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Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning
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作者 Bowen Yu Chunli Xie 《Computers, Materials & Continua》 SCIE EI 2024年第1期1329-1343,共15页
With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivo... With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components. 展开更多
关键词 Industrial defect detection deep learning intelligent manufacturing
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Research on Machine Tool Fault Diagnosis and Maintenance Optimization in Intelligent Manufacturing Environments
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作者 Feiyang Cao 《Journal of Electronic Research and Application》 2024年第4期108-114,共7页
In the context of intelligent manufacturing,machine tools,as core equipment,directly influence production efficiency and product quality through their operational reliability.Traditional maintenance methods for machin... In the context of intelligent manufacturing,machine tools,as core equipment,directly influence production efficiency and product quality through their operational reliability.Traditional maintenance methods for machine tools,often characterized by low efficiency and high costs,fail to meet the demands of modern manufacturing industries.Therefore,leveraging intelligent manufacturing technologies,this paper proposes a solution optimized for the diagnosis and maintenance of machine tool faults.Initially,the paper introduces sensor-based data acquisition technologies combined with big data analytics and machine learning algorithms to achieve intelligent fault diagnosis of machine tools.Subsequently,it discusses predictive maintenance strategies by establishing an optimized model for maintenance strategy and resource allocation,thereby enhancing maintenance efficiency and reducing costs.Lastly,the paper explores the architectural design,integration,and testing evaluation methods of intelligent manufacturing systems.The study indicates that optimization of machine tool fault diagnosis and maintenance in an intelligent manufacturing environment not only enhances equipment reliability but also significantly reduces maintenance costs,offering broad application prospects. 展开更多
关键词 Intelligent manufacturing Machine tool fault diagnosis Predictive maintenance Big data Machine learning System integration
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Research on the Design and Application of Virtual and Real Integrated Training Platform Based on Intelligent Manufacturing
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作者 Xiayun Liu Dakang Li +1 位作者 Xuan Liang Lingfang Wu 《Journal of Electronic Research and Application》 2024年第3期34-41,共8页
In this paper,we built a robot training platform using virtual simulation software,and the robot assembly,handling,and palletizing were realized.The workstation includes an industrial robot,gas control unit,track func... In this paper,we built a robot training platform using virtual simulation software,and the robot assembly,handling,and palletizing were realized.The workstation includes an industrial robot,gas control unit,track function module,assembly function module,palletizing function module,vision module,etc.,and robot movement is achieved through language programming.The platform provides conditions for the practical ability training of application-oriented talents. 展开更多
关键词 Intelligent manufacturing Training platform Virtual simulation
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Intelligent Manufacturing for the Process Industry Driven by Industrial Artificial Intelligence 被引量:17
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作者 Tao Yang Xinlei Yi +2 位作者 Shaowen Lu Karl HJohansson Tianyou Chai 《Engineering》 SCIE EI 2021年第9期1224-1230,共7页
Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the pro... Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry. 展开更多
关键词 Industrial artificial intelligence Industrial Internet Intelligent manufacturing Process industry
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Smart Design and Manufacturing the Welded Q350 Steel Frames via Lifecycle Management Strategy of Digital Twin
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作者 Letian Fan Xinchao Wang +11 位作者 Yongsheng Chen Li Wang Shumi Liu Yuanfei Wang Xinwei Li Kun Du Jia Zhang Xingyu Gao Feng Sun Haifeng Song William Yi Wang Jinshan Li 《Journal of Beijing Institute of Technology》 EI CAS 2023年第4期385-395,共11页
Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by ... Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by the dramatical developments of the services of China Railway High-speed series for more than a decade,it is essential to reveal the foundations of lifecycle man-agement of those trains under environmental conditions.Here,the smart design and manufacturing of welded Q350 steel frames of CR200J series are introduced,presenting the capability and opportu-nity of ICME in weight reduction and lifecycle management at a cost-effective approach.In order to address the required fatigue life time enduring more than 9×10^(6)km,the response of optimized frames to the static and the dynamic loads are comprehensively investigated.It is highlighted that the maximum residual stress of the optimized welded frame is reduced to 69 MPa from 477 MPa of previous existing one.Based on the measured stress and acceleration from the railways,the fatigue life of modified frame under various loading modes could fulfil the requirements of the lifecycle man-agement.Moreover,our recent developed intelligent quality control strategy of welding process mediated by machine learning is also introduced,envisioning its application in the intelligent weld-ing. 展开更多
关键词 FATIGUE intelligent manufacturing integrated computational materials engineering(ICME) digital twin machine learning
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Research on the Training of Interdisciplinary-Based Intelligent Manufacturing Talents
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作者 Yuan Qin Meng Wang Mei Li 《Journal of Contemporary Educational Research》 2023年第2期15-22,共8页
As a significant field of research under the 14th Five Year Plan,intelligent manufacturing holds a special position in industrial upgrading and core technology independence.Intelligent manufacturing is an important su... As a significant field of research under the 14th Five Year Plan,intelligent manufacturing holds a special position in industrial upgrading and core technology independence.Intelligent manufacturing is an important support for building a“scientific and technological power”in the future.Cultivating creative interdisciplinary talents who can adapt to the development of intelligent manufacturing industry in the new era is of great significance for China to realize the modernization and autonomy of its industrial system.In view of the existing gap between the interdisciplinary talent training of intelligent manufacturing and the actual needs of the industry,this paper focuses on the concept of interdisciplinary construction.Based on the cycle improvement of professional construction,a curriculum system that integrates the interaction of interconnected projects is established.Through four specific measures,namely establishing the collaborative development system of intelligent manufacturing specialty,building a cycle diagnosis and reform system of intelligent manufacturing specialty,improving the curriculum system of integrated modular specialty group,and setting up an application scenario project-based curriculum,we hope to provide reference for the cross-training of compound intelligent manufacturing talents. 展开更多
关键词 Intelligent manufacturing Personnel training Specialty construction Cycle diagnosis and correction
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An Interpretable Light Attention-Convolution-Gate Recurrent Unit Architecture for the Highly Accurate Modeling of Actual Chemical Dynamic Processes
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作者 Yue Li Ning Li +1 位作者 Jingzheng Ren Weifeng Shen 《Engineering》 SCIE EI CAS CSCD 2024年第8期104-116,共13页
To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new lig... To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing. 展开更多
关键词 Interpretable machine learning Light attention-convolution-gate recurrent unit architecture Process knowledge discovery Data-driven process model Intelligent manufacturing
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Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line
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作者 Xianfeng Cao Meihua Yao +2 位作者 Yahui Zhang Xiaofeng Hu Chuanxun Wu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第6期3233-3253,共21页
As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing ... As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment. 展开更多
关键词 Transmission front and middle case assembly line digital twin(DT) simulating optimization intelligent manufacturing
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Direct 4D printing of functionally graded hydrogel networks for biodegradable,untethered,and multimorphic soft robots
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作者 Soo Young Cho Dong Hae Ho +1 位作者 Sae Byeok Jo Jeong Ho Cho 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2024年第2期407-416,共10页
Recent advances in functionally graded additive manufacturing(FGAM)technology have enabled the seamless hybridization of multiple functionalities in a single structure.Soft robotics can become one of the largest benef... Recent advances in functionally graded additive manufacturing(FGAM)technology have enabled the seamless hybridization of multiple functionalities in a single structure.Soft robotics can become one of the largest beneficiaries of these advances,through the design of a facile four-dimensional(4D)FGAM process that can grant an intelligent stimuli-responsive mechanical functionality to the printed objects.Herein,we present a simple binder jetting approach for the 4D printing of functionally graded porous multi-materials(FGMM)by introducing rationally designed graded multiphase feeder beds.Compositionally graded cross-linking agents gradually form stable porous network structures within aqueous polymer particles,enabling programmable hygroscopic deformation without complex mechanical designs.Furthermore,a systematic bed design incorporating additional functional agents enables a multi-stimuli-responsive and untethered soft robot with stark stimulus selectivity.The biodegradability of the proposed 4D-printed soft robot further ensures the sustainability of our approach,with immediate degradation rates of 96.6%within 72 h.The proposed 4D printing concept for FGMMs can create new opportunities for intelligent and sustainable additive manufacturing in soft robotics. 展开更多
关键词 intelligent and sustainable additive manufacturing multi-material four-dimensional printing untethered soft robot multi-stimuli-responsive soft robot biodegradable soft robotics
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Intelligent Manufacturing in the Context of Industry 4.0: A Review 被引量:155
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作者 Ray Y. Zhong Xun Xu +1 位作者 Eberhard Klotz Stephen T. Newman 《Engineering》 SCIE EI 2017年第5期616-630,共15页
Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope wit... Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution. 展开更多
关键词 Intelligent manufacturing Industry 4.0 Internet of Things manufacturing systems Cloud manufacturing Cyber-physical system
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Integrated and Intelligent Manufacturing: Perspectives and Enablers 被引量:32
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作者 Yubao Chen 《Engineering》 SCIE EI 2017年第5期588-595,共8页
With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry ... With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership (AMP) in 2011 and the National Network for Manufacturing Innovation (NNMI) in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further "leverage existing resources... to nurture manufacturing innovation and accelerate commercialization" by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10- year plan and roadmap toward manufacturing: Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features: integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing (i2M) systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Intemet of Things and Services (IoTS), cyber-physical systems (CPSs), and cloud computing are discussed. Challenges are addressed with applica- tions that are based on commercially available platforms such as General Electric (GE)'s Predix and PTC's ThingWorx. 展开更多
关键词 Integrated manufacturing Intelligent manufacturing Cloud computing Cyber-physical system Internet of Things Industrial Internet Predictive analytics manufacturing platform
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Smart Manufacturing and Intelligent Manufacturing:A Comparative Review 被引量:33
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作者 Baicun Wang Fei Tao +3 位作者 Xudong Fang Chao Liu Yufei Liu Theodor Freiheit 《Engineering》 SCIE EI 2021年第6期738-757,共20页
The application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the world.However,different terminologies,namely smart manufacturing(SM)and intelligent manufact... The application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the world.However,different terminologies,namely smart manufacturing(SM)and intelligent manufacturing(IM),have been applied to what may be broadly characterized as a similar paradigm by some researchers and practitioners.While SM and IM are similar,they are not identical.From an evolutionary perspective,there has been little consideration on whether the definition,thought,connotation,and technical development of the concepts of SM or IM are consistent in the literature.To address this gap,the work performs a qualitative and quantitative investigation of research literature to systematically compare inherent differences of SM and IM and clarify the relationship between SM and IM.A bibliometric analysis of publication sources,annual publication numbers,keyword frequency,and top regions of research and development establishes the scope and trends of the currently presented research.Critical topics discussed include origin,definitions,evolutionary path,and key technologies of SM and IM.The implementation architecture,standards,and national focus are also discussed.In this work,a basis to understand SM and IM is provided,which is increasingly important because the trend to merge both terminologies rises in Industry 4.0 as intelligence is being rapidly applied to modern manufacturing and human–cyber–physical systems. 展开更多
关键词 Smart manufacturing Intelligent manufacturing Industry 4.0 Human–cyber–physical system(HCPS)
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Advanced Data Collection and Analysis in Data‑Driven Manufacturing Process 被引量:11
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作者 Ke Xu Yingguang Li +4 位作者 Changqing Liu Xu Liu Xiaozhong Hao James Gao Paul G.Maropoulos 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2020年第3期32-52,共21页
The rapidly increasing demand and complexity of manufacturing process potentiates the usage of manufacturing data with the highest priority to achieve precise analyze and control,rather than using simplified physical ... The rapidly increasing demand and complexity of manufacturing process potentiates the usage of manufacturing data with the highest priority to achieve precise analyze and control,rather than using simplified physical models and human expertise.In the era of data-driven manufacturing,the explosion of data amount revolutionized how data is collected and analyzed.This paper overviews the advance of technologies developed for in-process manufacturing data collection and analysis.It can be concluded that groundbreaking sensoring technology to facilitate direct measurement is one important leading trend for advanced data collection,due to the complexity and uncertainty during indirect measurement.On the other hand,physical model-based data analysis contains inevitable simplifications and sometimes ill-posed solutions due to the limited capacity of describing complex manufacturing process.Machine learning,especially deep learning approach has great potential for making better decisions to automate the process when fed with abundant data,while trending data-driven manufacturing approaches succeeded by using limited data to achieve similar or even better decisions.And these trends can demonstrated be by analyzing some typical applications of manufacturing process. 展开更多
关键词 Data-driven manufacturing Intelligent manufacturing Process monitoring Data analysis Machine learning
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Operation optimization of the steel manufacturing process: A brief review 被引量:7
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作者 Zhao-jun Xu Zhong Zheng Xiao-qiang Gao 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2021年第8期1274-1287,共14页
Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel ma... Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized. 展开更多
关键词 intelligent manufacturing operation optimization steel manufacturing process process simulation production planning production scheduling
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Intelligent Manufacturing Systems in COVID‑19 Pandemic and Beyond:Framework and Impact Assessment 被引量:4
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作者 Xingyu Li Baicun Wang +2 位作者 Chao Liu Theodor Freiheit Bogdan I.Epureanu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2020年第4期1-5,共5页
Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks.The intelligent manuf... Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks.The intelligent manufacturing(IM)systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms.The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network,which mitigates the severity of industrial chain disruption.In this study,we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks.Considering the constraints of the IM resources,we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic. 展开更多
关键词 Intelligent manufacturing system COVID-19 pandemic Industrial network Supply chain disruption OPTIMIZATION
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Knowledge expression,numerical modeling and optimization application of ethylene thermal cracking:From the perspective of intelligent manufacturing 被引量:2
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作者 Kexin Bi Shuyuan Zhang +4 位作者 Chen Zhang Haoran Li Xinye Huang Haoyu Liu Tong Qiu 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2021年第10期1-17,共17页
Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and intelligence.For ethylene thermal cracking,knowledge expression,numerical mo... Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and intelligence.For ethylene thermal cracking,knowledge expression,numerical modeling and intelligent optimization are key steps for intelligent manufacturing.This paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking;introduces the frameworks,methods and algorithms that have been proposed over the past10 years and discusses the advantages,limitations and applications in industrial practice.An entire set of molecular-level modeling approaches from feedstocks to products,including feedstock molecular reconstruction,reaction-network auto-generation and cracking unit simulation are described.Multilevel control and optimization methods are exhibited,including at the operational,cycle,plant and enterprise level.Relevant software packages are introduced.Finally,an outlook in terms of future directions is presented. 展开更多
关键词 Ethylene thermal cracking PSE Intelligent manufacturing Molecularization and digitization Modeling and optimization
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The Future of Manufacturing: A New Perspective 被引量:10
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作者 Ben Wang 《Engineering》 2018年第5期722-728,共7页
Many articles have been published on intelligent manufacturing, most of which focus on hardware, soft-ware, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a dif-ferent ... Many articles have been published on intelligent manufacturing, most of which focus on hardware, soft-ware, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a dif-ferent perspective by examining relevant challenges and providing examples of some less-talked-about yet essential topics, such as hybrid systems, redefining advanced manufacturing, basic building blocks of new manufacturing, ecosystem readiness, and technology scalahility. The first major challenge is to (re-)define what the manufacturing of the future will he, if we wish to: ① raise public awareness of new manufacturing's economic and societal impacts, and ② garner the unequivocal support of policy- makers. The second major challenge is to recognize that manufacturing in the future will consist of sys-tems of hybrid systems of human and robotic operators; additive and suhtractive processes; metal and composite materials; and cyher and physical systems. Therefore, studying the interfaces between con- stituencies and standards becomes important and essential. The third challenge is to develop a common framework in which the technology, manufacturing business case, and ecosystem readiness can he eval- uated concurrently in order to shorten the time it takes for products to reach customers. Integral to this is having accepted measures of "scalahility" of non-information technologies. The last, hut not least, chal-lenge is to examine successful modalities of industry-academia-government collaborations through public-private partnerships. This article discusses these challenges in detail. 展开更多
关键词 Advanced manufacturing Partnership ECOSYSTEM Industry 4.0 Intelligent manufacturing Internet of Things manufacturing innovation institutes National Network for manufacturing INNOVATION
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Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System
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作者 Zhong-Qi Sheng Chang-Ping Tang Ci-Xing Lv 《International Journal of Automation and computing》 EI 2010年第4期596-602,共7页
Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of ... Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper. 展开更多
关键词 Agile manufacturing intelligent manufacturing production scheduling system modeling agent technology
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Promoting the development of intelligent manufacturing in metallurgical enterprises based on physical and chemical metallurgical principles
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作者 CHANG Wenjie ZHAO Xianjiu XU Jin 《Baosteel Technical Research》 CAS 2022年第4期40-47,共8页
Based on production data and metallurgical theory, this study discusses the control of inclusions in Baosteel’s products from the perspective of three key processes: converting, refining, and continuous casting(CC).T... Based on production data and metallurgical theory, this study discusses the control of inclusions in Baosteel’s products from the perspective of three key processes: converting, refining, and continuous casting(CC).The control of converter slagging, refining oxygen blowing(OB),and CC are considered.Based on metallurgical theory, this research investigates the effects of refining OB decarburization and argon blowing in a tundish on the oxygen content of molten steel.Combining theory and practice is beneficial to the discovery of new ways to tackle existing problems and the development of intelligent manufacturing. 展开更多
关键词 intelligent manufacturing SLAGGING REFINING continuous casting TUNDISH
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Analysis on the development of intelligent manufacturing industry in Shanghai
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作者 CAI Xiaoyan XUE Xia NI Ai 《International English Education Research》 2017年第5期1-3,共3页
Intelligent manufacturing is the transformation and upgrading of Chma's manutactunng industry, to speeu up me transformation from the manufacturing power to the main direction of manufacturing power, but also to impl... Intelligent manufacturing is the transformation and upgrading of Chma's manutactunng industry, to speeu up me transformation from the manufacturing power to the main direction of manufacturing power, but also to implement the "Made in China 2025" and "lntemet plus" strategy to promote the supply side of the manufacturing sector reform, building a global influence of the importatu center of science and technology innovation center. An analysis of the present situation of intelligent manufacturing industry in Shanghai, we can point out the deficiency of its development and point out the direction for the development of the intelligent manufacturing industry in Shanghai. 展开更多
关键词 Intelligent manufacturing Transformation and upgrading Industry development
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