Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, ma...Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.展开更多
Virtual manufacturing is one of the key components of Industry 4.0,the fourth industrial revolution,in improving manufacturing processes.Virtual manufacturing enables manufacturers to optimize their production process...Virtual manufacturing is one of the key components of Industry 4.0,the fourth industrial revolution,in improving manufacturing processes.Virtual manufacturing enables manufacturers to optimize their production processes using real-time data from sensors and other connected devices in Industry 4.0.Web-based virtual manufacturing platforms are a critical component of Industry 4.0,enabling manufacturers to design,test,and optimize their processes collaboratively and efficiently.In Industry 4.0,radio frequency identification(RFID)technology is used to provide real-time visibility and control of the supply chain as well as to enable the automation of various manufacturing processes.Big data analytics can be used in conjunction with virtual manufacturing to provide valuable insights and optimize production processes in Industry 4.0.Artificial intelligence(AI)and virtual manufacturing have the potential to enhance the effectiveness,consistency,and adaptability of manufacturing processes,resulting in faster production cycles,better-quality products,and lower prices.Recent developments in the application of virtual manufacturing systems to digital manufacturing platforms from different perspectives,such as the Internet of things,big data analytics,additive manufacturing,autonomous robots,cybersecurity,and RFID technology in Industry 4.0,are discussed in this study to analyze and develop the part manufacturing process in Industry 4.0.The limitations and advantages of virtual manufacturing systems in Industry 4.0 are discussed,and future research projects are also proposed.Thus,productivity in the part manufacturing process can be enhanced by reviewing and analyzing the applications of virtual manufacturing in Industry 4.0.展开更多
Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope wit...Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.展开更多
Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation method...Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV（whole body vibration） test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed.展开更多
Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based ...Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.展开更多
The development of science and technology has led to the era of Industry 4.0.The core concept is the combination of“material and informationization”.In the supply chain and manufacturing process,the“material”of th...The development of science and technology has led to the era of Industry 4.0.The core concept is the combination of“material and informationization”.In the supply chain and manufacturing process,the“material”of the physical entity world is realized by data,identity,intelligence,and information.Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization.The goal is“maximizing production efficiency,minimizing production costs,and maximizing the individual needs of human beings for products and services.”Achieving this goal will surely bring about a major leap in the history of the industry,which will lead to the“Fourth Industrial Revolution.”This paper presents a detailed discussion of industrial big data,strategic roles,architectures,characteristics,and four types of innovative business models that can generate profits for enterprises.The key revolutionary aspect of Industry 4.0 is explained,which is the equipment revolution.Six important attributes of equipment are explained under the Industry 4.0 perspective.展开更多
Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design （CAD）/Computer Aided ...Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design （CAD）/Computer Aided Engineering analysis （CAE）/Computer Aided Manufacturing （CAM）, to modem digital design and manufacturing [1], and cloud manufacturing [2] converging into product lifecycle management （PLM） [3, 4] and Internet-enabled personalized manufacturing [5].展开更多
In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent changes.Event-based fault diagnosis techniques are capable model-based methods for diagnosin...In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent changes.Event-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under diagnosis.Most event-based diagnosis techniques rely on perfect observations of observable events.However,in practice,it is common to miss an observable event due to a problem in sensorreadings or communication/transmission channels.This paper develops a fault diagnosis tool,referred to as diagnoser,which can robustly detect,locate,and isolate occurred faults.The developed diagnoser is resilient against missed observations.A missed observation is detected from its successive sequence of events.Upon detecting a missed observation,the developed diagnoser automatically resets and then,asynchronously resumes the diagnosis process.This is achieved solely based on postreset/activation observations and without interrupting the performance of the system under diagnosis.New concepts of asynchronous detectability and asynchronous diagnosability are introduced.It is shown that if asynchronous detectability and asynchronous diagnosability hold,the proposed diagnoser is capable of diagnosing occurred faults under imperfect observations.The proposed technique is applied to diagnose faults in a manufacturing process.Illustrative examples are provided to explain the details of the proposed algorithm.The result paves the way towards fostering resilient cyber-physical systems in Industry4.0 context.展开更多
In modern scenarios,Industry 4.0 entails invention with various advanced technology,and blockchain is one among them.Blockchains are incorporated to enhance privacy,data transparency aswell as security for both large ...In modern scenarios,Industry 4.0 entails invention with various advanced technology,and blockchain is one among them.Blockchains are incorporated to enhance privacy,data transparency aswell as security for both large and small scale enterprises.Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively.However,because numerous devices and machines are involved,data security and privacy are always concerns.To achieve intelligence in Industry 4.0,blockchain technologies can overcome potential cybersecurity constraints.Nowadays,the blockchain and internet of things(IoT)are gaining more attention because of their favorable outcome in several applications.Though they generate massive data that need to be effectively optimized and in this research work,deep learning-based techniques are employed for this.This paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network(MLSC-DCNN)in order to attain a secure and optimized IoT blockchain for Industry 4.0.Here,an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of DCNN.Finally,the experimentation is carried out for various simulation measures.The comparative analysis is made for Best Tip Selection Method(BTSM),Smart Block-Software Defined Networking(SDN),and the proposed approach.The evaluation results show that the proposed approach attains better performances than BTSM and SDN.展开更多
Business needs to manage such a variety of things inside the firm or outside the business consistently. This factor affects the business in various ways. The factor which affects the business is clients, suppliers, di...Business needs to manage such a variety of things inside the firm or outside the business consistently. This factor affects the business in various ways. The factor which affects the business is clients, suppliers, distributors and so on. These all components are isolated from two sections full-scale environment and miniaturized scale environment. Macro perspective environment components are those external variables which are past the association＇s control. The problem of this study is guaranteeing a supportable evolvement of human presence in its social, ecological, and monetary measurement. So, we have to adapt test in order to outfit toward manageability. As for the method used in this study, it depends on using empirical framework to meet the interest of capital and buyer, in addition to supporting human presence in its social, ecological, monetary measurement. The paper is organised as following sections： first section is the introduction, second section is the literature review, the third section includes the research method, fourth one discusses the analysis, while the conclusion is in the fifth section.展开更多
文摘Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.
文摘Virtual manufacturing is one of the key components of Industry 4.0,the fourth industrial revolution,in improving manufacturing processes.Virtual manufacturing enables manufacturers to optimize their production processes using real-time data from sensors and other connected devices in Industry 4.0.Web-based virtual manufacturing platforms are a critical component of Industry 4.0,enabling manufacturers to design,test,and optimize their processes collaboratively and efficiently.In Industry 4.0,radio frequency identification(RFID)technology is used to provide real-time visibility and control of the supply chain as well as to enable the automation of various manufacturing processes.Big data analytics can be used in conjunction with virtual manufacturing to provide valuable insights and optimize production processes in Industry 4.0.Artificial intelligence(AI)and virtual manufacturing have the potential to enhance the effectiveness,consistency,and adaptability of manufacturing processes,resulting in faster production cycles,better-quality products,and lower prices.Recent developments in the application of virtual manufacturing systems to digital manufacturing platforms from different perspectives,such as the Internet of things,big data analytics,additive manufacturing,autonomous robots,cybersecurity,and RFID technology in Industry 4.0,are discussed in this study to analyze and develop the part manufacturing process in Industry 4.0.The limitations and advantages of virtual manufacturing systems in Industry 4.0 are discussed,and future research projects are also proposed.Thus,productivity in the part manufacturing process can be enhanced by reviewing and analyzing the applications of virtual manufacturing in Industry 4.0.
文摘Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.
基金Supported by National Natural Science Foundation of China(Grant No.51465056)Xinjiang Provincial Natural Science Foundation of China(Grant No.2015211C265)Xinjiang University Ph D Start-up Funds,China
文摘Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV（whole body vibration） test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed.
文摘Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.
基金The authors(Basem Alkazemi,bykazemi@uqu.edu.saAli Safaa Sadiq,ali.sadiq@wlv.ac.uk)would like to thank deanship of scientific research(DSR)at umm Al-Qura University for their partial funding the work(Grant#17-COM-1-01-0007)the National Research Foundation(NRF),Korea(2019R1C1C1007277)funded by the Ministry of Science and ICT(MSIT),Korea.
文摘The development of science and technology has led to the era of Industry 4.0.The core concept is the combination of“material and informationization”.In the supply chain and manufacturing process,the“material”of the physical entity world is realized by data,identity,intelligence,and information.Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization.The goal is“maximizing production efficiency,minimizing production costs,and maximizing the individual needs of human beings for products and services.”Achieving this goal will surely bring about a major leap in the history of the industry,which will lead to the“Fourth Industrial Revolution.”This paper presents a detailed discussion of industrial big data,strategic roles,architectures,characteristics,and four types of innovative business models that can generate profits for enterprises.The key revolutionary aspect of Industry 4.0 is explained,which is the equipment revolution.Six important attributes of equipment are explained under the Industry 4.0 perspective.
文摘Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design （CAD）/Computer Aided Engineering analysis （CAE）/Computer Aided Manufacturing （CAM）, to modem digital design and manufacturing [1], and cloud manufacturing [2] converging into product lifecycle management （PLM） [3, 4] and Internet-enabled personalized manufacturing [5].
基金the National Science Foundation(NSF)(1832110 and 2000320)Air Force Research Laboratory(AFRL)and Office of the Secretary of Defense(OSD)(FA8750-15-2-0116).
文摘In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent changes.Event-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under diagnosis.Most event-based diagnosis techniques rely on perfect observations of observable events.However,in practice,it is common to miss an observable event due to a problem in sensorreadings or communication/transmission channels.This paper develops a fault diagnosis tool,referred to as diagnoser,which can robustly detect,locate,and isolate occurred faults.The developed diagnoser is resilient against missed observations.A missed observation is detected from its successive sequence of events.Upon detecting a missed observation,the developed diagnoser automatically resets and then,asynchronously resumes the diagnosis process.This is achieved solely based on postreset/activation observations and without interrupting the performance of the system under diagnosis.New concepts of asynchronous detectability and asynchronous diagnosability are introduced.It is shown that if asynchronous detectability and asynchronous diagnosability hold,the proposed diagnoser is capable of diagnosing occurred faults under imperfect observations.The proposed technique is applied to diagnose faults in a manufacturing process.Illustrative examples are provided to explain the details of the proposed algorithm.The result paves the way towards fostering resilient cyber-physical systems in Industry4.0 context.
基金The authors extend their appreciation to King Saud University for funding this work through Researchers Supporting Project Number(RSP2022R499)King Saud University,Riyadh,Saudi Arabia.
文摘In modern scenarios,Industry 4.0 entails invention with various advanced technology,and blockchain is one among them.Blockchains are incorporated to enhance privacy,data transparency aswell as security for both large and small scale enterprises.Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively.However,because numerous devices and machines are involved,data security and privacy are always concerns.To achieve intelligence in Industry 4.0,blockchain technologies can overcome potential cybersecurity constraints.Nowadays,the blockchain and internet of things(IoT)are gaining more attention because of their favorable outcome in several applications.Though they generate massive data that need to be effectively optimized and in this research work,deep learning-based techniques are employed for this.This paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network(MLSC-DCNN)in order to attain a secure and optimized IoT blockchain for Industry 4.0.Here,an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of DCNN.Finally,the experimentation is carried out for various simulation measures.The comparative analysis is made for Best Tip Selection Method(BTSM),Smart Block-Software Defined Networking(SDN),and the proposed approach.The evaluation results show that the proposed approach attains better performances than BTSM and SDN.
文摘Business needs to manage such a variety of things inside the firm or outside the business consistently. This factor affects the business in various ways. The factor which affects the business is clients, suppliers, distributors and so on. These all components are isolated from two sections full-scale environment and miniaturized scale environment. Macro perspective environment components are those external variables which are past the association＇s control. The problem of this study is guaranteeing a supportable evolvement of human presence in its social, ecological, and monetary measurement. So, we have to adapt test in order to outfit toward manageability. As for the method used in this study, it depends on using empirical framework to meet the interest of capital and buyer, in addition to supporting human presence in its social, ecological, monetary measurement. The paper is organised as following sections： first section is the introduction, second section is the literature review, the third section includes the research method, fourth one discusses the analysis, while the conclusion is in the fifth section.
