Occupational structural transformation is a common pattern during the steady growth of GDP per capita in major economies worldwide.In recent years,there has been a decline in the employment share of goods occupation a...Occupational structural transformation is a common pattern during the steady growth of GDP per capita in major economies worldwide.In recent years,there has been a decline in the employment share of goods occupation and an increase in service occupation within the Chinese manufacturing industry,presenting a trend of occupational structural transformation and rapid development of service-oriented manufacturing.It is an important driving force and typical performance of the high-end,intelligent,and green development of the manufacturing industry.As a strategic general technology which leads the new round of technological revolution and industrial transformation,artificial intelligence(AI)has become a new fundamental force to accelerate the occupational structural transformation and service-oriented manufacturing development in China.Thus,this paper establishes a dynamic general equilibrium model with AI technology and occupational heterogeneity,showing the endogenous mechanism of occupational structural transformation.We find that when AI technology is biased towards goods occupation,and the elasticity of substitution between goods occupation and service occupation is less than 1,then AI will drive the transformation of occupational structure from goods to service within the manufacturing sector,increase the proportion of service-oriented manufacturing,improve labor productivity of manufacturing relative to service and stabilize the real output share of manufacturing.Promoting deeper integration of different occupations,intensifying R&D in AI technology and reducing labor mobility barriers between occupations can effectively accelerate the occupational structural transformation and industrial structural upgrading.We use theoretical analysis and numerical simulation method to show the theoretical mechanism by which AI affects occupational structural transformation and industrial structural transformation from a macroeconomic perspective,and put forward policy implications on how to promote the service-oriented manufacturing development and accelerate the construction of modern industrial system through AI innovation.展开更多
The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data f...The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data flexibility, process flexibility and system flexibility. We select some questionnaires from the third round of High-performance manufacturing (HPM) data to construct the construct, verify the reliability and validity of the construct, extract principal components, and analyze the mediating effect by using multiple chain linear regression and structural equation model. The results show that SMIS customization has a significant impact on its performance, and this effect works through its flexibility. More specifically, it is the multiple chain mediation effect composed of data flexibility, process flexibility and system flexibility. The importance of SMIS customization and flexibility to the organization is made clear, which helps practitioners understand the internal mechanism that affects SMIS performance, so as to use limited resources to improve system performance.展开更多
This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous revie...This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous reviews.This study proposes a classification framework for SOM research based on product flow,from its design to its final disposal.Although SOM has been studied for many years,most related research remains conceptual.Our criterion for choosing papers is that they must be relevant to practical problems.This review aims to provide readers a guide that will facilitate their search for papers in their field of interest.More importantly,we hope that this review can provide insightful managerial implications for SOM.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.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
Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps...Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps it fresh,a cooker hood that remains clean even after 10 years without disassembling it for cleaning.展开更多
The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them w...The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.展开更多
To improve efficiency,reduce cost,ensure quality effectively,researchers on CNC machining have focused on virtual machine tool,cloud manufacturing,wireless manufacturing.However,low level of information shared among d...To improve efficiency,reduce cost,ensure quality effectively,researchers on CNC machining have focused on virtual machine tool,cloud manufacturing,wireless manufacturing.However,low level of information shared among different systems is a common disadvantage.In this paper,a machining database with data evaluation module is set up to ensure integrity and update.An online monitoring system based on internet of things and multi-sensors"feel"a variety of signal features to"percept"the state in CNC machining process.A high efficiency and green machining parameters optimization system"execute"service-oriented manufacturing,intelligent manufacturing and green manufacturing.The intelligent CNC machining system is applied in production.CNC machining database effectively shares and manages process data among different systems.The prediction accuracy of online monitoring system is up to 98.8%by acquiring acceleration and noise in real time.High efficiency and green machining parameters optimization system optimizes the original processing parameters,and the calculation indicates that optimized processing parameters not only improve production efficiency,but also reduce carbon emissions.The application proves that the shared and service-oriented CNC machining system is reliable and effective.This research presents a shared and service-oriented CNC machining system for intelligent manufacturing process.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
Intelligent manufacturing(IM),a driving force behind the fourth industrial revolution,is reshaping the manufacturing sector by enhancing productivity,efficiency,and sustainability.Despite the rapid technological advan...Intelligent manufacturing(IM),a driving force behind the fourth industrial revolution,is reshaping the manufacturing sector by enhancing productivity,efficiency,and sustainability.Despite the rapid technological advancements in IM,comprehensive bibliometric reviews remain limited.This article systematically reviews the latest research in IM,addressing emerging hotspots,key technologies,and their applications across the entire product manufacturing cycle.Bibliometric analysis is employed to identify research trends visualize publication volume,collaboration patterns,research domains,co-citations,and emerging areas of interest.The article then examines key technologies supporting IM,including sensors,the Internet of Things(IoT),big data analytics,cloud computing,artificial intelligence(AI),digital twins,and virtual reality(VR)/augmented reality(AR).Furthermore,it explores the application of these technologies throughout the manufacturing cycle-from intelligent reliability design,material transportation and tracking,to intelligent planning and scheduling,machining and fabrication,monitoring and maintenance,quality inspection and control,warehousing and management,and sustainable green manufacturing—through specific case studies.Lastly,the article discusses future research directions,highlighting the increasing global market and the need for enhanced interdisciplinary collaboration,technological integration,computing power upgrades,and attention to security and privacy in IM.This study provides valuable insights for scholars and serves as a guide for future research and strategic investment decisions,offering a comprehensive view of the IM field.展开更多
Laser additive manufacturing(LAM)has been widely used in high-end manufacturing fields such as aerospace,nuclear power,and shipbuilding.However,it is a grand challenge for direct and continuous observation of complex ...Laser additive manufacturing(LAM)has been widely used in high-end manufacturing fields such as aerospace,nuclear power,and shipbuilding.However,it is a grand challenge for direct and continuous observation of complex laser-matter interaction,melt flow,and defect formation during LAM due to extremely large temperature gradient,fast cooling rate,and small time(millisecond)and space(micron)scales.The emergence of synchrotron radiation provides a feasible approach for in situ observation of the LAM process.This paper outlines the current development in real-time characterization of LAM by synchrotron radiation,including laser-matter interaction,molten pool evolution,solidification structure evolution,and defects formation and elimination.Furthermore,the future development direction and application-oriented research are also discussed.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
The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This pap...The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This paper aims to reveal the impact mechanism of the data elements on the“three transformations”(high-end,intelligent,and green)in the manufacturing sector,theoretically elucidating the intrinsic mechanisms by which the data elements influence these transformations.The study finds that the data elements significantly enhance the high-end,intelligent,and green levels of China's manufacturing industry.In terms of the pathways of impact,the data elements primarily influence the development of high-tech industries and overall green technological innovation,thereby affecting the high-end,intelligent,and green transformation of the industry.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 mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial....The mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial.Mixing intensification encompasses innovative methods and tools that address the limitations of inadequate mixing within reactors,enabling efficient reaction scaling and boosting the productivity of industrial processes.This review provides a concise introduction to the fundamentals of multiphase mixing,followed by case studies highlighting the application of mixing intensification in the production of energy-storage materials,advanced optical materials,and nanopesticides.These examples illustrate the significance of theoretical analysis in informing and advancing engineering practices within the chemical industry.We also explore the challenges and opportunities in this field,offering insights based on our current understanding.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
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
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
基金This study was supported by:The Late-Stage Support Program of the National Social Science Fund of China“Supply-Side Structural Reform and the Dual Structural Transformation of China's Economy”(Grant No.22FJLB009)The National Natural Science Fund of China for Young Scholars“The Dual Structural Transformation of China’s Economy:A Theoretical Analysis and Empirical Test Based on the Supply-Side Structural Reform”(Grant No.71703056).
文摘Occupational structural transformation is a common pattern during the steady growth of GDP per capita in major economies worldwide.In recent years,there has been a decline in the employment share of goods occupation and an increase in service occupation within the Chinese manufacturing industry,presenting a trend of occupational structural transformation and rapid development of service-oriented manufacturing.It is an important driving force and typical performance of the high-end,intelligent,and green development of the manufacturing industry.As a strategic general technology which leads the new round of technological revolution and industrial transformation,artificial intelligence(AI)has become a new fundamental force to accelerate the occupational structural transformation and service-oriented manufacturing development in China.Thus,this paper establishes a dynamic general equilibrium model with AI technology and occupational heterogeneity,showing the endogenous mechanism of occupational structural transformation.We find that when AI technology is biased towards goods occupation,and the elasticity of substitution between goods occupation and service occupation is less than 1,then AI will drive the transformation of occupational structure from goods to service within the manufacturing sector,increase the proportion of service-oriented manufacturing,improve labor productivity of manufacturing relative to service and stabilize the real output share of manufacturing.Promoting deeper integration of different occupations,intensifying R&D in AI technology and reducing labor mobility barriers between occupations can effectively accelerate the occupational structural transformation and industrial structural upgrading.We use theoretical analysis and numerical simulation method to show the theoretical mechanism by which AI affects occupational structural transformation and industrial structural transformation from a macroeconomic perspective,and put forward policy implications on how to promote the service-oriented manufacturing development and accelerate the construction of modern industrial system through AI innovation.
文摘The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data flexibility, process flexibility and system flexibility. We select some questionnaires from the third round of High-performance manufacturing (HPM) data to construct the construct, verify the reliability and validity of the construct, extract principal components, and analyze the mediating effect by using multiple chain linear regression and structural equation model. The results show that SMIS customization has a significant impact on its performance, and this effect works through its flexibility. More specifically, it is the multiple chain mediation effect composed of data flexibility, process flexibility and system flexibility. The importance of SMIS customization and flexibility to the organization is made clear, which helps practitioners understand the internal mechanism that affects SMIS performance, so as to use limited resources to improve system performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.71671033,71971052,71790614,and 71871207)the Fundamental Research Funds for the Central Universities(Grant No.N2006006)+2 种基金the Project of Promoting Talents in Liaoning Province(Grant No.XLYC1807252)the 111 Project(Grant No.B16009)the Project of Longgang Innovation Research Institute of Shenzhen University(Grant No.SZJR006).
文摘This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous reviews.This study proposes a classification framework for SOM research based on product flow,from its design to its final disposal.Although SOM has been studied for many years,most related research remains conceptual.Our criterion for choosing papers is that they must be relevant to practical problems.This review aims to provide readers a guide that will facilitate their search for papers in their field of interest.More importantly,we hope that this review can provide insightful managerial implications for SOM.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
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.
文摘Nanjing’s determination to transform itself from a production base to a research center reflects China’s evolution toward higher-quality development.A refrigerator that thaws frozen meat in 10 minutes and then keeps it fresh,a cooker hood that remains clean even after 10 years without disassembling it for cleaning.
文摘The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.
基金Supported by National Defense Basic Scientific Research of China(Grant No.A2120110002)National Science Foundation of China(Grant No.11290144)Major National Science and Technology Special Project of China(Grant Nos.2010ZX04014-052,2010ZX0414-017)
文摘To improve efficiency,reduce cost,ensure quality effectively,researchers on CNC machining have focused on virtual machine tool,cloud manufacturing,wireless manufacturing.However,low level of information shared among different systems is a common disadvantage.In this paper,a machining database with data evaluation module is set up to ensure integrity and update.An online monitoring system based on internet of things and multi-sensors"feel"a variety of signal features to"percept"the state in CNC machining process.A high efficiency and green machining parameters optimization system"execute"service-oriented manufacturing,intelligent manufacturing and green manufacturing.The intelligent CNC machining system is applied in production.CNC machining database effectively shares and manages process data among different systems.The prediction accuracy of online monitoring system is up to 98.8%by acquiring acceleration and noise in real time.High efficiency and green machining parameters optimization system optimizes the original processing parameters,and the calculation indicates that optimized processing parameters not only improve production efficiency,but also reduce carbon emissions.The application proves that the shared and service-oriented CNC machining system is reliable and effective.This research presents a shared and service-oriented CNC machining system for intelligent manufacturing process.
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.
基金Supported by National Natural Science Foundation of China(Grant Nos.52375447,52305477 and 52105457)the Shandong Provincial Natural Science Foundation of China(Grant Nos.ZR2023QE057,ZR2024QE100 and ZR2024ME255)+2 种基金Qingdao Municipal Science and Technology Planning Park Cultivation Plan(Grant No.23-1-5-yqpy-17-qy)Shandong Provincial Science and Technology SMEs Innovation Capacity Improvement Project(Grant No.2022TSGC1115)the Special Fund of Taishan Scholars Project。
文摘Intelligent manufacturing(IM),a driving force behind the fourth industrial revolution,is reshaping the manufacturing sector by enhancing productivity,efficiency,and sustainability.Despite the rapid technological advancements in IM,comprehensive bibliometric reviews remain limited.This article systematically reviews the latest research in IM,addressing emerging hotspots,key technologies,and their applications across the entire product manufacturing cycle.Bibliometric analysis is employed to identify research trends visualize publication volume,collaboration patterns,research domains,co-citations,and emerging areas of interest.The article then examines key technologies supporting IM,including sensors,the Internet of Things(IoT),big data analytics,cloud computing,artificial intelligence(AI),digital twins,and virtual reality(VR)/augmented reality(AR).Furthermore,it explores the application of these technologies throughout the manufacturing cycle-from intelligent reliability design,material transportation and tracking,to intelligent planning and scheduling,machining and fabrication,monitoring and maintenance,quality inspection and control,warehousing and management,and sustainable green manufacturing—through specific case studies.Lastly,the article discusses future research directions,highlighting the increasing global market and the need for enhanced interdisciplinary collaboration,technological integration,computing power upgrades,and attention to security and privacy in IM.This study provides valuable insights for scholars and serves as a guide for future research and strategic investment decisions,offering a comprehensive view of the IM field.
基金supported by the National Natural Science Foundation of China-Distinguished Young Scholars(No.52325407)the National Natural Science Foundation of China-Key Program(No.52234010)the Open Research Fund of the State Key Laboratory of Rolling and Automation,Northeastern University(No.2022RALKFKT004).
文摘Laser additive manufacturing(LAM)has been widely used in high-end manufacturing fields such as aerospace,nuclear power,and shipbuilding.However,it is a grand challenge for direct and continuous observation of complex laser-matter interaction,melt flow,and defect formation during LAM due to extremely large temperature gradient,fast cooling rate,and small time(millisecond)and space(micron)scales.The emergence of synchrotron radiation provides a feasible approach for in situ observation of the LAM process.This paper outlines the current development in real-time characterization of LAM by synchrotron radiation,including laser-matter interaction,molten pool evolution,solidification structure evolution,and defects formation and elimination.Furthermore,the future development direction and application-oriented research are also discussed.
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.
文摘The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This paper aims to reveal the impact mechanism of the data elements on the“three transformations”(high-end,intelligent,and green)in the manufacturing sector,theoretically elucidating the intrinsic mechanisms by which the data elements influence these transformations.The study finds that the data elements significantly enhance the high-end,intelligent,and green levels of China's manufacturing industry.In terms of the pathways of impact,the data elements primarily influence the development of high-tech industries and overall green technological innovation,thereby affecting the high-end,intelligent,and green transformation of the industry.
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 by the National Natural Science Foundation of China(22288102,22035007,and 22122815)。
文摘The mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial.Mixing intensification encompasses innovative methods and tools that address the limitations of inadequate mixing within reactors,enabling efficient reaction scaling and boosting the productivity of industrial processes.This review provides a concise introduction to the fundamentals of multiphase mixing,followed by case studies highlighting the application of mixing intensification in the production of energy-storage materials,advanced optical materials,and nanopesticides.These examples illustrate the significance of theoretical analysis in informing and advancing engineering practices within the chemical industry.We also explore the challenges and opportunities in this field,offering insights based on our current understanding.
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 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.
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.
