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
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
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
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
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
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
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
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
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
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
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
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
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
NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological proces...NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological process and production tempo.The layout and simulation of the production line can more directly reflect the problems that may occur in the operation of the production line,and solve these problems through scientific methods.This project uses VisualOne software to simulate the operation of the intelligent manufacturing production line,which can directly find the existing problems in the layout of the production line and the process of the craftsmen,and optimize the layout of the production line.In addition,it can provide reliable support for the equipment procurement and on-site construction of the intelligent manufacturing automation production line in the later stage.展开更多
This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management succe...This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management success,being a new entrepreneurial management,with support of this new technology in the reduction of costs and increased value added.HMS is in the process of being developed in the so-called"Consortium of the Rich Countries for the 21st Century",which involves governments,companies and universities from the first world countries,developing technology and knowledge related to the Holonic Manufacturing System(HMS).This new concept,under development by the above consortium,will allow the countries that hold this advancement to overcome the challenges of the globalized market and gain even more international competitiveness.展开更多
The 5th Meeting of Sino-German Standardization Sub-working Group on Intelligent Manufacturing/Industry 4.0 was held in Hangzhou,capital of east China’s Zhejiang province from December 3 to 4,2017,bringing together ov...The 5th Meeting of Sino-German Standardization Sub-working Group on Intelligent Manufacturing/Industry 4.0 was held in Hangzhou,capital of east China’s Zhejiang province from December 3 to 4,2017,bringing together over 90 representatives of both countries.SAC Vice-Administrator Yin Minghan highly appreciated the role of the standardization cooperation mechanism in展开更多
The advancement of intelligent manufacturing in Dongguan puts forward new requirements for industrial talents,and the development of new productivity is bound to force enterprises and employees to make adaptive adjust...The advancement of intelligent manufacturing in Dongguan puts forward new requirements for industrial talents,and the development of new productivity is bound to force enterprises and employees to make adaptive adjustments.The upgrading of intelligent manufacturing is not only the upgrading of intelligent machines but also the upgrading of the human brain,which includes the reshaping and cultivation of industrial talents.Based on field research,this study analyzes the different characteristics of the traditional and the new intelligent manufacturing model,as well as summarizes the characteristics of industrial talents and the changing trend of talent demand in view of the intelligent manufacturing model in Dongguan.展开更多
The world is currently undergoing profound changes which have never happened within the past century.Global competition in the technology and industry fields is becoming increasingly fierce.The strategic competition o...The world is currently undergoing profound changes which have never happened within the past century.Global competition in the technology and industry fields is becoming increasingly fierce.The strategic competition of the major powers further focuses on the manufacturing industry.Developed countries such as the United States,Germany,and Japan have successively put forward strategic plans such as“re-industrialization”and“return of manufacturing industry”,aiming to seize the commanding heights of a new round of global high-end technology competition and expand international market share.Standing at the historic intersection of a new round of scientific and technological revolution and China's accelerated high-quality development,the“14th Five-Year Plan”clearly pointed out that intelligent manufacturing is the main development trend to promote China's manufacturing to the medium-high end of the global value chain.This reflects the importance of advanced manufacturing for national strategic layout.To better grasp the development direction of advanced manufacturing equipment,the development process and current application status of manufacturing equipment are summarized,and thereafter the characteristics of manufacturing equipment in different development stages of the manufacturing industry are analyzed.Finally,the development trend of advanced milling equipment is prospected.展开更多
Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significa...Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.展开更多
基金supported by the Natural Science Foundation of Heilongjiang Province(Grant Number:LH2021F002).
文摘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.
基金2023 Autonomous Region Level College Students Innovation and Entrepreneurship Training Plan Project:Virtual and Real Integration of Industrial Robot Training Room(Project number:S202311546109)2023 Industry-University Cooperative Education Project of the Ministry of Education(Project number:230801212255027)+2 种基金2023 Guangxi Higher Education Undergraduate Teaching Reform Project:Research and Practice of Mixed Teaching Reform of Industrial Robot Operation and Programming Based on the Integration of Industry and Education(Project number:2023JGA362)2022 Guangxi Vocational Education Teaching Reform Research Project:Construction and Practice of Integrated Curriculum Resources for Robot Engineering Majors Based on Industrial College(Project number:GXGZJG2022B076)2022 Guangxi Science and Technology Normal University Research Fund Project:Path Planning of Loading and Unloading Robot based on Optimal Energy Consumption(Project number:GXKS2022QN006).
文摘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.
基金This research was supported by the National Natural Science Foundation of China(61991400,61991403,and 61991404)China Institute of Engineering Consulting Research Project(2019-ZD-12)the 2020 Science and Technology Major Project of Liaoning Province(2020JH1/10100008),China.
文摘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.
基金supported by the National Basic Scientific Research Project of China (No.JCKY2020607B003)CRRC (No.202CDA001)
文摘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.
基金This work was supported by the 2022 China University of Geosciences(Beijing)Disciplinary Development Research Fund Project“Research on Intelligent Manufacturing Talents Training Method Based on Interdisciplinary Integration”(Project Number:2022XK104).
文摘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.
基金supported by China National Heavy Duty Truck Group Co.,Ltd.(Grant No.YF03221048P)the Shanghai Municipal Bureau of Market Supervision and Administration(Grant No.2022-35)New Young TeachersResearch Start-Up Foundation of Shanghai Jiao Tong University(Grant No.22X010503668).
文摘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.
基金supported by the International Postdoctoral Exchange Fellowship Program(20180025)National Natural Science Foundation of China(51703180)+2 种基金China Postdoctoral Science Foundation(2018M630191,2017M610634)Shaanxi Postdoctoral Science Foundation(2017BSHEDZZ73)Fundamental Research Funds for the Central Universities(xpt012020006,xjj2017024).
文摘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.
基金Supported by National Natural Science Foundation of China(Grant No.51805260)National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.51925505)National Natural Science Foundation of China(Grant No.51775278).
文摘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.
基金financially supported by the National Natural Science Foundation of China (No.51734004)the National Key Research and Development Program of China (No.2017YFB0304005)the National Natural Science Foundation of China (No.51474044)。
文摘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.
基金the International Postdoctoral Exchange Fellowship Program(20180025).
文摘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.
基金The authors gratefully acknowledge the National Natural Science Foundation of China for its financial support(U1462206).
文摘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.
基金supported by Fundamental Research Funds for the Central Universities (No. N090403005)
文摘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.
文摘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.
基金supported by 2019 Project of the 13th Five-year Plan of Fujian Education and Science(FJJKCGZ19-016)。
文摘NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological process and production tempo.The layout and simulation of the production line can more directly reflect the problems that may occur in the operation of the production line,and solve these problems through scientific methods.This project uses VisualOne software to simulate the operation of the intelligent manufacturing production line,which can directly find the existing problems in the layout of the production line and the process of the craftsmen,and optimize the layout of the production line.In addition,it can provide reliable support for the equipment procurement and on-site construction of the intelligent manufacturing automation production line in the later stage.
文摘This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management success,being a new entrepreneurial management,with support of this new technology in the reduction of costs and increased value added.HMS is in the process of being developed in the so-called"Consortium of the Rich Countries for the 21st Century",which involves governments,companies and universities from the first world countries,developing technology and knowledge related to the Holonic Manufacturing System(HMS).This new concept,under development by the above consortium,will allow the countries that hold this advancement to overcome the challenges of the globalized market and gain even more international competitiveness.
文摘The 5th Meeting of Sino-German Standardization Sub-working Group on Intelligent Manufacturing/Industry 4.0 was held in Hangzhou,capital of east China’s Zhejiang province from December 3 to 4,2017,bringing together over 90 representatives of both countries.SAC Vice-Administrator Yin Minghan highly appreciated the role of the standardization cooperation mechanism in
文摘The advancement of intelligent manufacturing in Dongguan puts forward new requirements for industrial talents,and the development of new productivity is bound to force enterprises and employees to make adaptive adjustments.The upgrading of intelligent manufacturing is not only the upgrading of intelligent machines but also the upgrading of the human brain,which includes the reshaping and cultivation of industrial talents.Based on field research,this study analyzes the different characteristics of the traditional and the new intelligent manufacturing model,as well as summarizes the characteristics of industrial talents and the changing trend of talent demand in view of the intelligent manufacturing model in Dongguan.
基金the Ministry of Education-China Mobile Research Foundation Project of China(MCM20180703)the National Key Research and Development Program of China(2020YFB1711100)for financial support.
基金Supported by National Natural Science Foundation of China (Grant No.92148301)。
文摘The world is currently undergoing profound changes which have never happened within the past century.Global competition in the technology and industry fields is becoming increasingly fierce.The strategic competition of the major powers further focuses on the manufacturing industry.Developed countries such as the United States,Germany,and Japan have successively put forward strategic plans such as“re-industrialization”and“return of manufacturing industry”,aiming to seize the commanding heights of a new round of global high-end technology competition and expand international market share.Standing at the historic intersection of a new round of scientific and technological revolution and China's accelerated high-quality development,the“14th Five-Year Plan”clearly pointed out that intelligent manufacturing is the main development trend to promote China's manufacturing to the medium-high end of the global value chain.This reflects the importance of advanced manufacturing for national strategic layout.To better grasp the development direction of advanced manufacturing equipment,the development process and current application status of manufacturing equipment are summarized,and thereafter the characteristics of manufacturing equipment in different development stages of the manufacturing industry are analyzed.Finally,the development trend of advanced milling equipment is prospected.
文摘Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.