The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational per...The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.展开更多
This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To...This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker's algorithm(MBA) to ensure that all resources required by these jobs can be freed. Moreover,a Petri net based deadlock avoidance policy(DAP) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.展开更多
Deadlock avoidance problems are investigated for automated manufacturing systems with flexible routings. Based on the Petri net models of the systems, this paper proposes, for the first time, the concept of perfect ma...Deadlock avoidance problems are investigated for automated manufacturing systems with flexible routings. Based on the Petri net models of the systems, this paper proposes, for the first time, the concept of perfect maximal resourcetransition circuits and their saturated states. The concept facilitates the development of system liveness characterization and deadlock avoidance Petri net supervisors. Deadlock is characterized as some perfect maximal resource-transition circuits reaching their saturated states. For a large class of manufacturing systems, which do not contain center resources, the optimal deadlock avoidance Petri net supervisors are presented. For a general manufacturing system, a method is proposed for reducing the system Petri net model so that the reduced model does not contain center resources and, hence, has optimal deadlock avoidance Petri net supervisor. The controlled reduced Petri net model can then be used as the liveness supervisor of the system.展开更多
Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators...Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors （S2ensors） to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems （SMS）. The concept, classification, operational logics, and for- malization of S2ensors are clarified. S2ensors collect sub- jective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2en- sors-Cloud platform is discussed to integrate different S2- ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors- Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.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
In-space 3D printing is transforming the manufacturing paradigm of space structures from ground-based production to in-situ space manufacturing,effectively addressing the challenges of high costs,long response times,a...In-space 3D printing is transforming the manufacturing paradigm of space structures from ground-based production to in-situ space manufacturing,effectively addressing the challenges of high costs,long response times,and structural size limitations associated with traditional rocket launches.This technology enables rapid on-orbit emergency repairs and significantly expands the geometric dimensions of space structures.High-performance polymers and their composites are widely used in in-space 3D printing,yet their implementation faces complex challenges posed by extreme space environmental conditions and limited energy or resources.This paper reviews the state-of-the-art in 3D printing of polymer and composites for on-orbit structure manufacturing.Based on existing research activities,the review focuses on three key aspects including the impact of extreme space environments on forming process and performance,innovative design and manufacturing methods for space structures,and on-orbit recycling and remanufacturing of raw materials.Some experiments that have already been conducted on-orbit and simulated experiments completed on the ground are systematically analyzed to provide a more comprehensive understanding of the constraints and objectives for on-orbit structure manufacturing.Furthermore,several perspectives requiring further research in future are proposed to facilitate the development of new in-space 3D printing technologies and space structures,thereby supporting increasingly advanced space exploration activities.展开更多
Solid propellants are essential energy sources for rockets and other aerospace vehicles,and improvements in their performance have significant implications for the aerospace industry.The application of additive manufa...Solid propellants are essential energy sources for rockets and other aerospace vehicles,and improvements in their performance have significant implications for the aerospace industry.The application of additive manufacturing(AM)in the production of solid propellants promises a substantial leap in the design and fabrication of solid propellant grains.This review summarizes recent research on AM techniques for solid propellant manufacturing,evaluates current applications,and explores development trends.This review highlights that AM technology for solid propellants offers unparalleled advantages in terms of propellant design flexibility and functional gradient loading compared with traditional processes.This study presents a new perspective for the future manufacturing of intelligent and controllable solid propulsion systems.展开更多
Ti at the oxidation states of Ti^(3+)and Ti^(4+),was used to enhance the performance of Na_(3)V_(2)(PO_(4))_(2)F_(2)O by partially substituting vanadium.After doping Ti,the crystallographic volume is decreased due to ...Ti at the oxidation states of Ti^(3+)and Ti^(4+),was used to enhance the performance of Na_(3)V_(2)(PO_(4))_(2)F_(2)O by partially substituting vanadium.After doping Ti,the crystallographic volume is decreased due to the less radii of Ti^(3+/4+),and the valence of Ti is demonstrated identical to V.During sodium insertion in Ti-doped Na_(3)V_(2)(PO_(4))_(2)F_(2)O,the two discharge plateaus split into three because of the rearrangement of local redox environment.Consequently,the optimized Na_(3)V_(0.96)Ti_(0.04)(PO_(4))_(2)F_(2)O shows a specific capacity of 123 and 63 mA·h/g at 0.1C and 20C,respectively.After 350 cycles at 0.5C,the capacity is gradually reduced corresponding to a retention of 71.05%.The significantly improved performance is attributed to the rapid electrochemical kinetics,and showcases the strategy of replacing V^(3+/4+)with Ti^(3+/4+)for high-performance vanadium-based oxyfluorophosphates.展开更多
Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have g...Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.展开更多
Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is p...Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.展开更多
Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the...Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.展开更多
The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-ME...The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-MES）, real-time e-quality tracking （e-QT）, in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices （RFID） data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.展开更多
As an integrated application of modern information technologies and artificial intelligence,Prognostic and Health Management(PHM)is important for machine health monitoring.Prediction of tool wear is one of the symboli...As an integrated application of modern information technologies and artificial intelligence,Prognostic and Health Management(PHM)is important for machine health monitoring.Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry.In this paper,a multi-scale Convolutional Gated Recurrent Unit network(MCGRU)is proposed to address raw sensory data for tool wear prediction.At the bottom of MCGRU,six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network,which augments the adaptability to features of different time scales.These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations.At the top of the MCGRU,a fully connected layer and a regression layer are built for cutting tool wear prediction.Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.展开更多
In this paper,a novel roll-to-roll imprint process is proposed to fabricate gratings in large area. The key challenges in roll-to-roll imprint process,such as the roller mold preparation,imprint system,misalignment of...In this paper,a novel roll-to-roll imprint process is proposed to fabricate gratings in large area. The key challenges in roll-to-roll imprint process,such as the roller mold preparation,imprint system,misalignment of imprint roller and backup roller,and also the imprint pressure,are investigated. Various gratings with different periods and profiles are obtained by the roll-to-roll process. To calibrate the measuring ability of the self-made grating by imprint,a calibration system is built with a dual-frequency laser interferometer. By the calibration,the self-made gratings can achieve ±4μm accuracy in 45mm measuring distance.展开更多
Development of a prototype of a portable optical sensing system is presented for fast detecting of samples’fluorescence spectra.A compact configuration is achieved by integrating a small spectrometer,a microcontrolle...Development of a prototype of a portable optical sensing system is presented for fast detecting of samples’fluorescence spectra.A compact configuration is achieved by integrating a small spectrometer,a microcontroller,a Universal Serial Bus(USB)Host Shield,a network module,and a web server.The fluorescence spectra of a tested sample can be obtained.Then the test data are sent through network communication to our Cloud Server which can store the data for further analyses.With this configuration,test results can be revealed in a short time and downloaded by users to their laptops,tablets or cellphones anytime and anywhere.展开更多
Introduction During the last two decades,organic light-emitting diodes (OLED) have attracted considerable interest owing to their promising applications by replacing cathode ray tubes (CRTs) or liquid crystal displays...Introduction During the last two decades,organic light-emitting diodes (OLED) have attracted considerable interest owing to their promising applications by replacing cathode ray tubes (CRTs) or liquid crystal displays (LCDs).展开更多
This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-pl...This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.展开更多
Ceramic matrix composites(CMCs)structural components encounter the dual challenges of severe mechanical conditions and complex electromagnetic environments due to the increasing demand for stealth technology in aerosp...Ceramic matrix composites(CMCs)structural components encounter the dual challenges of severe mechanical conditions and complex electromagnetic environments due to the increasing demand for stealth technology in aerospace field.To address various functional requirements,this study integrates a biomimetic strategy inspired by gradient bamboo vascular bundles with a novel dual-material 3D printing approach.Three distinct bamboo-inspired structural configurations Cf/SiC composites are designed and manufactured,and the effects of these different structural configurations on the CVI process are analyzed.Nanoindentation method is utilized to characterize the relationship between interface bonding strength and mechanical properties.The results reveal that the maximum flexural strength and fracture toughness reach 108.6±5.2 MPa and 16.45±1.52 MPa m1/2,respectively,attributed to the enhanced crack propagation resistance and path caused by the weak fiber-matrix interface.Furthermore,the bio-inspired configuration enhances the dielectric loss and conductivity loss,exhibiting a minimum reflection loss of−24.3 dB with the effective absorption band of 3.89 GHz.This work introduces an innovative biomimetic strategy and 3D printing method for continuous fiber-reinforced ceramic composites,expanding the application of 3D printing technology in the field of CMCs.展开更多
Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exa...Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.展开更多
Porous designs effectively reduce stress shielding in metallic orthopedic implants.However,current porous structures often fail to adequately meet the needs of patients with osteoporosis and low-modulus body regions.T...Porous designs effectively reduce stress shielding in metallic orthopedic implants.However,current porous structures often fail to adequately meet the needs of patients with osteoporosis and low-modulus body regions.This study proposes a sinusoidal-based lattice structure for an ultralow and widely tunable modulus design,aiming to match diverse bone tissue requirements and enhance biomechanical compatibility.Parametric modeling and finite element analysis were used to evaluate the performance of this structure.Results show that,within the design range suitable for bone growth,the elastic modulus of this lattice structure is tunable over a wide range,from 0.09 to 32.67 GPa,outperforming existing porous structures.The lowest value closely matched the minimum mechanical properties of human cancellous bone among porous structures.Moreover,the structure exhibited distinct anisotropic characteristics,allowing for directional design based on mechanical requirements.The structure’s permeability ranged from 1.19×10^(-8) m^(2) to 2.3×10^(-7) m^(2),making it highly compatible with human cancellous bone and meeting the requirements of orthopedic implants.Samples with porosities ranging from 46% to 87% were successfully fabricated using powder bed fusion additive manufacturing,validating the simulation predictions.This tunable low-modulus lattice structure provides a novel approach for developing personalized orthopedic implants,particularly for patients with specialized needs such as osteoporosis,and can potentially enhance biomechanical compatibility and long-term stability.展开更多
基金National Natural Science Foundation of China (52075420)Fundamental Research Funds for the Central Universities (xzy022023049)National Key Research and Development Program of China (2023YFB3408600)。
文摘The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ensemble methods for battery SOH estimation. The convergence of advanced machine learning with ensemble learning is anticipated to yield valuable avenues for research. Accelerated research in ensemble learning holds promising prospects for achieving more accurate and reliable battery SOH estimation under real-world conditions.
基金supported in part by the Fundamental Research Funds for the Central Universities(3102017OQD110)the Natural Science Basic Research Plan in Shaanxi Province of China(2019JQ-435)+3 种基金the Project Funded by China Postdoctoral Science Foundation(2019M663818)the National Key Research and Development Program of China(2019YFB1703800)Guangdong Basic and Applied Basic Research Foundation(2019A1515111076)the National Natural Science Foundation of China(71931007)。
文摘This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker's algorithm(MBA) to ensure that all resources required by these jobs can be freed. Moreover,a Petri net based deadlock avoidance policy(DAP) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.
基金the State Key Laboratory for Manufacturing System Engineering at Xi'an Jiaotong University. China.
文摘Deadlock avoidance problems are investigated for automated manufacturing systems with flexible routings. Based on the Petri net models of the systems, this paper proposes, for the first time, the concept of perfect maximal resourcetransition circuits and their saturated states. The concept facilitates the development of system liveness characterization and deadlock avoidance Petri net supervisors. Deadlock is characterized as some perfect maximal resource-transition circuits reaching their saturated states. For a large class of manufacturing systems, which do not contain center resources, the optimal deadlock avoidance Petri net supervisors are presented. For a general manufacturing system, a method is proposed for reducing the system Petri net model so that the reduced model does not contain center resources and, hence, has optimal deadlock avoidance Petri net supervisor. The controlled reduced Petri net model can then be used as the liveness supervisor of the system.
基金Supported by National Natural Science Foundation of China(Grant Nos.71571142,51275396)
文摘Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors （S2ensors） to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems （SMS）. The concept, classification, operational logics, and for- malization of S2ensors are clarified. S2ensors collect sub- jective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2en- sors-Cloud platform is discussed to integrate different S2- ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors- Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.
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.
基金supported by National Natural Science Foundation of China(Grant No.52205413)National Key Research and Development Program(Grant No.2022YFB3806101)+1 种基金K C Wong Education FoundationThe Youth Innovation Team of Shaanxi Universities。
文摘In-space 3D printing is transforming the manufacturing paradigm of space structures from ground-based production to in-situ space manufacturing,effectively addressing the challenges of high costs,long response times,and structural size limitations associated with traditional rocket launches.This technology enables rapid on-orbit emergency repairs and significantly expands the geometric dimensions of space structures.High-performance polymers and their composites are widely used in in-space 3D printing,yet their implementation faces complex challenges posed by extreme space environmental conditions and limited energy or resources.This paper reviews the state-of-the-art in 3D printing of polymer and composites for on-orbit structure manufacturing.Based on existing research activities,the review focuses on three key aspects including the impact of extreme space environments on forming process and performance,innovative design and manufacturing methods for space structures,and on-orbit recycling and remanufacturing of raw materials.Some experiments that have already been conducted on-orbit and simulated experiments completed on the ground are systematically analyzed to provide a more comprehensive understanding of the constraints and objectives for on-orbit structure manufacturing.Furthermore,several perspectives requiring further research in future are proposed to facilitate the development of new in-space 3D printing technologies and space structures,thereby supporting increasingly advanced space exploration activities.
基金supported by National Key Research and Development Program of China(Grant.No.2022YFB4603102)Insight Action(Grant.No.AA5F41D0).
文摘Solid propellants are essential energy sources for rockets and other aerospace vehicles,and improvements in their performance have significant implications for the aerospace industry.The application of additive manufacturing(AM)in the production of solid propellants promises a substantial leap in the design and fabrication of solid propellant grains.This review summarizes recent research on AM techniques for solid propellant manufacturing,evaluates current applications,and explores development trends.This review highlights that AM technology for solid propellants offers unparalleled advantages in terms of propellant design flexibility and functional gradient loading compared with traditional processes.This study presents a new perspective for the future manufacturing of intelligent and controllable solid propulsion systems.
文摘Ti at the oxidation states of Ti^(3+)and Ti^(4+),was used to enhance the performance of Na_(3)V_(2)(PO_(4))_(2)F_(2)O by partially substituting vanadium.After doping Ti,the crystallographic volume is decreased due to the less radii of Ti^(3+/4+),and the valence of Ti is demonstrated identical to V.During sodium insertion in Ti-doped Na_(3)V_(2)(PO_(4))_(2)F_(2)O,the two discharge plateaus split into three because of the rearrangement of local redox environment.Consequently,the optimized Na_(3)V_(0.96)Ti_(0.04)(PO_(4))_(2)F_(2)O shows a specific capacity of 123 and 63 mA·h/g at 0.1C and 20C,respectively.After 350 cycles at 0.5C,the capacity is gradually reduced corresponding to a retention of 71.05%.The significantly improved performance is attributed to the rapid electrochemical kinetics,and showcases the strategy of replacing V^(3+/4+)with Ti^(3+/4+)for high-performance vanadium-based oxyfluorophosphates.
基金supported by National Natural Science Foundation of China(Grant Nos.52025055,52375576,52350349)Key Research and Development Program of Shaanxi(Program No.2022GXLH-01-12)+2 种基金Joint Fund of Ministry of Education for Equipment Pre-research(No.8091B03012304)Aeronautical Science Foundation of China(No.2022004607001)the Fundamental Research Funds for the Central Universities(No.xtr072024031).
文摘Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.
基金supported by National Natural Science Foundation of China(No.52025055 and 52275571)Basic Research Operation Fund of China(No.xzy012024024).
文摘Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z2443)State Key Laboratory for Man ufacturing Systems Engineering of Xi’an Jiaotong University of China
文摘Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.
基金supported by Natinoal Basic Research Program of China (973 Program, Grant No. 2011CB706805)National Natural Science Foundation of China (Grant No. 50875204)
文摘The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-MES）, real-time e-quality tracking （e-QT）, in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices （RFID） data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.
基金Supported in part by Natural Science Foundation of China(Grant Nos.51835009,51705398)Shaanxi Province 2020 Natural Science Basic Research Plan(Grant No.2020JQ-042)Aeronautical Science Foundation(Grant No.2019ZB070001).
文摘As an integrated application of modern information technologies and artificial intelligence,Prognostic and Health Management(PHM)is important for machine health monitoring.Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry.In this paper,a multi-scale Convolutional Gated Recurrent Unit network(MCGRU)is proposed to address raw sensory data for tool wear prediction.At the bottom of MCGRU,six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network,which augments the adaptability to features of different time scales.These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations.At the top of the MCGRU,a fully connected layer and a regression layer are built for cutting tool wear prediction.Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.
基金The Major Special Projects of Ministry of Science and Technology of China(No.2011ZX04014-071)National Natural Science Foundation of China(No.51275400)
文摘In this paper,a novel roll-to-roll imprint process is proposed to fabricate gratings in large area. The key challenges in roll-to-roll imprint process,such as the roller mold preparation,imprint system,misalignment of imprint roller and backup roller,and also the imprint pressure,are investigated. Various gratings with different periods and profiles are obtained by the roll-to-roll process. To calibrate the measuring ability of the self-made grating by imprint,a calibration system is built with a dual-frequency laser interferometer. By the calibration,the self-made gratings can achieve ±4μm accuracy in 45mm measuring distance.
基金supported by the National Key Development Program (2016YFB1102704)Natural Science Foundation of Liaoning Province (2015020115)+1 种基金National Natural Science Foundation of China (U1609209)National Science Fund for Distinguished Youth Scholars (51625504)
文摘Development of a prototype of a portable optical sensing system is presented for fast detecting of samples’fluorescence spectra.A compact configuration is achieved by integrating a small spectrometer,a microcontroller,a Universal Serial Bus(USB)Host Shield,a network module,and a web server.The fluorescence spectra of a tested sample can be obtained.Then the test data are sent through network communication to our Cloud Server which can store the data for further analyses.With this configuration,test results can be revealed in a short time and downloaded by users to their laptops,tablets or cellphones anytime and anywhere.
基金This work was supported by the National Science Support Program （2006BAE04B05-3）MOE Program for Changjiang Scholars and Innovative Research Team （grant No. 0629）+2 种基金National Science Foundation of China （grant No. 50505037）863 Hi-Teeh Program （grant No. 2006AA04Z322 ）＂Qing Lan＂ Talent Engineering Funds by Lanzhou Jiaotong University.
文摘Introduction During the last two decades,organic light-emitting diodes (OLED) have attracted considerable interest owing to their promising applications by replacing cathode ray tubes (CRTs) or liquid crystal displays (LCDs).
基金National Natural Science Foundation of China(No.50875204)National Basic Research "973" Project(No.2011CB706805)
文摘This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.
基金supported by The National Key Research and Development Program of China(No.2019YFB1901001).
文摘Ceramic matrix composites(CMCs)structural components encounter the dual challenges of severe mechanical conditions and complex electromagnetic environments due to the increasing demand for stealth technology in aerospace field.To address various functional requirements,this study integrates a biomimetic strategy inspired by gradient bamboo vascular bundles with a novel dual-material 3D printing approach.Three distinct bamboo-inspired structural configurations Cf/SiC composites are designed and manufactured,and the effects of these different structural configurations on the CVI process are analyzed.Nanoindentation method is utilized to characterize the relationship between interface bonding strength and mechanical properties.The results reveal that the maximum flexural strength and fracture toughness reach 108.6±5.2 MPa and 16.45±1.52 MPa m1/2,respectively,attributed to the enhanced crack propagation resistance and path caused by the weak fiber-matrix interface.Furthermore,the bio-inspired configuration enhances the dielectric loss and conductivity loss,exhibiting a minimum reflection loss of−24.3 dB with the effective absorption band of 3.89 GHz.This work introduces an innovative biomimetic strategy and 3D printing method for continuous fiber-reinforced ceramic composites,expanding the application of 3D printing technology in the field of CMCs.
基金supported by National Key Research and Development Program of China(Grant No.2023YFB4604100)National Key Research and Development Program of China(Grant No.2022YFB3806104)+4 种基金Key Research and Development Program in Shaanxi Province(Grant No.2021LLRH-08-17)Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001)K C Wong Education Foundation of ChinaYouth Innovation Team of Shaanxi Universities of ChinaKey Research and Development Program of Shaanxi Province(Grant 2021LLRH-08-3.1).
文摘Ensuring the consistent mechanical performance of three-dimensional(3D)-printed continuous fiber-reinforced composites is a significant challenge in additive manufacturing.The current reliance on manual monitoring exacerbates this challenge by rendering the process vulnerable to environmental changes and unexpected factors,resulting in defects and inconsistent product quality,particularly in unmanned long-term operations or printing in extreme environments.To address these issues,we developed a process monitoring and closed-loop feedback control strategy for the 3D printing process.Real-time printing image data were captured and analyzed using a well-trained neural network model,and a real-time control module-enabled closed-loop feedback control of the flow rate was developed.The neural network model,which was based on image processing and artificial intelligence,enabled the recognition of flow rate values with an accuracy of 94.70%.The experimental results showed significant improvements in both the surface performance and mechanical properties of printed composites,with three to six times improvement in tensile strength and elastic modulus,demonstrating the effectiveness of the strategy.This study provides a generalized process monitoring and feedback control method for the 3D printing of continuous fiber-reinforced composites,and offers a potential solution for remote online monitoring and closed-loop adjustment in unmanned or extreme space environments.
基金supported by National Key R&D Program of China(Grant No.2022YFB4600500)Fundamental Research Funds for the Central Universities,and the Program for Innovation Team of Shaanxi Province(Grant No.2023-CX-TD-17).
文摘Porous designs effectively reduce stress shielding in metallic orthopedic implants.However,current porous structures often fail to adequately meet the needs of patients with osteoporosis and low-modulus body regions.This study proposes a sinusoidal-based lattice structure for an ultralow and widely tunable modulus design,aiming to match diverse bone tissue requirements and enhance biomechanical compatibility.Parametric modeling and finite element analysis were used to evaluate the performance of this structure.Results show that,within the design range suitable for bone growth,the elastic modulus of this lattice structure is tunable over a wide range,from 0.09 to 32.67 GPa,outperforming existing porous structures.The lowest value closely matched the minimum mechanical properties of human cancellous bone among porous structures.Moreover,the structure exhibited distinct anisotropic characteristics,allowing for directional design based on mechanical requirements.The structure’s permeability ranged from 1.19×10^(-8) m^(2) to 2.3×10^(-7) m^(2),making it highly compatible with human cancellous bone and meeting the requirements of orthopedic implants.Samples with porosities ranging from 46% to 87% were successfully fabricated using powder bed fusion additive manufacturing,validating the simulation predictions.This tunable low-modulus lattice structure provides a novel approach for developing personalized orthopedic implants,particularly for patients with specialized needs such as osteoporosis,and can potentially enhance biomechanical compatibility and long-term stability.
