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
With the rapid development of the aviation industry,the development of intelligent manufacturing equipment represented by composite robots has been paid close attention by the aviation industry.Based on the analysis o...With the rapid development of the aviation industry,the development of intelligent manufacturing equipment represented by composite robots has been paid close attention by the aviation industry.Based on the analysis of the background and main structure function of composite robots,this paper focuses on the analysis of key technologies such as composite robot hardware design,visual sensing and planning system,integrated control of‘hands,feet,and eyes',multi-robot collaborative operation,and safety.The typical applications of composite robots in aviation intelligent manufacturing such as automatic drilling and connection of aircraft,aircraft surface spraying and finishing,parts handling,aircraft measurement,and inspection are presented.The development trends such as standardization of composite robots,integration of‘5G+cloud computing+AI',and fusion of intelligent sensors are proposed.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
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
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
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
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
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
An intelligent manufacturing system is a composite intelligent system comprising humans,cyber systems,and physical systems with the aim of achieving specific manufacturing goals at an optimized level.This kind of inte...An intelligent manufacturing system is a composite intelligent system comprising humans,cyber systems,and physical systems with the aim of achieving specific manufacturing goals at an optimized level.This kind of intelligent system is called a human-cyber-physical system(HCPS).In terms of technology,HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing.It can be concluded that the essence of intelligent manufacturing is to design,construct,and apply HCPSs in various cases and at different levels.With advances in information technology,intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing,and is evolving toward new-generation intelligent manufacturing(NGIM).NGIM is characterized by the in-depth integration of new-generation artificial intelligence(AI)technology(i.e.,enabling technology)with advanced manufacturing technology(i.e.,root technology);it is the core driving force of the new industrial revolution.In this study,the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs,and the implications,characteristics,technical frame,and key technologies of HCPSs for NGIM are then discussed in depth.Finally,an outlook of the major challenges of HCPSs for NGIM is proposed.展开更多
Intelligent technologies are leading to the next wave of industrial revolution in manufacturing.In developed economies,firms are embracing these advanced technologies following a sequential upgrading strategy-from dig...Intelligent technologies are leading to the next wave of industrial revolution in manufacturing.In developed economies,firms are embracing these advanced technologies following a sequential upgrading strategy-from digital manufacturing to smart manufacturing(digital-networked),and then to newgeneration intelligent manufacturing paradigms.However,Chinese firms face a different scenario.On the one hand,they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies;thus,they may not follow an identical upgrading pathway.On the other hand,Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners;thus,the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging,if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies.This study addresses the following question by conducting multiple case studies:Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies?The data sources include semistructured interviews and archival data.This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in nonconsecutive ways.This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics;furthermore,this finding can be extended to other catching-up economies.This paper provides a strategic roadmap as an explanatory guide to manufacturing firms,policymakers,and investors.展开更多
Intelligent manufacturing technology has become a major trend in the development of the manufacturing industry around the world,and is being studied and applied by numerous industrially developed countries.For example...Intelligent manufacturing technology has become a major trend in the development of the manufacturing industry around the world,and is being studied and applied by numerous industrially developed countries.For example,the United States has proposed an intelligent manufacturing layout based on the Industrial Internet and the‘‘New Generation of Robots”;Germany has proposed the Industry 4.0 initiative to boost the competitiveness of the manufacturing industry through intelligent manufacturing;and the European Union(EU),Japan,Korea,China,and other large manufacturing countries have put forward corresponding strategies for the development of intelligent manufacturing.Clearly,intelligent manufacturing has become an important direction in the development of the manufacturing industry.展开更多
Green and intelligent manufacturing will be the development direction of manufacturing industry because of their features: low pollution on the environment, high effi ciency and automatic production. The rapid develop...Green and intelligent manufacturing will be the development direction of manufacturing industry because of their features: low pollution on the environment, high effi ciency and automatic production. The rapid development of internet is changing the direction of the manufacturing industry, which will impact the green and intelligent manufacturing. Based on these, the environment and conditions of green and intelligent manufacturing brought by internet is sorted out in this paper; and the new opportunities and challenges of green and intelligent manufacturing in the internet era are analyzed. Then, the path for the realizing green and intelligent manufacturing is studied; and some policy recommendations are put forward to promote the realization of green and intelligent manufacturing.展开更多
Estimating the cycle time of each job over event streams in intelligent manufacturing is critical. These streams include many long-lasting events which have certain durations. The temporal relationships among those in...Estimating the cycle time of each job over event streams in intelligent manufacturing is critical. These streams include many long-lasting events which have certain durations. The temporal relationships among those interval-based events are often complex. Meanwhile, network latencies and machine failures in intelligent manufacturing may cause events to be out-of-order. This topic has rarely been discussed because most existing methods do not consider both interval-based and out-of-order events. In this work, we analyze the preliminaries of event temporal semantics. A tree-plan model of interval-based out-of-order events is proposed. A hybrid solution is correspondingly introduced. Extensive experimental studies demonstrate the efficiency of our approach.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the National Key Research and Development Program of China(No.2022YFB4700400)。
文摘With the rapid development of the aviation industry,the development of intelligent manufacturing equipment represented by composite robots has been paid close attention by the aviation industry.Based on the analysis of the background and main structure function of composite robots,this paper focuses on the analysis of key technologies such as composite robot hardware design,visual sensing and planning system,integrated control of‘hands,feet,and eyes',multi-robot collaborative operation,and safety.The typical applications of composite robots in aviation intelligent manufacturing such as automatic drilling and connection of aircraft,aircraft surface spraying and finishing,parts handling,aircraft measurement,and inspection are presented.The development trends such as standardization of composite robots,integration of‘5G+cloud computing+AI',and fusion of intelligent sensors are proposed.
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 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.
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.
文摘An intelligent manufacturing system is a composite intelligent system comprising humans,cyber systems,and physical systems with the aim of achieving specific manufacturing goals at an optimized level.This kind of intelligent system is called a human-cyber-physical system(HCPS).In terms of technology,HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing.It can be concluded that the essence of intelligent manufacturing is to design,construct,and apply HCPSs in various cases and at different levels.With advances in information technology,intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing,and is evolving toward new-generation intelligent manufacturing(NGIM).NGIM is characterized by the in-depth integration of new-generation artificial intelligence(AI)technology(i.e.,enabling technology)with advanced manufacturing technology(i.e.,root technology);it is the core driving force of the new industrial revolution.In this study,the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs,and the implications,characteristics,technical frame,and key technologies of HCPSs for NGIM are then discussed in depth.Finally,an outlook of the major challenges of HCPSs for NGIM is proposed.
基金This research is supported by the National Natural Science Foundation of China(91646102,L1824039,L1724034,L1624045,and L1524015)the project of China’s Ministry of Education(16JDGC011)+6 种基金the Chinese Academy of Engineering’s consultancy project(2019-ZD-9)the National Science and Technology Major Project(2016ZX04005002)Beijing Natural Science Foundation Project(9182013)the technology projects of the Chinese Academy of Engineering’s China Knowledge Center for Engineering Sciences(CKCEST-2019-2-13,CKCEST-2018-1-13,CKCEST-2017-1-10,and CKCEST-2015-4-2)the UK–China Industry Academia Partnership Programme(UK-CIAPP\260)the Volvo-supported Green Economy and Sustainable Development Projects in the Tsinghua University(20153000181)Tsinghua Initiative Research(2016THZW).
文摘Intelligent technologies are leading to the next wave of industrial revolution in manufacturing.In developed economies,firms are embracing these advanced technologies following a sequential upgrading strategy-from digital manufacturing to smart manufacturing(digital-networked),and then to newgeneration intelligent manufacturing paradigms.However,Chinese firms face a different scenario.On the one hand,they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies;thus,they may not follow an identical upgrading pathway.On the other hand,Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners;thus,the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging,if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies.This study addresses the following question by conducting multiple case studies:Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies?The data sources include semistructured interviews and archival data.This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in nonconsecutive ways.This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics;furthermore,this finding can be extended to other catching-up economies.This paper provides a strategic roadmap as an explanatory guide to manufacturing firms,policymakers,and investors.
文摘Intelligent manufacturing technology has become a major trend in the development of the manufacturing industry around the world,and is being studied and applied by numerous industrially developed countries.For example,the United States has proposed an intelligent manufacturing layout based on the Industrial Internet and the‘‘New Generation of Robots”;Germany has proposed the Industry 4.0 initiative to boost the competitiveness of the manufacturing industry through intelligent manufacturing;and the European Union(EU),Japan,Korea,China,and other large manufacturing countries have put forward corresponding strategies for the development of intelligent manufacturing.Clearly,intelligent manufacturing has become an important direction in the development of the manufacturing industry.
文摘Green and intelligent manufacturing will be the development direction of manufacturing industry because of their features: low pollution on the environment, high effi ciency and automatic production. The rapid development of internet is changing the direction of the manufacturing industry, which will impact the green and intelligent manufacturing. Based on these, the environment and conditions of green and intelligent manufacturing brought by internet is sorted out in this paper; and the new opportunities and challenges of green and intelligent manufacturing in the internet era are analyzed. Then, the path for the realizing green and intelligent manufacturing is studied; and some policy recommendations are put forward to promote the realization of green and intelligent manufacturing.
基金partially supported by a GRF project from RGC of Hong Kong China (City U: 11207714)+2 种基金a SRG grant from City University of Hong Kong China (7004909)a National Basic Research Program of China (2011CB013104)
文摘Estimating the cycle time of each job over event streams in intelligent manufacturing is critical. These streams include many long-lasting events which have certain durations. The temporal relationships among those interval-based events are often complex. Meanwhile, network latencies and machine failures in intelligent manufacturing may cause events to be out-of-order. This topic has rarely been discussed because most existing methods do not consider both interval-based and out-of-order events. In this work, we analyze the preliminaries of event temporal semantics. A tree-plan model of interval-based out-of-order events is proposed. A hybrid solution is correspondingly introduced. Extensive experimental studies demonstrate the efficiency of our approach.