As the coronavirus pandemic spreads through the continents,it has dramatically disrupted everything in the global economy from stock markets and supply chains to oil and food prices,and in seeking to restrict the spre...As the coronavirus pandemic spreads through the continents,it has dramatically disrupted everything in the global economy from stock markets and supply chains to oil and food prices,and in seeking to restrict the spread of COVID-19,governments are shutting down whole commercial sectors which could cause a huge recession in some countries as the United Nations have already warned.All these new circumstances have raised again the fundamental questions about the future of our global economy.Therefore,this paper has tried to make sense of how the post-pandemic global economy would look like by shedding light on Jeremy Rifkin’s theory of the new industrial revolution and the coming disruption in the global market.展开更多
Built on artificial intelligence, digitalization, and information technologies, the ＂Third Industrial Revolution ＂＂ transforms large-scale assembly lines and flexible manufacturing system with fundamental modern ma...Built on artificial intelligence, digitalization, and information technologies, the ＂Third Industrial Revolution ＂＂ transforms large-scale assembly lines and flexible manufacturing system with fundamental modern manufacturing technologies and features personalized manufacturing, which is enabled by reconfigurable manufacturing system, and quick market response. It is a profound transformation of techno-economic paradigms, imbedded in the technology, management, and institutional systems. As this revolution deepens, it is likely that manufacturing and the manufacturing sector would acquire new definitions. In addition, the resource foundation and factor structure, which are central to the competitiveness of a nation and an enterprise, would perhaps be reconfigured, hence rewriting the landscape of global industrial competition. Under this scenario, the ＂smiling curve ＇＂ which used to portray the economic features of the value chain, may change into a ＂silence curve＂ or even ＂sadness curve ＂. The catching- up pathway of latecomer countries, as predicted by the traditional ＇flying geese model＂, is likely to be blocked, solidifying the division of＂core and periphery countries＂ which is unfavorable to developing countries. Industrial competition between countries would move from competition between enterprises and supply chains to competition in industrial ecosystems, matdng system adaptability and dynamics the key to long-term industrial competitiveness. As an effort to embrace the ＂Third Industrial Revolution＂ and meet the challenges brought by ＂multi-facets competition＂ with developed industrial nations in various links of value chain, in the future China should make appropriate adjustments in its strategies for economic transition and upgrading, global competition, technological innovation, industrial development and information technology.展开更多
The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly fa...The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.展开更多
Due to the increasing price of raw material,the appreciation of RMB and the change in draw- back tax policy,the tie producing industry of Shengzhou has met a new crossroad after 20 years’ development.The Shengzhou go...Due to the increasing price of raw material,the appreciation of RMB and the change in draw- back tax policy,the tie producing industry of Shengzhou has met a new crossroad after 20 years’ development.The Shengzhou government is researching in the prospective development of tie industry,and has decided to implement the"Silk Expanding Project",whose goal is to form a silk industry base of China and even the world basing on the tie industry and other related textile industry.展开更多
The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has dri...The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.展开更多
As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds...As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.展开更多
In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalm...In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.展开更多
Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e....Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.展开更多
With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety...With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrai...Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrained hardware or lose accuracy under occlusion,vibration,and lighting changes.We introduce Industrial EdgeSign,a dual-path framework that combines hardware-aware neural architecture search(NAS)with large multimodalmodel(LMM)guided semantics to deliver robust,low-latency gesture recognition on edge devices.The searched model uses a truncated ResNet50 front end,a dimensional-reduction network that preserves spatiotemporal structure for tubelet-based attention,and localized Transformer layers tuned for on-device inference.To reduce reliance on gloss annotations and mitigate domain shift,we distill semantics from factory-tuned vision-language models and pre-train with masked language modeling and video-text contrastive objectives,aligning visual features with a shared text space.OnML2HP and SHREC’17,theNAS-derived architecture attains 94.7% accuracywith 86ms inference latency and about 5.9W power on Jetson Nano.Under occlusion,lighting shifts,andmotion blur,accuracy remains above 82%.For safetycritical commands,the emergency-stop gesture achieves 72 ms 99th percentile latency with 99.7% fail-safe triggering.Ablation studies confirm the contribution of the spatiotemporal tubelet extractor and text-side pre-training,and we observe gains in translation quality(BLEU-422.33).These results show that Industrial EdgeSign provides accurate,resource-aware,and safety-aligned gesture recognition suitable for deployment in smart factory settings.展开更多
Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the...Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the application of TVMDs for seismic response control of industrial buildings coupled with mechanical equipment.Therefore,this study proposes ungrounded and grounded TVMDs to effectively utilize the mass of the mechanical equipment and fully exploit the capabilities of the inerter element.An optimal design methodology is developed by pursuing the maximum effective damping ratio and seeking the most rational TVMD control scheme.Validation of TVMD control performance is conducted through time-history analysis based on 20 real seismic ground motions recommended by ATC-40,and by providing a barrel mixer industrial building as a real-life numerical example.The results show that both an ungrounded and grounded TVMD can effectively mitigate the seismic response of the primary structure.Compared to the traditional tuned mass damper(TMD),TVMDs can obtain improved control performance for a given equipment mass ratio.Moreover,an ungrounded TVMD and a TMD show similar working mechanisms that tend to release the displacement of equipment to keep their optimal state,whereas equipment displacement for a grounded TVMD should be strictly limited to provide sufficient anti-force.展开更多
TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,th...TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.展开更多
The world is marching into a new development period when the digital technology,physical technology,and biological technology have achieved an unprecedented development respectively in their own fields,and at the same...The world is marching into a new development period when the digital technology,physical technology,and biological technology have achieved an unprecedented development respectively in their own fields,and at the same time their applications are converging greatly.These are the three major technological drivers for the Fourth Industrial Revolution.This paper discusses the specific technology niches of each kind technological driver behind the Fourth Industrial Revolution,and then evaluates impacts of the Fourth Industrial Revolution on global industrial,economic,and social development.At last this paper proposes possible measures and policies for both firms and governments to cope with the changes brought by the Fourth Industrial Revolution.展开更多
Industrial revolutions have a profound impact on energy and metal demand.Based on technological improvement,industrial transformation,and changes of energy and metal consumption in the United States,this paper identif...Industrial revolutions have a profound impact on energy and metal demand.Based on technological improvement,industrial transformation,and changes of energy and metal consumption in the United States,this paper identified the evolution characteristics of energy and metal demand driven by industrial revolutions,and analyzed the trends of energy and metal demand driven by the fourth industrial revolution which is happening currently.Results indicated that fossil fuels were the major energy sources which boosted up the past three industrial revolutions,whereas their consumption increased at a slowing pace as the economy was growing continually;after the third industrial revolution,the consumption of fossil fuels decoupled gradually with the economic growth.As the industrial structure transformed as the industrial revolutions went on,more and more metals were used in the industries,and the consumption of different metals showed different trends.In recent years,a new technological revolution has surged mainly driven by the overall application of new information technologies.The technological advance in information,new energies,new materials,etc.,will speed up the industrial transformation and exert a deep effect on the demand of energy and metals.It can be inferred that the ratio of clean,non-polluting,renewable energy will rise while the ratio of fossil fuels will drop in the energy demand,and the demand of rare metals will perhaps enter a fast-growing period,while the demand of traditional bulk metals will fluctuate at mid-high levels.Following the new industrial revolution,China should adopt an energy transition strategy of developing low-carbon and free-carbon technologies simultaneously,reinforce the domestic and international metal supply system with the aim of enhancing global governance capability,strengthen the deep development of rich rare metals and broaden the overseas supply channels of scare rare metals.展开更多
The two apparent issues,Corona effect and 4th industrial revolution,are seemed to be totally irrelevant but can point out numerous similarities.Why and how?We may be able to point out how without any difficulty,but no...The two apparent issues,Corona effect and 4th industrial revolution,are seemed to be totally irrelevant but can point out numerous similarities.Why and how?We may be able to point out how without any difficulty,but no one can identify why.This article starts with how first then mumble around why with no confirmed conclusion.The only concluding remark may be“It is a Historian’s duty,not the engineers nor scientists”.For Corona virus,the major catch phrase is“Separation”,physically and mentally,which can be related to the 4th industrial revolution,which this article foresees and no confirmation on“what will happen next”.展开更多
Based on the analysis of manufacturing landscape, the landscape changes caused by the transportation revolution, and the urban landscape of the newly-developed houses caused by the industrial revolution, the landscape...Based on the analysis of manufacturing landscape, the landscape changes caused by the transportation revolution, and the urban landscape of the newly-developed houses caused by the industrial revolution, the landscape changes in England during the industrial revolution were summarized to fill the research gaps in this field and lay the foundations for relevant research.展开更多
文摘As the coronavirus pandemic spreads through the continents,it has dramatically disrupted everything in the global economy from stock markets and supply chains to oil and food prices,and in seeking to restrict the spread of COVID-19,governments are shutting down whole commercial sectors which could cause a huge recession in some countries as the United Nations have already warned.All these new circumstances have raised again the fundamental questions about the future of our global economy.Therefore,this paper has tried to make sense of how the post-pandemic global economy would look like by shedding light on Jeremy Rifkin’s theory of the new industrial revolution and the coming disruption in the global market.
文摘Built on artificial intelligence, digitalization, and information technologies, the ＂Third Industrial Revolution ＂＂ transforms large-scale assembly lines and flexible manufacturing system with fundamental modern manufacturing technologies and features personalized manufacturing, which is enabled by reconfigurable manufacturing system, and quick market response. It is a profound transformation of techno-economic paradigms, imbedded in the technology, management, and institutional systems. As this revolution deepens, it is likely that manufacturing and the manufacturing sector would acquire new definitions. In addition, the resource foundation and factor structure, which are central to the competitiveness of a nation and an enterprise, would perhaps be reconfigured, hence rewriting the landscape of global industrial competition. Under this scenario, the ＂smiling curve ＇＂ which used to portray the economic features of the value chain, may change into a ＂silence curve＂ or even ＂sadness curve ＂. The catching- up pathway of latecomer countries, as predicted by the traditional ＇flying geese model＂, is likely to be blocked, solidifying the division of＂core and periphery countries＂ which is unfavorable to developing countries. Industrial competition between countries would move from competition between enterprises and supply chains to competition in industrial ecosystems, matdng system adaptability and dynamics the key to long-term industrial competitiveness. As an effort to embrace the ＂Third Industrial Revolution＂ and meet the challenges brought by ＂multi-facets competition＂ with developed industrial nations in various links of value chain, in the future China should make appropriate adjustments in its strategies for economic transition and upgrading, global competition, technological innovation, industrial development and information technology.
基金supported by the Knowledge Innovation Program of Wuhan-Shuguang Project(Grant No.2023010201020443)the School-Level Scientific Research Project Funding Program of Jianghan University(Grant No.2022XKZX33)the Natural Science Foundation of Hubei Province(Grant No.2024AFB466).
文摘The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.
文摘Due to the increasing price of raw material,the appreciation of RMB and the change in draw- back tax policy,the tie producing industry of Shengzhou has met a new crossroad after 20 years’ development.The Shengzhou government is researching in the prospective development of tie industry,and has decided to implement the"Silk Expanding Project",whose goal is to form a silk industry base of China and even the world basing on the tie industry and other related textile industry.
文摘The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by the Korea Internet&Security Agency(KISA)through the Information Security Specialized University Support Project(50%).
文摘As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
基金supported in part by the National Natural Science Foundation of China(Grant No.62071123)in part by the Natural Science Foundation of Fujian Province(Grant Nos.2024J01971,2022J05202)in part by the Young and Middle-Aged Teacher Education Research Project of Fujian Province(Grant No.JAT210370).
文摘In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.
文摘Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.
文摘With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
文摘Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrained hardware or lose accuracy under occlusion,vibration,and lighting changes.We introduce Industrial EdgeSign,a dual-path framework that combines hardware-aware neural architecture search(NAS)with large multimodalmodel(LMM)guided semantics to deliver robust,low-latency gesture recognition on edge devices.The searched model uses a truncated ResNet50 front end,a dimensional-reduction network that preserves spatiotemporal structure for tubelet-based attention,and localized Transformer layers tuned for on-device inference.To reduce reliance on gloss annotations and mitigate domain shift,we distill semantics from factory-tuned vision-language models and pre-train with masked language modeling and video-text contrastive objectives,aligning visual features with a shared text space.OnML2HP and SHREC’17,theNAS-derived architecture attains 94.7% accuracywith 86ms inference latency and about 5.9W power on Jetson Nano.Under occlusion,lighting shifts,andmotion blur,accuracy remains above 82%.For safetycritical commands,the emergency-stop gesture achieves 72 ms 99th percentile latency with 99.7% fail-safe triggering.Ablation studies confirm the contribution of the spatiotemporal tubelet extractor and text-side pre-training,and we observe gains in translation quality(BLEU-422.33).These results show that Industrial EdgeSign provides accurate,resource-aware,and safety-aligned gesture recognition suitable for deployment in smart factory settings.
基金National Natural Science Foundation of China under Grant Nos.52408327 and 52278306Key Research and Development Program of Hunan Province,China under Grant No.2022SK2096+3 种基金Science and Technology Progress and Innovation Project of the Department of Transportation of Hunan Province,China under Grant No.201912Natural Science Foundation of Hunan Province,China under Grant No.2024JJ6198Scientific Research Project of the Education Department of Hunan Province,China under Grant No.25A0645Emergency Management Science and Technology Project of the Emergency Management Department of Hunan Province,China under Grant No.yjtkjxm_202406。
文摘Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the application of TVMDs for seismic response control of industrial buildings coupled with mechanical equipment.Therefore,this study proposes ungrounded and grounded TVMDs to effectively utilize the mass of the mechanical equipment and fully exploit the capabilities of the inerter element.An optimal design methodology is developed by pursuing the maximum effective damping ratio and seeking the most rational TVMD control scheme.Validation of TVMD control performance is conducted through time-history analysis based on 20 real seismic ground motions recommended by ATC-40,and by providing a barrel mixer industrial building as a real-life numerical example.The results show that both an ungrounded and grounded TVMD can effectively mitigate the seismic response of the primary structure.Compared to the traditional tuned mass damper(TMD),TVMDs can obtain improved control performance for a given equipment mass ratio.Moreover,an ungrounded TVMD and a TMD show similar working mechanisms that tend to release the displacement of equipment to keep their optimal state,whereas equipment displacement for a grounded TVMD should be strictly limited to provide sufficient anti-force.
文摘TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.
基金Under the auspices of National Natural Science Foundation of China(No.41671120,41401125)
文摘The world is marching into a new development period when the digital technology,physical technology,and biological technology have achieved an unprecedented development respectively in their own fields,and at the same time their applications are converging greatly.These are the three major technological drivers for the Fourth Industrial Revolution.This paper discusses the specific technology niches of each kind technological driver behind the Fourth Industrial Revolution,and then evaluates impacts of the Fourth Industrial Revolution on global industrial,economic,and social development.At last this paper proposes possible measures and policies for both firms and governments to cope with the changes brought by the Fourth Industrial Revolution.
文摘Industrial revolutions have a profound impact on energy and metal demand.Based on technological improvement,industrial transformation,and changes of energy and metal consumption in the United States,this paper identified the evolution characteristics of energy and metal demand driven by industrial revolutions,and analyzed the trends of energy and metal demand driven by the fourth industrial revolution which is happening currently.Results indicated that fossil fuels were the major energy sources which boosted up the past three industrial revolutions,whereas their consumption increased at a slowing pace as the economy was growing continually;after the third industrial revolution,the consumption of fossil fuels decoupled gradually with the economic growth.As the industrial structure transformed as the industrial revolutions went on,more and more metals were used in the industries,and the consumption of different metals showed different trends.In recent years,a new technological revolution has surged mainly driven by the overall application of new information technologies.The technological advance in information,new energies,new materials,etc.,will speed up the industrial transformation and exert a deep effect on the demand of energy and metals.It can be inferred that the ratio of clean,non-polluting,renewable energy will rise while the ratio of fossil fuels will drop in the energy demand,and the demand of rare metals will perhaps enter a fast-growing period,while the demand of traditional bulk metals will fluctuate at mid-high levels.Following the new industrial revolution,China should adopt an energy transition strategy of developing low-carbon and free-carbon technologies simultaneously,reinforce the domestic and international metal supply system with the aim of enhancing global governance capability,strengthen the deep development of rich rare metals and broaden the overseas supply channels of scare rare metals.
文摘The two apparent issues,Corona effect and 4th industrial revolution,are seemed to be totally irrelevant but can point out numerous similarities.Why and how?We may be able to point out how without any difficulty,but no one can identify why.This article starts with how first then mumble around why with no confirmed conclusion.The only concluding remark may be“It is a Historian’s duty,not the engineers nor scientists”.For Corona virus,the major catch phrase is“Separation”,physically and mentally,which can be related to the 4th industrial revolution,which this article foresees and no confirmation on“what will happen next”.
文摘Based on the analysis of manufacturing landscape, the landscape changes caused by the transportation revolution, and the urban landscape of the newly-developed houses caused by the industrial revolution, the landscape changes in England during the industrial revolution were summarized to fill the research gaps in this field and lay the foundations for relevant research.
