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
一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家...一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。展开更多
The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficien...The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.展开更多
To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and l...To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.展开更多
Effective vegetation reconstruction plays a vital role in the restoration of desert ecosystems.However,in reconstruction of different vegetation types,the community characteristics,assembly processes,and functions of ...Effective vegetation reconstruction plays a vital role in the restoration of desert ecosystems.However,in reconstruction of different vegetation types,the community characteristics,assembly processes,and functions of different soil microbial taxa under environmental changes are still disputed,which limits the understanding of the sustainability of desert restoration.Hence,we investigated the soil microbial community characteristics and functional attributes of grassland desert(GD),desert steppe(DS),typical steppe(TS),and artificial forest(AF)in the Mu Us Desert,China.Our findings confirmed the geographical conservation of soil microbial composition but highlighted decreased microbial diversity in TS.Meanwhile,the abundance of rare taxa and microbial community stability in TS improved.Heterogeneous and homogeneous selection determined the assembly of rare and abundant bacterial taxa,respectively,with both being significantly influenced by soil moisture.In contrast,fungal communities displayed stochastic processes and exhibited sensitivity to soil nutrient conditions.Furthermore,our investigation revealed a noteworthy augmentation in bacterial metabolic functionality in TS,aligning with improved vegetation restoration and the assemblage of abundant bacterial taxa.However,within nutrient-limited soils(GD,DS,and AF),the assembly dynamics of rare fungal taxa assumed a prominent role in augmenting their metabolic capacity and adaptability to desert ecosystems.These results highlighted the variations in the assembly processes and metabolic functions of soil microorganisms during vegetation reestablishment and provided corresponding theoretical support for anthropogenic revegetation of desert ecosystems.展开更多
1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex...1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].展开更多
Nondestructive testing(NDT)methods such as visual inspection and ultrasonic testing are widely applied in manufacturing quality control,but they remain limited in their ability to detect defect characteristics.Visual ...Nondestructive testing(NDT)methods such as visual inspection and ultrasonic testing are widely applied in manufacturing quality control,but they remain limited in their ability to detect defect characteristics.Visual inspection depends strongly on operator experience,while ultrasonic testing requires physical contact and stable coupling conditions that are difficult to maintain in production lines.These constraints become more pronounced when defect-related information is scarce or when background noise interferes with signal acquisition in manufacturing processes.This study presents a non-contact acoustic method for diagnosing defects in scroll compressors during the manufacturing process.The diagnostic approach leverages Mel-frequency cepstral coefficients(MFCC),and shorttime Fourier transform(STFT)parameters to capture the rotational frequency and harmonic characteristics of the scroll compressor.These parameters enable the extraction of defect-related features even in the presence of background noise.A convolutional neural network(CNN)model was constructed using MFCCs and spectrograms as image inputs.The proposed method was validated using acoustic data collected from compressors operated at a fixed rotational speed under real manufacturing process.The method identified normal operation and three defect types.These results demonstrate the applicability of this method in noise-prone manufacturing environments and suggest its potential for improving product quality,manufacturing reliability and productivity.展开更多
To achieve sustainable development goals and the requirements of a circular economy,a new class of intelligent computer-aided methods and tools is needed.Artificial intelligence(AI)techniques have been gaining much at...To achieve sustainable development goals and the requirements of a circular economy,a new class of intelligent computer-aided methods and tools is needed.Artificial intelligence(AI)techniques have been gaining much attention due to their ability to provide options to tackle the challenges we are currently facing.However,the successful application of AI to solve problems of current interest requires AI to be integrated with associated process systems engineering methods and tools that are already available or being developed.In this perspective paper,we highlight the use of a collection of process systems engineering methods and tools augmented by AI techniques to solve problems related to process manufacturing,with a focus on chemical product design,process synthesis and design,process control,and process safety and hazards.展开更多
A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are ...A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.展开更多
The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product l...The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product lifecycle,the problem of high energy usage is increasingly notable.Nevertheless,current analyses of carbon emissions in textile manufacturing emphasize the dynamic temporal characteristics while failing to adequately consider critical information such as material flows and energy consumption.A carbon emission analysis method based on a holographic process model(HPM)is proposed to address these issues.First,the system boundary in the textile manufacturing is defined,and the characteristics of carbon emissions are analyzed.Next,an HPM based on the object-centric Petri net(OCPN)is constructed,and simulation experiments are conducted on three different scenarios in the textile manufacturing.Subsequently,the constructed HPM is utilized to achieve a multi-perspective analysis of carbon emissions.Finally,the feasibility of the method is verified by using the production data of pure cotton products from a certain textile manufacturing enterprise.The results indicate that this method can analyze the impact of various factors on the carbon emissions of pure cotton product production,and by applying targeted optimization strategies,carbon emissions have been reduced by nearly 20%.This contributes to propelling the textile manufacturing industry toward sustainable development.展开更多
Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nic...Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nickel-based superalloys,pivotal materials for high-temperature bearing components in aeroengines,present significant challenges in the fabrication of complex parts due to their great hardness.Huge attention and rapid progress have been garnered in AM processing of nicklebased superalloys,largely owing to its distinct benefits in the freedom of fabrication and reduced manufacturing lifecycle.Despite extensive research into AM in nickel-based superalloys,the corresponding results and conclusions are scattered attributed to the variety of nickel-based superalloys and complex AM processing parameters.Therefore,there is still a pressing need for a comprehensive and deep understanding of the relationship between the AM processing and microstructures and mechanical performance of nickel-based superalloys.This review introduces the processing characteristics of four primary AM technologies utilized for superalloys and summarizes the microstructures and mechanical properties prior to and post-heat treatments.Additionally,this review presents innovative superalloys specifically accommodated to AM processing and offers insights into the material development and performance improvement,aiming to provide a valuable assessment on AM processing of nickel-based superalloys and an effective guidance for the future research.展开更多
Electronic 3D printing possesses a remarkable molding ability and convenience in integrated circuits,flexible wearables,and individual automobile requirements.However,traditional 3D printing technology still struggles...Electronic 3D printing possesses a remarkable molding ability and convenience in integrated circuits,flexible wearables,and individual automobile requirements.However,traditional 3D printing technology still struggles to meet the demands of high precision and high efficiency in the process of fabricating a curved surface circuit,particularly achieving precise silver circuit molding on irregular substrates.Here,a high-precision and muti-scaled conformal manufacturing method for silver circuits is presented through the digital light processing(DLP)of ultraviolet-curable silver paste(UV-SP)with adjustable photocuring properties,enabling the successful preparation of micro-scaled conductive structure on the sharply skewed hook face.The minimum modeling depth and width of the cured silver paste can be well controlled to 10 and 88µm,respectively.Compared with traditional printing technology,the printing efficiency of complex patterns has increased by over 70%.The printed silver circuit demonstrates an exceptionally high electrical conductivity,reaching as high as 1.16×10^(7) S/m.Additionally,the UV-SP exhibits significant manufacturing efficiency and superior molding resolution compared to conventional direct ink writing and inkjet printing techniques,thereby contributing to the attainment of high precision and efficiency of conformal and micro-molding manufacturing in sensors,communication antennas,and other electronic devices based on curved substrates.展开更多
With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking f...With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking furnace in ethylene manufacturing determines not only the profitability of an ethylene plant but also the carbon emissions it releases.While multi-objective optimization of the thermal cracking furnace to balance profit with environmental impact is an effective solution to achieve green ethylene man-ufacturing,it carries a high computational demand due to the complex dynamic processes involved.In this work,artificial intelligence(AI)is applied to develop a novel hybrid model based on physically consistent machine learning(PCML).This hybrid model not only reduces the computational demand but also retains the interpretability and scalability of the model.With this hybrid model,the computational demand of the multi-objective dynamic optimization is reduced to 77 s.The optimization results show that dynamically adjusting the operating variables with coke formation can effectively improve profit and reduce CO_(2)emissions.In addition,the results from this study indicate that sacrificing 28.97%of the annual profit can significantly reduce the annual CO_(2)emissions by 42.89%.The key findings of this study highlight the great potential for green ethylene manufacturing based on AI through modeling and optimization approaches.This study will be important for industrial practitioners and policy-makers.展开更多
Process manufacturing is going through a critical transformation in response to escalating demands for efficiency,sustainability,and intelligent innovation.With process manufacturing being characterized by complex wor...Process manufacturing is going through a critical transformation in response to escalating demands for efficiency,sustainability,and intelligent innovation.With process manufacturing being characterized by complex workflows and high resource consumption,the process manufacturing industry is under mounting pressure to optimize resource utilization,enhance intelligent design,reduce carbon emissions,and address emerging challenges in quality assurance,safety,and information integration.展开更多
This paper investigates the economic and operational trade-offs between continuous manufacturing and batch processing in the context of biopharmaceutical engineering design,through the lens of project management.The s...This paper investigates the economic and operational trade-offs between continuous manufacturing and batch processing in the context of biopharmaceutical engineering design,through the lens of project management.The study explores the fundamental principles of both manufacturing modes,assesses their implications on capital and operational expenditures,and evaluates their performance against key project management metrics such as cost,time,quality,and risk.Drawing on current regulatory guidance,industrial practices,and technological advances,the paper concludes that while continuous manufacturing offers significant benefits in process efficiency and quality control,its implementation requires substantial upfront investment,risk management,and stakeholder alignment.The study aims to support informed decision-making in early-stage biopharmaceutical facility and process design.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite a...Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.展开更多
In mass spectrometry, fragments with a mass higher than the original molecular ion provide valuable insights into the molecular structure and can guide the assembly and disassembly processes for chemical synthesis. He...In mass spectrometry, fragments with a mass higher than the original molecular ion provide valuable insights into the molecular structure and can guide the assembly and disassembly processes for chemical synthesis. Here, we report such an example and following up by modifying the solvothermal reaction conditions (temperature and time) it is possible to isolate the high mass species in crystalline form. [Zn_(4)L_(4)Cl_(4)] (Zn_(4)L_(4), L = N-methylbenzimidazole-2-methanolate) has a boat-like Zn_(4)O_(4) core but electrospray ionization mass spectrometry (ESI-MS) of the solution of its crystals shows higher mass peaks of Zn_(5)L_(5), Zn_(5)L_(6) and Zn_(6)L_(6) species. Thus, both disassembly and reassembly are highly probable processes. Consequently, [Zn(HL)_(2)Cl_(2)] (Zn1, L = N-methylbenzimidazole-2-methanolate), [Zn_(4)L_(6)Cl_(2)] (Zn_(4)L_(6), L = N-methylbenzimidazole-2-methanolate) and [Zn_(6)L_(6)Cl_(4)(CH_(3)O)_(2)] (Zn_(6)L_(6), L = N-methylbenzimidazole-2-methanolate) were prepared. The results of multistage ESI-MS of their dissolved crystals led to a proposed mechanism of their formation in the gas phase as follows: [Zn_(3)L_(4)] through [ZnL] → [ZnL(HL)] → [Zn(HL)_(2)] → [Zn_(2)L] → [Zn_(2)L_(2)] → [Zn_(2)L_(3)]. The mechanism was derived in conjunction with Gibbs free energies calculated using DFT of the fragments observed in the ESI-MS of Zn_(4)L_(4), Zn_(4)L_(6) and Zn_(6)L_(6). This work reveals the complex of chemical reactions, involving fragmentation and unexpected combination, under mass spectrometry condition which allows one to synthesize the observed transients, leading to mechanism of formation by correlation of solid-state/solution structural information.展开更多
Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental con...Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.展开更多
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
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.
文摘一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。
基金the National Natural Science Foundation of China(No.52275378)the National Key Laboratory for Precision Hot Processing of Metals(6142909200208)。
文摘The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.
基金Shaanxi Province Qin Chuangyuan“Scientist+Engineer”Team Construction Project(2022KXJ-071)2022 Qin Chuangyuan Achievement Transformation Incubation Capacity Improvement Project(2022JH-ZHFHTS-0012)+1 种基金Shaanxi Province Key Research and Development Plan-“Two Chains”Integration Key Project-Qin Chuangyuan General Window Industrial Cluster Project(2023QCY-LL-02)Xixian New Area Science and Technology Plan(2022-YXYJ-003,2022-XXCY-010)。
文摘To overcome the shortage of complex equipment,large volume,and high energy consumption in space capsule manufacturing,a novel sliding pressure Joule heat fuse additive manufacturing technique with reduced volume and low energy consumption was proposed.But the unreasonable process parameters may lead to the inferior consistency of the forming quality of single-channel multilayer in Joule heat additive manufacturing process,and it is difficult to reach the condition for forming thinwalled parts.Orthogonal experiments were designed to fabricate single-channel multilayer samples with varying numbers of layers,and their forming quality was evaluated.The influence of printing current,forming speed,and contact pressure on the forming quality of the single-channel multilayer was analyzed.The optimal process parameters were obtained and the quality characterization of the experiment results was conducted.Results show that the printing current has the most significant influence on the forming quality of the single-channel multilayer.Under the optimal process parameters,the forming section is well fused and the surface is continuously smooth.The surface roughness of a single-channel 3-layer sample is 0.16μm,and the average Vickers hardness of cross section fusion zone is 317 HV,which lays a foundation for the subsequent use of Joule heat additive manufacturing technique to form thinwall parts.
基金supported by the National Natural Science Foundation of China(No.42007428)the National Forage Industry Technology System Program of China(No.CARS34)+1 种基金the Key Research and Development Program of Shaanxi,China(No.2022SF-285)Shaanxi Province Forestry Science and Technology Innovation Program,China(No.SXLK2022-02-14)。
文摘Effective vegetation reconstruction plays a vital role in the restoration of desert ecosystems.However,in reconstruction of different vegetation types,the community characteristics,assembly processes,and functions of different soil microbial taxa under environmental changes are still disputed,which limits the understanding of the sustainability of desert restoration.Hence,we investigated the soil microbial community characteristics and functional attributes of grassland desert(GD),desert steppe(DS),typical steppe(TS),and artificial forest(AF)in the Mu Us Desert,China.Our findings confirmed the geographical conservation of soil microbial composition but highlighted decreased microbial diversity in TS.Meanwhile,the abundance of rare taxa and microbial community stability in TS improved.Heterogeneous and homogeneous selection determined the assembly of rare and abundant bacterial taxa,respectively,with both being significantly influenced by soil moisture.In contrast,fungal communities displayed stochastic processes and exhibited sensitivity to soil nutrient conditions.Furthermore,our investigation revealed a noteworthy augmentation in bacterial metabolic functionality in TS,aligning with improved vegetation restoration and the assemblage of abundant bacterial taxa.However,within nutrient-limited soils(GD,DS,and AF),the assembly dynamics of rare fungal taxa assumed a prominent role in augmenting their metabolic capacity and adaptability to desert ecosystems.These results highlighted the variations in the assembly processes and metabolic functions of soil microorganisms during vegetation reestablishment and provided corresponding theoretical support for anthropogenic revegetation of desert ecosystems.
基金the National Natural Science Foundation of China(NSFC)(62103283)the Australia Research Council’s Discovery Pro-jects Scheme(DP220100355).
文摘1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].
基金supported in part by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(RS-2023-00239657)in part by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.RS-2024-00423772)。
文摘Nondestructive testing(NDT)methods such as visual inspection and ultrasonic testing are widely applied in manufacturing quality control,but they remain limited in their ability to detect defect characteristics.Visual inspection depends strongly on operator experience,while ultrasonic testing requires physical contact and stable coupling conditions that are difficult to maintain in production lines.These constraints become more pronounced when defect-related information is scarce or when background noise interferes with signal acquisition in manufacturing processes.This study presents a non-contact acoustic method for diagnosing defects in scroll compressors during the manufacturing process.The diagnostic approach leverages Mel-frequency cepstral coefficients(MFCC),and shorttime Fourier transform(STFT)parameters to capture the rotational frequency and harmonic characteristics of the scroll compressor.These parameters enable the extraction of defect-related features even in the presence of background noise.A convolutional neural network(CNN)model was constructed using MFCCs and spectrograms as image inputs.The proposed method was validated using acoustic data collected from compressors operated at a fixed rotational speed under real manufacturing process.The method identified normal operation and three defect types.These results demonstrate the applicability of this method in noise-prone manufacturing environments and suggest its potential for improving product quality,manufacturing reliability and productivity.
基金funding support from the National Natural Science Foundation of China(62394343)the Program of Introducing Talents of Discipline to Universities(the 111 Project)(B17017).
文摘To achieve sustainable development goals and the requirements of a circular economy,a new class of intelligent computer-aided methods and tools is needed.Artificial intelligence(AI)techniques have been gaining much attention due to their ability to provide options to tackle the challenges we are currently facing.However,the successful application of AI to solve problems of current interest requires AI to be integrated with associated process systems engineering methods and tools that are already available or being developed.In this perspective paper,we highlight the use of a collection of process systems engineering methods and tools augmented by AI techniques to solve problems related to process manufacturing,with a focus on chemical product design,process synthesis and design,process control,and process safety and hazards.
基金The National Natural Science Foundation of China(No.52305381)the Natural Science Foundation of Jiangsu Province(No.BK20210351)the Fundamental Research Funds for the Central Universities(No.30923011008).
文摘A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.
基金National Key R&D Program of China(No.2019YFB1706300)。
文摘The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product lifecycle,the problem of high energy usage is increasingly notable.Nevertheless,current analyses of carbon emissions in textile manufacturing emphasize the dynamic temporal characteristics while failing to adequately consider critical information such as material flows and energy consumption.A carbon emission analysis method based on a holographic process model(HPM)is proposed to address these issues.First,the system boundary in the textile manufacturing is defined,and the characteristics of carbon emissions are analyzed.Next,an HPM based on the object-centric Petri net(OCPN)is constructed,and simulation experiments are conducted on three different scenarios in the textile manufacturing.Subsequently,the constructed HPM is utilized to achieve a multi-perspective analysis of carbon emissions.Finally,the feasibility of the method is verified by using the production data of pure cotton products from a certain textile manufacturing enterprise.The results indicate that this method can analyze the impact of various factors on the carbon emissions of pure cotton product production,and by applying targeted optimization strategies,carbon emissions have been reduced by nearly 20%.This contributes to propelling the textile manufacturing industry toward sustainable development.
基金financially supported by the National Key R&D Program of China(No.2021YFB3702301)the National Natural Science Foundation of China(No.52101068]+2 种基金the China Postdoctoral Science Foundation[No.2022T150342]the Postdoctoral International Exchange Program[No.YJ20210129]the Shuimu Tsinghua Scholar Program(No.2020SM100)
文摘Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nickel-based superalloys,pivotal materials for high-temperature bearing components in aeroengines,present significant challenges in the fabrication of complex parts due to their great hardness.Huge attention and rapid progress have been garnered in AM processing of nicklebased superalloys,largely owing to its distinct benefits in the freedom of fabrication and reduced manufacturing lifecycle.Despite extensive research into AM in nickel-based superalloys,the corresponding results and conclusions are scattered attributed to the variety of nickel-based superalloys and complex AM processing parameters.Therefore,there is still a pressing need for a comprehensive and deep understanding of the relationship between the AM processing and microstructures and mechanical performance of nickel-based superalloys.This review introduces the processing characteristics of four primary AM technologies utilized for superalloys and summarizes the microstructures and mechanical properties prior to and post-heat treatments.Additionally,this review presents innovative superalloys specifically accommodated to AM processing and offers insights into the material development and performance improvement,aiming to provide a valuable assessment on AM processing of nickel-based superalloys and an effective guidance for the future research.
基金supported by the National Natural Science Foundation of China(Nos.51972079 and 52302062)the National Key Research and Development Program of China(Nos.2022YFB370630202 and 2022YFB3706305).
文摘Electronic 3D printing possesses a remarkable molding ability and convenience in integrated circuits,flexible wearables,and individual automobile requirements.However,traditional 3D printing technology still struggles to meet the demands of high precision and high efficiency in the process of fabricating a curved surface circuit,particularly achieving precise silver circuit molding on irregular substrates.Here,a high-precision and muti-scaled conformal manufacturing method for silver circuits is presented through the digital light processing(DLP)of ultraviolet-curable silver paste(UV-SP)with adjustable photocuring properties,enabling the successful preparation of micro-scaled conductive structure on the sharply skewed hook face.The minimum modeling depth and width of the cured silver paste can be well controlled to 10 and 88µm,respectively.Compared with traditional printing technology,the printing efficiency of complex patterns has increased by over 70%.The printed silver circuit demonstrates an exceptionally high electrical conductivity,reaching as high as 1.16×10^(7) S/m.Additionally,the UV-SP exhibits significant manufacturing efficiency and superior molding resolution compared to conventional direct ink writing and inkjet printing techniques,thereby contributing to the attainment of high precision and efficiency of conformal and micro-molding manufacturing in sensors,communication antennas,and other electronic devices based on curved substrates.
基金the financial support of the National Key Research and Development Program of China(2021YFE0112800)EU RISE project OPTIMAL(101007963).
文摘With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking furnace in ethylene manufacturing determines not only the profitability of an ethylene plant but also the carbon emissions it releases.While multi-objective optimization of the thermal cracking furnace to balance profit with environmental impact is an effective solution to achieve green ethylene man-ufacturing,it carries a high computational demand due to the complex dynamic processes involved.In this work,artificial intelligence(AI)is applied to develop a novel hybrid model based on physically consistent machine learning(PCML).This hybrid model not only reduces the computational demand but also retains the interpretability and scalability of the model.With this hybrid model,the computational demand of the multi-objective dynamic optimization is reduced to 77 s.The optimization results show that dynamically adjusting the operating variables with coke formation can effectively improve profit and reduce CO_(2)emissions.In addition,the results from this study indicate that sacrificing 28.97%of the annual profit can significantly reduce the annual CO_(2)emissions by 42.89%.The key findings of this study highlight the great potential for green ethylene manufacturing based on AI through modeling and optimization approaches.This study will be important for industrial practitioners and policy-makers.
文摘Process manufacturing is going through a critical transformation in response to escalating demands for efficiency,sustainability,and intelligent innovation.With process manufacturing being characterized by complex workflows and high resource consumption,the process manufacturing industry is under mounting pressure to optimize resource utilization,enhance intelligent design,reduce carbon emissions,and address emerging challenges in quality assurance,safety,and information integration.
文摘This paper investigates the economic and operational trade-offs between continuous manufacturing and batch processing in the context of biopharmaceutical engineering design,through the lens of project management.The study explores the fundamental principles of both manufacturing modes,assesses their implications on capital and operational expenditures,and evaluates their performance against key project management metrics such as cost,time,quality,and risk.Drawing on current regulatory guidance,industrial practices,and technological advances,the paper concludes that while continuous manufacturing offers significant benefits in process efficiency and quality control,its implementation requires substantial upfront investment,risk management,and stakeholder alignment.The study aims to support informed decision-making in early-stage biopharmaceutical facility and process design.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
基金Supported by National Key Research and Development Program(Grant No.2024YFB3312700)National Natural Science Foundation of China(Grant No.52405541)the Changzhou Municipal Sci&Tech Program(Grant No.CJ20241131)。
文摘Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.
基金supported by the BAGUI Talent Program in Guangxi Province(No.2019AC26001),and the National Natural Science Foundation of China(No.22171075,U23A2080).
文摘In mass spectrometry, fragments with a mass higher than the original molecular ion provide valuable insights into the molecular structure and can guide the assembly and disassembly processes for chemical synthesis. Here, we report such an example and following up by modifying the solvothermal reaction conditions (temperature and time) it is possible to isolate the high mass species in crystalline form. [Zn_(4)L_(4)Cl_(4)] (Zn_(4)L_(4), L = N-methylbenzimidazole-2-methanolate) has a boat-like Zn_(4)O_(4) core but electrospray ionization mass spectrometry (ESI-MS) of the solution of its crystals shows higher mass peaks of Zn_(5)L_(5), Zn_(5)L_(6) and Zn_(6)L_(6) species. Thus, both disassembly and reassembly are highly probable processes. Consequently, [Zn(HL)_(2)Cl_(2)] (Zn1, L = N-methylbenzimidazole-2-methanolate), [Zn_(4)L_(6)Cl_(2)] (Zn_(4)L_(6), L = N-methylbenzimidazole-2-methanolate) and [Zn_(6)L_(6)Cl_(4)(CH_(3)O)_(2)] (Zn_(6)L_(6), L = N-methylbenzimidazole-2-methanolate) were prepared. The results of multistage ESI-MS of their dissolved crystals led to a proposed mechanism of their formation in the gas phase as follows: [Zn_(3)L_(4)] through [ZnL] → [ZnL(HL)] → [Zn(HL)_(2)] → [Zn_(2)L] → [Zn_(2)L_(2)] → [Zn_(2)L_(3)]. The mechanism was derived in conjunction with Gibbs free energies calculated using DFT of the fragments observed in the ESI-MS of Zn_(4)L_(4), Zn_(4)L_(6) and Zn_(6)L_(6). This work reveals the complex of chemical reactions, involving fragmentation and unexpected combination, under mass spectrometry condition which allows one to synthesize the observed transients, leading to mechanism of formation by correlation of solid-state/solution structural information.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
文摘The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
