.Smart manufacturing integrates advanced technologies suc...This paper focuses on the roles of smart manufacturing and digital economy integration in driving the transformation and upgrading of the manufacturing industry.Smart manufacturing integrates advanced technologies such as automation and digital twin,while digital economy takes data as the core driver.Many studies have shown that automation and digital twin technologies can effectively improve productivity,reduce costs and enhance production flexibility.The smart shop floor control system based on digital twin and IoT involves several key technologies such as digital twin integration interface,shop floor modeling and simulation analysis.The deep integration of these technologies not only improves production efficiency and product quality,but also optimizes resource allocation,reduces energy consumption,and provides strong support for the sustainable development of highend manufacturing.This study provides theoretical basis and practical guidance for the intelligent transformation of manufacturing industry.展开更多
The additive manufacturing(AM)landscape has significantly transformed in alignment with Industry 4.0 principles,primarily driven by the integration of artificial intelligence(AI)and digital twins(DT).However,current i...The additive manufacturing(AM)landscape has significantly transformed in alignment with Industry 4.0 principles,primarily driven by the integration of artificial intelligence(AI)and digital twins(DT).However,current intelligent AM(IAM)systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction.This paper reviews existing IAM solutions,emphasizing control,monitoring,process autonomy,and end-to-end integration,and identifies key limitations,such as the absence of a high-level controller for global decision-making.To address these gaps,we propose a transition from IAM to autonomous AM,featuring a hierarchical framework with four integrated layers:knowledge,generative solution,operational,and cognitive.In the cognitive layer,AI agents notably enable machines to independently observe,analyze,plan,and execute operations that traditionally require human intervention.These capabilities streamline production processes and expand the possibilities for innovation,particularly in sectors like in-space manufacturing.Additionally,this paper discusses the role of AI in self-optimization and lifelong learning,positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy,fostering a more adaptive,resilient manufacturing ecosystem.展开更多
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
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supported by National Natural Science Foundation of China(Grant No.U2006218)Project of Construction and Support for High-Level Innovative Teams of Beijing Municipal Institutions(Grant No.BPHR20220124).
文摘SiC is a wave-absorbing material with good dielectric properties,high-temperature resistance,and corrosion resistance,which has great potential for development in the field of high-temperature wave-absorbing.However,SiC is limited by its low impedance-matching performance and single wave-absorbing mechanism.Therefore,compatible metamaterial technologies are required to enhance its wave-absorbing performance further.The electromagnetic wave(EMW)absorbing metamaterials can realize perfect absorption of EMWs in specific frequency bands and precise regulation of EMW phase,propagation mode,and absorption frequency bands through structural changes.However,the traditional molding methods for manufacturing complex geometric shapes require expensive molds,involve process complexity,and have poor molding accuracy and other limitations.Therefore,additive manufacturing(AM)technology,through material layered stacking to achieve the processing of materials,is a comprehensive multidisciplinary advanced manufacturing technology and has become the core technology for manufacturing metamaterials.This review introduces the principles and applications of different AM technologies for SiC and related materials,discusses the current status and development trends of various AM technologies for fabricating silicon-carbon-based wave-absorbing metamaterials,summarizes the limitations and technological shortcomings of existing AM technologies for fabricating silicon-carbon-based wave-absorbing metamaterials,and provides an outlook for the future development of related AM technologies.
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 in part by the National Natural Science Foundation of China(62273310)the Natural Science Foundation of Zhejiang Province of China(LY22F030006,LZ24F030009)
文摘The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a blockchain-enabled manufacturing collaboration framework is proposed,with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P)collaboration.First,a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain.Second,an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants.Third,a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information.It facilitates automation of the matching process while protecting users'privacy via blockchainbased smart contracts.Finally,simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4%compared to the Bayesian game-based approach,makes all participants profitable,and achieves 90%fairness of enterprises.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2022R1I1A3063493).
文摘Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.
基金supported by the National Key Research and Development Program of China(No.2022YFB3404700)the National Natural Science Foundation of China(Nos.52105313 and 52275299)+2 种基金the Research and Development Program of Beijing Municipal Education Commission,China(No.KM202210005036)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)the National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.
文摘The functionally graded materials(FGMs)are obtained by various processes.Although a few FGMs are obtained naturally,such as oyster,pearl,and bamboo,additive manufacturing(AM),known as 3D printing,is a net-shaped manufacturing process employed to manufacture complex 3D objects without tools,molds,assembly,and joining.Currently,commercial AM techniques mostly use homogeneous composition with simplified geometric descriptions,employing a single material across the entire component to achieve functional graded additive manufacturing(FGAM),in contrast to multi-material FGAM with heterogeneous structures.FGMs are widely used in various fields due to their mechanical property advantages.Because FGM plays a significant role in the industrial production,the characteristics and mechanical behaviour of FGMs prepared by AM were reviewed.In this review,the research on FGMs and AM over the past 30 years was reviewed,suggesting that future researchers should focus on the application of artificial intelligence and machine learning technologies in industry to optimize the process parameters of different gradient systems.
基金supported by the National Natural Science Foundation of China(Nos.52275299,52105313)R&D Program of Beijing Municipal Education Commission(No.KM202210005036)+1 种基金Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘Friction rolling additive manufacturing(FRAM)is a solid-state additive manufacturing technology that plasticizes the feed and deposits a material using frictional heat generated by the tool head.The thermal efficiency of FRAM,which depends only on friction to generate heat,is low,and the thermal-accumulation effect of the deposition process must be addressed.An FRAM heat-balance-control method that combines plasma-arc preheating and instant water cooling(PC-FRAM)is devised in this study,and a temperature field featuring rapidly increasing and decreasing temperature is constructed around the tool head.Additionally,2195-T87 Al-Li alloy is used as the feed material,and the effects of heating and cooling rates on the microstructure and mechanical properties are investigated.The results show that water cooling significantly improves heat accumulation during the deposition process.The cooling rate increases by 11.7 times,and the high-temperature residence time decreases by more than 50%.The grain size of the PC-FRAM sample is the smallest,i.e.,3.77±1.03μm,its dislocation density is the highest,and the number density of precipitates is the highest,the size of precipitates is the smallest,which shows the best precipitation-strengthening effect.The hardness test results are consistent with the precipitation distribution.The ultimate tensile strength,yield strength and elongation of the PC-FRAM samples are the highest(351±15.6 MPa,251.3±15.8 MPa and 16.25%±1.25%,respectively)among the samples investigated.The preheating and water-cooling-assisted deposition simultaneously increases the tensile strength and elongation of the deposited samples.The combination of preheating and instant cooling improves the deposition efficiency of FRAM and weakens the thermal-softening effect.
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funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金support provided by National Key Research and Development Program of China(2023YFE0203000 and 2016YFC0300200)the NSAF(Grant No.U2330205)+3 种基金Full-Sea-Depth Battery Project(2020-XXXX-XX-246-00)Open project of Shaanxi Laboratory of Aerospace Power(2022ZY2-JCYJ-01-09)Fundamental Research Funds for the Central Universities,ND Basic Research Funds(G2022WD)the Innovation Team of Shaanxi Province。
文摘The operation of deep-sea underwater vehicles relies entirely on onboard batteries.However,the extreme deep-sea conditions,characterized by ultrahigh hydraulic pressure,low temperature,and seawater conductivity,pose significant challenges for battery development.These conditions drive the need for specialized designs in deep-sea batteries,incorporating critical aspects of power generation,protection,distribution,and management.Over time,deep-sea battery technology has evolved through multiple generations,with lithium(Li)batteries emerging in recent decades as the preferred power source due to their high energy and reduced operational risks.Although the rapid progress of Li batteries has notably advanced the capabilities of underwater vehicles,critical technical issues remain unresolved.This review first systematically presents the whole picture of deep-sea battery manufacturing,focusing on Li batteries as the current mainstream solution for underwater power.It examines the key aspects of deep-sea Li battery development,including materials selection informed by electro-chemo-mechanics models,component modification and testing,and battery management systems specialized in software and hardware.Finally,it discusses the main challenges limiting the utilization of deep-sea batteries and outlines promising directions for future development.Based on the systematic reflection on deep-sea batteries and discussion on deep-sea Li batteries,this review aims to provide a research foundation for developing underwater power tailored for extreme environmental exploration.
基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Construction Project(2022KXJ-071)2022 Qin Chuangyuan Achievement Transformation Incubation Capacity Improvement Project(2022JH-ZHFHTS-0012)+1 种基金Shaanxi Province Key Research and Development Plan-“Two Chains”Integration Key Project-Qin Chuangyuan General Window Industrial Cluster Project(2023QCY-LL-02)Xixian New Area Science and Technology Plan(2022-YXYJ-003,2022-XXCY-010)。
文摘To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.
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The National Natural Science Foundation of China(No.52305381)the Natural Science Foundation of Jiangsu Province(No.BK20210351)the Fundamental Research Funds for the Central Universities(No.30923011008).
文摘A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.
文摘Intelligent manufacturing is a crucial path for promoting the transformation and upgrading of the manufacturing industr y. St andardization, connecting innovation, production, market s and ser v ices, plays an indispensable role in the development of intelligent manufacturing. This paper aims to explore the mechanism by which standardization aids in the high-quality development of the manufacturing industry in three aspects: standards are useful tools to identify the intelligent shortcomings of manufacturing enterprises;standards provide intelligent solutions for manufacturing enterprises;standards system guides the development of manufacturing industry. It is expected to provide insights for enterprises to facilitate their intelligent construction via standards, thereby boosting the intelligent development of the industry.
文摘As the demand for intelligent and flexible production in the automotive manufacturing industry continues to intensify,industrial automation enterprises are gaining ever-greater market opportunities and competitive advantages in this field.Based on a literature review and representative case studies,this paper constructs a theoretical framework for growth strategies and systematically analyzes the current application status and growth paths of automation enterprises in both complete vehicle and component production.The research finds that different growth strategies(such as vertical integration,horizontal diversification,and digital service transformation)exhibit varying applicability across upstream and downstream segments of automotive manufacturing,while simultaneously facing challenges related to technology integration,business models,and organizational change.In response to these issues,this paper proposes countermeasures such as optimizing R&D and customer relationship management,improving branding and after-sales service systems,and strengthening policy and industry environment support,thereby offering guidance for sustainable growth of industrial automation enterprises in the automotive manufacturing sector.
基金supported by the Scientific Research Foundation of Nanjing Institute of Technology(No.YKJ202425)the National Natural Science Foundation of China(No.72301130).
文摘The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are difficult to achieve efficient and real-time production management under dynamic disturbance.In order to improve the intelligence and adaptability of production scheduler,a novel distributed scheduling architecture is proposed,which has the ability to autonomously allocate tasks and handle disturbances.All production tasks are scheduled through autonomous collaboration and decision-making between intelligent machines.Firstly,the multi-agent technology is applied to build a self-organizing manufacturing system,enabling each machine to be equipped with the ability of active information interaction and joint-action execution.Secondly,various self-organizing collaboration strategies are designed to effectively facilitate cooperation and competition among multiple agents,thereby flexibly achieving global perception of environmental state.To ensure the adaptability and superiority of production decisions in dynamic environment,deep reinforcement learning is applied to build a smart production scheduler:Based on the perceived environment state,the scheduler intelligently generates the optimal production strategy to guide the task allocation and resource configuration.The feasibility and effectiveness of the proposed method are verified through three experimental scenarios using a discrete manufacturing workshop as the test bed.Compared to heuristic dispatching rules,the proposed method achieves an average performance improvement of 34.0%in three scenarios in terms of order tardiness.The proposed system can provide a new reference for the design of smart manufacturing systems.
文摘This paper focuses on the roles of smart manufacturing and digital economy integration in driving the transformation and upgrading of the manufacturing industry.Smart manufacturing integrates advanced technologies such as automation and digital twin,while digital economy takes data as the core driver.Many studies have shown that automation and digital twin technologies can effectively improve productivity,reduce costs and enhance production flexibility.The smart shop floor control system based on digital twin and IoT involves several key technologies such as digital twin integration interface,shop floor modeling and simulation analysis.The deep integration of these technologies not only improves production efficiency and product quality,but also optimizes resource allocation,reduces energy consumption,and provides strong support for the sustainable development of highend manufacturing.This study provides theoretical basis and practical guidance for the intelligent transformation of manufacturing industry.
基金funded by the MUREP High Volume project(80NSSC22M0132)through the U.S.NASA Office of STEM Engagementthe SMART IAC Project(DE-EE0009726)through the U.S.Department of Energy Office of Manufacturing and Energy Supply Chainssupport of San Diego Supercomputer Center(SDSC)National Research Platform(NRP)Nautilus sponsored by the U.S.NSF(2100237,2120019)。
文摘The additive manufacturing(AM)landscape has significantly transformed in alignment with Industry 4.0 principles,primarily driven by the integration of artificial intelligence(AI)and digital twins(DT).However,current intelligent AM(IAM)systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction.This paper reviews existing IAM solutions,emphasizing control,monitoring,process autonomy,and end-to-end integration,and identifies key limitations,such as the absence of a high-level controller for global decision-making.To address these gaps,we propose a transition from IAM to autonomous AM,featuring a hierarchical framework with four integrated layers:knowledge,generative solution,operational,and cognitive.In the cognitive layer,AI agents notably enable machines to independently observe,analyze,plan,and execute operations that traditionally require human intervention.These capabilities streamline production processes and expand the possibilities for innovation,particularly in sectors like in-space manufacturing.Additionally,this paper discusses the role of AI in self-optimization and lifelong learning,positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy,fostering a more adaptive,resilient manufacturing ecosystem.
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.
