Assortative mating, the tendency for mate selection to occur on the basis of similar traits plays an essential role in understanding the genetic variation on academic achievements and intelligence (IQ), it is also an ...Assortative mating, the tendency for mate selection to occur on the basis of similar traits plays an essential role in understanding the genetic variation on academic achievements and intelligence (IQ), it is also an important mechanism explaining spousal concordance. We used a subset of The Collaborative Study on the Genetics of Alcoholism sample to study the mating patterns in 84 pairs of spouses from Caucasian families with their academic achievements (reading, spelling, arithmetic, vocabulary and comprehension) and IQ (verbal IQ, performance IQ and full scale IQ). Simple correlation analysis showed that 6 of these 8 traits revealed evidence of spousal correlation (P < 0.05). The first principal component (PC1) of husbands explains 73.61% for the variation in the eight variables, which has high loadings from reading, spelling, arithmetic, verbal IQ and full scale IQ while PC1 of wives explains 72.86% for the variation in the eight variables, which has high loadings from reading, spelling, verbal IQ and full scale IQ. There was highly significant positive correlation between spouses by PC1 (P < 0.0001). The new variable PC1 may be important in spousal concordance and mate selection in society and act upon achievements and intelligence levels.展开更多
Although mass customization, which utilizes modularization to simultaneously increase product variety and maintain mass production （MP） efficiency, has become a trend in recent times, there are some limitations to m...Although mass customization, which utilizes modularization to simultaneously increase product variety and maintain mass production （MP） efficiency, has become a trend in recent times, there are some limitations to mass customization. Firstly, customers do not participate wholeheartedly in the design phase. Secondly, potential combinations are predetermined by designers. Thirdly, the concept of mass customization is not necessary to satisfy individual requirements and is not capable of providing personalized services and goods. Industry 4.0 is a collec- tive term for technologies and concepts of value chain organization. Based on the technological concepts of radio frequency identification, cyber-physical system, the Inter- net of things, Internet of service, and data mining, Industry 4.0 will enable novel forms of personalization. Direct customer input to design will enable companies to increasingly produce customized products with shorter cycle-times and lower costs than those associated with standardization and MP. The producer and the customer will share in the new value created. To overcome the gaps between mass customization and mass personalization, this paper presents a framework for mass personalization production based on the concepts of Industry 4.0. Several industrial practices and a lab demonstration show how we can realize mass personalization.展开更多
In the wake of globalization,many modern manufacturing companies in Norway have come under intense pressure caused by increased competition,stricter government regulation,and customer demand for higher value at low co...In the wake of globalization,many modern manufacturing companies in Norway have come under intense pressure caused by increased competition,stricter government regulation,and customer demand for higher value at low cost in a short time.Manufacturing companies need traceability,which means a real-time view into thenproduction processes and operations.Radio frequency identification（RFID） technology enables manufacturing companies to gain instant traceability and visibility because it handles manufactured goods,materials and processes transparently.RFID has become an important driver in manufacturing and supply chain activities.However,there is still a challenge in effectively deploying RFID in manufacturing.This paper describes the importance for Norwegian manufacturing companies to implement RFID technology,and shows how the intelligent and integrated RFID（n-RFID） system,which has been developed in the Knowledge Discovery Laboratory of Norwegian University of Science and Technology,provides instant traceability and visibility into manufacturing processes.It supports the Norwegian manufacturing industries survive and thrive in global competition.The future research work will focus on the field of RFID data mining to support decision-making process in manufacturing.展开更多
Fault diagnosis and prognosis in mechanical systems have been researched and developed in the last few decades at a very rapid rate. However, owing to the high complexity of machine centers, research on improving the ...Fault diagnosis and prognosis in mechanical systems have been researched and developed in the last few decades at a very rapid rate. However, owing to the high complexity of machine centers, research on improving the accuracy and reliability of fault diagnosis and prognosis via data mining remains a prominent issue in this field. This study investigates fault diagnosis and prognosis in machine centers based on data mining approaches to formulate a systematic approach and obtain knowledge for predictive maintenance in Industry 4.0 era. We introduce a system framework based on Industry 4.0 concepts, which includes the process of fault analysis and treatment for predictive maintenance in machine centers. The framework includes five modules： sensor selection and data acquisition module, data preprocessing module, data mining module, decision support module, and maintenance implementation module. Furthermore, a case study is presented to illustrate the application of the data mining methods for fault diagnosis and prognosis in machine centers as an Industry 4.0 scenario.展开更多
Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distanc...Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distance is proposed.The input data required being filtered have been shunt by considering a large number of redundant data existing in the unreliable data for RFID and the redundant data in RFID are the main filtering object with utilizing the filter based on Euclidean distance.The comparison between the results from the method proposed in this paper and previous research shows that it can improve the accuracy of the RFID for unreliable data filtering and largely reduce the redundant reading rate.展开更多
The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero- defec...The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero- defect manufacturing （ZDM） system is necessary in order to increase the reliability and safety of manufacturing systems and reach zero-defect quality of products. One of the major challenges for ZDM is the analysis of massive raw datasets. This type of analysis needs an automated and self-orga- nized decision making system. Data mining （DM） is an effective methodology for discovering interesting knowl- edge within a huge datasets. It plays an important role in developing a ZDM system. The paper presents a general framework of ZDM and explains how to apply DM approaches to manufacture the products with zero-defect. This paper also discusses 3 ongoing projects demonstrating the practice of using DM approaches for reaching the goal of ZDM.展开更多
It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article r...It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article re- ports on research in the backlash error data interpretation and compensation for intelligent predictive maintenance in machine centers based on artificial neural networks （ANNs）. The backlash error, measurement system and prediction methods are analyzed in detail. The result indicates that it is possible to predict and compensate for the backlash error in both forward and backward directions in machine centers.展开更多
In fringe projection profilometry, the nonlinear intensity response caused by the γ effect of a digital projector results in periodic phase error and therefore measurement error. Previous error correction methods are...In fringe projection profilometry, the nonlinear intensity response caused by the γ effect of a digital projector results in periodic phase error and therefore measurement error. Previous error correction methods are largely based on the calibration of single γ value. However, in practice, it is difficult to accurately model the full range of the intensity response with a one-parameter γ function. In this paper, a compensated intensity response curve is generated and fitted with the constrained cubic spline. With the compensated curve, the full range of the nonlinear intensity response can be corrected and the periodic phase errors can be removed significantly. Experimental results on a flat board confirm the average root mean square （RMS） of the phase error which can be reduced to at least 0.0049 rad.展开更多
We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligen...We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligent decision-making tech-niques, which can be used by maintenance professionals who are working with cutting-edge equipment. The systems will provide technical solutions to real-time online maintenance tasks, avoid outages due to equipment failures, and ensure the continuous and healthy operation of equipment and manufacturing assets. The implementation framework of CM consists of four modules, i.e., cyber-physical system, Internet of Things, data mining, and Internet of Services. In the data mining module, fault diagnosis and prediction are realized by deep learning methods. In the case study, the backlash error of cutting-edge machine tools is taken as an example. We use a deep belief network to predict the backlash of the machine tool, so as to predict the possible failure of the machine tool, and realize the strategy of CM. Through the case study, we discuss the significance of implementing CM for cutting-edge equipment, and the framework of CM implementation has been verified. Some CM system applications in manufacturing enterprises are summarized.展开更多
It is difficult to qualitatively evaluate the design effects of product appearance. Electroencephalograph （EEG） and eye-tracking data can serve as reflection of the subcon- scious activities of human beings. The app...It is difficult to qualitatively evaluate the design effects of product appearance. Electroencephalograph （EEG） and eye-tracking data can serve as reflection of the subcon- scious activities of human beings. The application of advanced neuroscience technology in industrial operation management has become a new research hot spot. This study uses EEG equipment and an eye-tracking device to record a subject＇s brain activity and eye-gaze data, and then uses data mining methods to analyze the correlation between the two types of signals. The fuzzy theory is then applied to create a fuzzy comprehensive evaluation model. The neural attributes are used to quantify the factors affected by product appear- ance and evaluation indicators. We use women＇s shirts as research subjects for a case study. The EEG Emotiv device and Tobii mobile eye-tracking glasses are used to record a subject＇s brain activity and eye-gaze data in order to quantify the evaluation factors related to product appearance. This method not only scientifically evaluates the uniqueness of product appearance but also provides an objective reference for improving product appearance design.展开更多
Wind turbines（WTs） are quite expensive pieces of equipment in power industry. Maintenance and repair is a critical activity which also consumes lots of time and effort, hence making it a costly affair. Carefully pla...Wind turbines（WTs） are quite expensive pieces of equipment in power industry. Maintenance and repair is a critical activity which also consumes lots of time and effort, hence making it a costly affair. Carefully planning the maintenance based upon condition of the equipment would make the process reasonable. Mostly the WTs are equipped with some kind of condition monitoring device/system, which provides the information about the device to the central data base i.e., supervisory control and data acquisition（SCADA） data base. These devices/systems make use of data processing techniques/methods in order to detect and predict faults. The information provided by condition monitoring equipments keeps on recoding in the SCADA data base. This paper dwells upon the techniques/methods/algorithms developed, to carry out diagnosis and prognosis of the faults, based upon SCADA data.Subsequently data driven approaching for SCADA data interpretation has been reviewed and an artificial intelligence（AI） based framework for fault diagnosis and prognosis of WTs using SCADA data is proposed.展开更多
The capability automated warehouse in of a company to implement an an optimized way might be nowadays a crucial leverage in order to gain competitive advantage to satisfy the demand. The order picking is a warehouse f...The capability automated warehouse in of a company to implement an an optimized way might be nowadays a crucial leverage in order to gain competitive advantage to satisfy the demand. The order picking is a warehouse function that needs to deal with the retrieval of articles from their storage locations. Merging several single customer orders into one, a picking order can increase efficiency of warehouse operations. The aim of this paper is to define throughout the use of ad-hoc genetic algorithm （GA） how better a warehouse can be set up. The paper deals with order batching, which has a major effect on efficiency of warehouse operations to avoid wastes of resources in terms of processes and to control possibility of unexpected costs in advance.展开更多
Information and communication technology （ICT） has been considered as an enabling tool for having more effective and efficient operations in the management of logistics and supply chains for many years. Various info...Information and communication technology （ICT） has been considered as an enabling tool for having more effective and efficient operations in the management of logistics and supply chains for many years. Various information and communication technologies are used to improve perfor- mance of the logistics and supply chain network, such as ＂data mining＂, ＂radio frequency identification （RFID）＂, ＂machine learning＂, ＂smart transportation＂. While ICT systems are vital components in logistics and supply chains, their successful management rests on intelligent and inte- grated decision making throughout the logistics network. Intelligent decision technologies are applied to collect and store real-time data and then analyze and interpret the data and information of product, inventory, manufacturing and sales to discover useful knowledge for making better operation and management decisions. Advanced simulation and optimization of planning and scheduling systems are also used for improvement of inventory, production, pro-curement, and distribution planning. Intelligent agents can communicate with different partners in the supply chain, assist in collecting information, share product information, negotiate prices, and distribute alerts throughout the logis- tics and supply chains networks.展开更多
This paper provides an overview of models and methods for estimation of lifetime of technical components. Although the focus in this paper is on wind turbine applications, the major content of the paper is of general ...This paper provides an overview of models and methods for estimation of lifetime of technical components. Although the focus in this paper is on wind turbine applications, the major content of the paper is of general nature. Thus, most of the paper content is also valid for lifetime models applied to other technical systems. The models presented and discussed in this paper are classified in different types of model classes. The main classification used in this paper divides the models in the following classes： physical models, stochastic models, data-driven models and artificial intelligence, and combined models. The paper provides an overview of different models for the different classes. Furthermore, advantages and disadvantages of the models are discussed, and the estimation of model parameters is briefly described. Finally, a number of literature examples are given in this paper, providing an overview of applications of different models on wind turbines.展开更多
Manufacturing is and continues to be an essential part of world＇s economy. Manufacturing accounts for around 16 % of Europe＇s GDP. It remains a key driver of R＆D, innovation, productivity growth, job creation. 80 %...Manufacturing is and continues to be an essential part of world＇s economy. Manufacturing accounts for around 16 % of Europe＇s GDP. It remains a key driver of R＆D, innovation, productivity growth, job creation. 80 % of innovations are made by industries. 75 % of EU exports are in manufacturing products. Each job in manufacturing generates two jobs in service. Manufacturing in the middle of 21st century will look very different from today, and will be virtually unrecognizable from that of 30 years ago. Smart factories will be capable of rapidly adapting their physical and intellectual infrastructures to exploit changes in technology as manufacturing becomes faster, more responsive to changing global markets and closer to customers. The main driver is intelligent and advanced manufacturing technologies.展开更多
文摘Assortative mating, the tendency for mate selection to occur on the basis of similar traits plays an essential role in understanding the genetic variation on academic achievements and intelligence (IQ), it is also an important mechanism explaining spousal concordance. We used a subset of The Collaborative Study on the Genetics of Alcoholism sample to study the mating patterns in 84 pairs of spouses from Caucasian families with their academic achievements (reading, spelling, arithmetic, vocabulary and comprehension) and IQ (verbal IQ, performance IQ and full scale IQ). Simple correlation analysis showed that 6 of these 8 traits revealed evidence of spousal correlation (P < 0.05). The first principal component (PC1) of husbands explains 73.61% for the variation in the eight variables, which has high loadings from reading, spelling, arithmetic, verbal IQ and full scale IQ while PC1 of wives explains 72.86% for the variation in the eight variables, which has high loadings from reading, spelling, verbal IQ and full scale IQ. There was highly significant positive correlation between spouses by PC1 (P < 0.0001). The new variable PC1 may be important in spousal concordance and mate selection in society and act upon achievements and intelligence levels.
文摘Although mass customization, which utilizes modularization to simultaneously increase product variety and maintain mass production （MP） efficiency, has become a trend in recent times, there are some limitations to mass customization. Firstly, customers do not participate wholeheartedly in the design phase. Secondly, potential combinations are predetermined by designers. Thirdly, the concept of mass customization is not necessary to satisfy individual requirements and is not capable of providing personalized services and goods. Industry 4.0 is a collec- tive term for technologies and concepts of value chain organization. Based on the technological concepts of radio frequency identification, cyber-physical system, the Inter- net of things, Internet of service, and data mining, Industry 4.0 will enable novel forms of personalization. Direct customer input to design will enable companies to increasingly produce customized products with shorter cycle-times and lower costs than those associated with standardization and MP. The producer and the customer will share in the new value created. To overcome the gaps between mass customization and mass personalization, this paper presents a framework for mass personalization production based on the concepts of Industry 4.0. Several industrial practices and a lab demonstration show how we can realize mass personalization.
文摘In the wake of globalization,many modern manufacturing companies in Norway have come under intense pressure caused by increased competition,stricter government regulation,and customer demand for higher value at low cost in a short time.Manufacturing companies need traceability,which means a real-time view into thenproduction processes and operations.Radio frequency identification（RFID） technology enables manufacturing companies to gain instant traceability and visibility because it handles manufactured goods,materials and processes transparently.RFID has become an important driver in manufacturing and supply chain activities.However,there is still a challenge in effectively deploying RFID in manufacturing.This paper describes the importance for Norwegian manufacturing companies to implement RFID technology,and shows how the intelligent and integrated RFID（n-RFID） system,which has been developed in the Knowledge Discovery Laboratory of Norwegian University of Science and Technology,provides instant traceability and visibility into manufacturing processes.It supports the Norwegian manufacturing industries survive and thrive in global competition.The future research work will focus on the field of RFID data mining to support decision-making process in manufacturing.
文摘Fault diagnosis and prognosis in mechanical systems have been researched and developed in the last few decades at a very rapid rate. However, owing to the high complexity of machine centers, research on improving the accuracy and reliability of fault diagnosis and prognosis via data mining remains a prominent issue in this field. This study investigates fault diagnosis and prognosis in machine centers based on data mining approaches to formulate a systematic approach and obtain knowledge for predictive maintenance in Industry 4.0 era. We introduce a system framework based on Industry 4.0 concepts, which includes the process of fault analysis and treatment for predictive maintenance in machine centers. The framework includes five modules： sensor selection and data acquisition module, data preprocessing module, data mining module, decision support module, and maintenance implementation module. Furthermore, a case study is presented to illustrate the application of the data mining methods for fault diagnosis and prognosis in machine centers as an Industry 4.0 scenario.
基金supported by the foundation of Science and Technology Commission of Shanghai Municipality (Grant No.13521103902)
文摘Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distance is proposed.The input data required being filtered have been shunt by considering a large number of redundant data existing in the unreliable data for RFID and the redundant data in RFID are the main filtering object with utilizing the filter based on Euclidean distance.The comparison between the results from the method proposed in this paper and previous research shows that it can improve the accuracy of the RFID for unreliable data filtering and largely reduce the redundant reading rate.
文摘The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero- defect manufacturing （ZDM） system is necessary in order to increase the reliability and safety of manufacturing systems and reach zero-defect quality of products. One of the major challenges for ZDM is the analysis of massive raw datasets. This type of analysis needs an automated and self-orga- nized decision making system. Data mining （DM） is an effective methodology for discovering interesting knowl- edge within a huge datasets. It plays an important role in developing a ZDM system. The paper presents a general framework of ZDM and explains how to apply DM approaches to manufacture the products with zero-defect. This paper also discusses 3 ongoing projects demonstrating the practice of using DM approaches for reaching the goal of ZDM.
文摘It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article re- ports on research in the backlash error data interpretation and compensation for intelligent predictive maintenance in machine centers based on artificial neural networks （ANNs）. The backlash error, measurement system and prediction methods are analyzed in detail. The result indicates that it is possible to predict and compensate for the backlash error in both forward and backward directions in machine centers.
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant No. 51175318）, the National High Technology Research and Development Program of China （Grant No. 2012AA040507）, and the Major National Science and Technology Project of China （Grant No.2013ZX04006011-217）. Junzheng Peng is also thankful for the support of the China Schol- arship Council to carry out research at Norwegian University of Science and Technology for one year.
文摘In fringe projection profilometry, the nonlinear intensity response caused by the γ effect of a digital projector results in periodic phase error and therefore measurement error. Previous error correction methods are largely based on the calibration of single γ value. However, in practice, it is difficult to accurately model the full range of the intensity response with a one-parameter γ function. In this paper, a compensated intensity response curve is generated and fitted with the constrained cubic spline. With the compensated curve, the full range of the nonlinear intensity response can be corrected and the periodic phase errors can be removed significantly. Experimental results on a flat board confirm the average root mean square （RMS） of the phase error which can be reduced to at least 0.0049 rad.
文摘We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligent decision-making tech-niques, which can be used by maintenance professionals who are working with cutting-edge equipment. The systems will provide technical solutions to real-time online maintenance tasks, avoid outages due to equipment failures, and ensure the continuous and healthy operation of equipment and manufacturing assets. The implementation framework of CM consists of four modules, i.e., cyber-physical system, Internet of Things, data mining, and Internet of Services. In the data mining module, fault diagnosis and prediction are realized by deep learning methods. In the case study, the backlash error of cutting-edge machine tools is taken as an example. We use a deep belief network to predict the backlash of the machine tool, so as to predict the possible failure of the machine tool, and realize the strategy of CM. Through the case study, we discuss the significance of implementing CM for cutting-edge equipment, and the framework of CM implementation has been verified. Some CM system applications in manufacturing enterprises are summarized.
文摘It is difficult to qualitatively evaluate the design effects of product appearance. Electroencephalograph （EEG） and eye-tracking data can serve as reflection of the subcon- scious activities of human beings. The application of advanced neuroscience technology in industrial operation management has become a new research hot spot. This study uses EEG equipment and an eye-tracking device to record a subject＇s brain activity and eye-gaze data, and then uses data mining methods to analyze the correlation between the two types of signals. The fuzzy theory is then applied to create a fuzzy comprehensive evaluation model. The neural attributes are used to quantify the factors affected by product appear- ance and evaluation indicators. We use women＇s shirts as research subjects for a case study. The EEG Emotiv device and Tobii mobile eye-tracking glasses are used to record a subject＇s brain activity and eye-gaze data in order to quantify the evaluation factors related to product appearance. This method not only scientifically evaluates the uniqueness of product appearance but also provides an objective reference for improving product appearance design.
文摘Wind turbines（WTs） are quite expensive pieces of equipment in power industry. Maintenance and repair is a critical activity which also consumes lots of time and effort, hence making it a costly affair. Carefully planning the maintenance based upon condition of the equipment would make the process reasonable. Mostly the WTs are equipped with some kind of condition monitoring device/system, which provides the information about the device to the central data base i.e., supervisory control and data acquisition（SCADA） data base. These devices/systems make use of data processing techniques/methods in order to detect and predict faults. The information provided by condition monitoring equipments keeps on recoding in the SCADA data base. This paper dwells upon the techniques/methods/algorithms developed, to carry out diagnosis and prognosis of the faults, based upon SCADA data.Subsequently data driven approaching for SCADA data interpretation has been reviewed and an artificial intelligence（AI） based framework for fault diagnosis and prognosis of WTs using SCADA data is proposed.
文摘The capability automated warehouse in of a company to implement an an optimized way might be nowadays a crucial leverage in order to gain competitive advantage to satisfy the demand. The order picking is a warehouse function that needs to deal with the retrieval of articles from their storage locations. Merging several single customer orders into one, a picking order can increase efficiency of warehouse operations. The aim of this paper is to define throughout the use of ad-hoc genetic algorithm （GA） how better a warehouse can be set up. The paper deals with order batching, which has a major effect on efficiency of warehouse operations to avoid wastes of resources in terms of processes and to control possibility of unexpected costs in advance.
文摘Information and communication technology （ICT） has been considered as an enabling tool for having more effective and efficient operations in the management of logistics and supply chains for many years. Various information and communication technologies are used to improve perfor- mance of the logistics and supply chain network, such as ＂data mining＂, ＂radio frequency identification （RFID）＂, ＂machine learning＂, ＂smart transportation＂. While ICT systems are vital components in logistics and supply chains, their successful management rests on intelligent and inte- grated decision making throughout the logistics network. Intelligent decision technologies are applied to collect and store real-time data and then analyze and interpret the data and information of product, inventory, manufacturing and sales to discover useful knowledge for making better operation and management decisions. Advanced simulation and optimization of planning and scheduling systems are also used for improvement of inventory, production, pro-curement, and distribution planning. Intelligent agents can communicate with different partners in the supply chain, assist in collecting information, share product information, negotiate prices, and distribute alerts throughout the logis- tics and supply chains networks.
文摘This paper provides an overview of models and methods for estimation of lifetime of technical components. Although the focus in this paper is on wind turbine applications, the major content of the paper is of general nature. Thus, most of the paper content is also valid for lifetime models applied to other technical systems. The models presented and discussed in this paper are classified in different types of model classes. The main classification used in this paper divides the models in the following classes： physical models, stochastic models, data-driven models and artificial intelligence, and combined models. The paper provides an overview of different models for the different classes. Furthermore, advantages and disadvantages of the models are discussed, and the estimation of model parameters is briefly described. Finally, a number of literature examples are given in this paper, providing an overview of applications of different models on wind turbines.
文摘Manufacturing is and continues to be an essential part of world＇s economy. Manufacturing accounts for around 16 % of Europe＇s GDP. It remains a key driver of R＆D, innovation, productivity growth, job creation. 80 % of innovations are made by industries. 75 % of EU exports are in manufacturing products. Each job in manufacturing generates two jobs in service. Manufacturing in the middle of 21st century will look very different from today, and will be virtually unrecognizable from that of 30 years ago. Smart factories will be capable of rapidly adapting their physical and intellectual infrastructures to exploit changes in technology as manufacturing becomes faster, more responsive to changing global markets and closer to customers. The main driver is intelligent and advanced manufacturing technologies.
