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Intelligent Manufacturing in the Context of Industry 4.0: A Review 被引量:151
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作者 Ray Y. Zhong Xun Xu +1 位作者 Eberhard Klotz Stephen T. Newman 《Engineering》 SCIE EI 2017年第5期616-630,共15页
Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope wit... Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution. 展开更多
关键词 Intelligent manufacturing industry 4.0 Internet of Things manufacturing systems Cloud manufacturing Cyber-physical system
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Fundamental Theories and Key Technologies for Smart andOptimal Manufacturing in the Process Industry 被引量:26
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作者 Feng Qian Weimin Zhong Wenli Du 《Engineering》 SCIE EI 2017年第2期154-160,共7页
Given the significant requirements for transforming and promoting the process industry, we present themajor limitations of current petrochemical enterprises, including limitations in decision-making, produc-tion opera... Given the significant requirements for transforming and promoting the process industry, we present themajor limitations of current petrochemical enterprises, including limitations in decision-making, produc-tion operation, efficiency and security, information integration, and so forth. To promote a vision of theprocess industry with efficient, green, and smart production, modern information technology should beutilized throughout the entire optimization process for production, management, and marketing. To focuson smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of themanufacturing process, operating mode, and supply chain management, we put forward several key scien-tific problems in engineering in a demand-driven and application-oriented manner, namely:intelligentsensing and integration of all process information, including production and management information; collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; cooperative control and optimization of plant-wide production processes via human-cyber-physical in-teraction; and Q life-cycle assessments for safety and environmental footprint monitoring, in addition totracing analysis and risk control. In order to solve these limitations and core scientific problems, we furtherpresent fundamental theories and key technologies for smart and optimal manufacturing in the processindustry. Although this paper discusses the process industry in China, the conclusions in this paper can beextended to the larocess industry around the world. 展开更多
关键词 Process industry smart and optimal manufacturing Green manufacturing HIGH-END manufacturing OPTIMALITY assessment
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Future Digital Design and Manufacturing: Embracing Industry 4.0 and Beyond 被引量:3
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作者 Sheng-Feng Qin Kai Cheng 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第5期1047-1049,共3页
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
关键词 Digital design Future manufacturing industry 4.0
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ChainApparel: A Trustworthy Blockchain and IoT-Based Traceability Framework for Apparel Industry 4.0
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作者 Muhammad Shakeel Faridi Saqib Ali +2 位作者 Guojun Wang Salman Afsar Awan Muhammad Zafar Iqbal 《Computers, Materials & Continua》 SCIE EI 2023年第11期1837-1854,共18页
Trustworthiness and product traceability are essential factors in the apparel industry 4.0 for establishing successful business relationships among stakeholders such as customers,manufacturers,suppliers,and consumers.... Trustworthiness and product traceability are essential factors in the apparel industry 4.0 for establishing successful business relationships among stakeholders such as customers,manufacturers,suppliers,and consumers.Each stakeholder has implemented different technology-based systems to record and track product transactions.However,these systems work in silos,and there is no intra-system communication,leading to a lack of complete supply chain traceability for all apparel stakeholders.Moreover,apparel stakeholders are reluctant to share their business information with business competitors;thus,they involve third-party auditors to ensure the quality of the final product.Furthermore,the apparel manufacturing industry faces challenges with counterfeit products,making it difficult for consumers to determine the authenticity of the products.Therefore,in this paper,a trustworthy apparel product traceability framework called ChainApparel is developed using the Internet of Things(IoT)and blockchain to address these challenges of authenticity and traceability of apparel products.Specifically,multiple smart contracts are designed and developed for registration,process execution,audit,fault,and product traceability to authorize,validate,and trace every business transaction among the apparel stakeholders.Further,the real-time performance analysis of ChainApparel is carried out regarding transaction throughput and latency by deploying the compute nodes at different geographical locations using Hyperledger Fabric.The results conclude that ChainApparel accomplished significant performance under diverse workloads while ensuring complete traceability along the complex supply chain of the apparel industry.Thus,the ChainApparel framework helps make the apparel product more trustworthy and transparent in the market while safeguarding trust among the industry stakeholders. 展开更多
关键词 Blockchain smart contracts hyperledger fabric Internet of Things TRACEABILITY apparel industry 4.0
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Enhancing Operational Efficiency: Exploring the Integration of SOPs Using Virtual Reality and Smart Glasses Technology in Food Manufacturing
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作者 Somil Nishar 《Intelligent Control and Automation》 2023年第3期37-44,共8页
This paper explores the integration of Standard Operating Procedures (SOPs) using virtual reality and smart glasses technology in food manufacturing. The study employs a thorough methodology, combining observational i... This paper explores the integration of Standard Operating Procedures (SOPs) using virtual reality and smart glasses technology in food manufacturing. The study employs a thorough methodology, combining observational insights to develop a comprehensive SOP. Implementation at different firms resulted in significant improvements, reducing product waste and enhancing overall efficiency. The use of virtual reality further augments SOP adoption. The findings underscore SOPs’ transformative influence, offering a tangible solution to challenges in the food production sector. Recommendations include regular SOP reviews and ongoing training for sustained success. Different firms exemplify SOPs as indispensable tools for operational excellence. 展开更多
关键词 smart manufacturing Standard Operating Procedures 5S Six Sigma Lean manufacturing Augmented Reality smart Glasses Food manufacturing TR Toppers industry 4.0
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工业4.0目标下澳大利亚木材智能建造建筑的实践
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作者 郑生 钟灵芳 《四川建材》 2024年第8期39-41,44,共4页
随着工业4.0(通常是指数字工业技术)的兴起,工业4.0转型能够以全新、高效的方式与机器协同工作,并将工业生产中的诸如设计、建造、施工等内容嵌入到工业物联网、云连接、人工智能和机器学习等技术中。基于这种统一的集成式建造方法即为... 随着工业4.0(通常是指数字工业技术)的兴起,工业4.0转型能够以全新、高效的方式与机器协同工作,并将工业生产中的诸如设计、建造、施工等内容嵌入到工业物联网、云连接、人工智能和机器学习等技术中。基于这种统一的集成式建造方法即为智能建造。梳理了澳大利亚现阶段的木材智能建造建筑实践工作,分析其实践案例、政策支撑、企业实践等,为推动工业4.0下的智能建造战略目标发展提供参考。 展开更多
关键词 工业4.0 智能建造 木材
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Special Issue on Future Digital Design and Manufacturing:Embracing Industry 4.0 and Beyond-Part Ⅱ
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作者 Sheng-Feng Qin Kai Cheng 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第5期1045-1046,共2页
Digital design and manufacturing have been under pinned by digital modeling, simulation, and automation controls for decades. Under the new market requirement of mass customized products and services, the advancements... Digital design and manufacturing have been under pinned by digital modeling, simulation, and automation controls for decades. Under the new market requirement of mass customized products and services, the advancements in artificial intelligence (AI), smart technology, virtual reality (VR), big data, digital twin, robotics and human-centered design are becoming driving forces for the development of future digital design and manufacturing. This special issue focuses on the future digital design and manufacturing especially under the Industry 4.0 framework and beyond. This editorial introduces the papers in this special issue, which linked to the International Workshop on Digital Design and Manufacturing Technologies - Embracing Industry 4.0 and Beyond at Northumbria University in Newcastle, UK, held on 12-13 April 2016. In the Part I of the issue [1], there are 13 papers published in 2016, Vol- ume 29, No 6 of the Chinese Journal of Mechanical Engineering (this journal). 展开更多
关键词 DESIGN In Special Issue on Future Digital Design and manufacturing:Embracing industry 4.0 and Beyond-Part
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“工业4.0”背景下“中国智造”能否赋能劳动力就业
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作者 刘英 《南京财经大学学报》 2024年第1期88-99,共12页
“工业4.0”背景下厘清“中国智造”对劳动力就业的影响,有助于缓解“机器换人”带来的冲击,实现“稳就业”目标。基于2007—2021年A股上市公司数据,以“工业4.0”理念作为准自然实验,利用双重差分法考察“中国智造”能否赋能劳动力就... “工业4.0”背景下厘清“中国智造”对劳动力就业的影响,有助于缓解“机器换人”带来的冲击,实现“稳就业”目标。基于2007—2021年A股上市公司数据,以“工业4.0”理念作为准自然实验,利用双重差分法考察“中国智造”能否赋能劳动力就业。结果显示:(1)“中国智造”显著提高了企业的劳动力雇佣量,通过一系列稳健性检验后结果仍然显著。(2)“中国智造”的就业效应在市场化程度高的地区和人口规模适度的城市、低市场地位和小规模企业、高技能劳动力数量多和薪酬水平高的企业中更突出。(3)“中国智造”通过扩大企业生产规模和缓解融资约束影响劳动力雇佣。(4)“中国智造”可以扩大企业利润,降低企业风险,提高企业生产率,在一定程度上改善企业的经营绩效。研究结论为智能时代企业如何实现“稳就业,促增长”提供价值参考。 展开更多
关键词 “工业4.0 “中国智造” 劳动力就业 A股上市公司 双重差分法
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A Mini-Review and Perspective on Current Best Practice and Emerging Industry 4.0 Methods for Risk Reduction in Advanced Composites Manufacturing
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作者 Bryn Crawford Hamid Khayyam Abbas S. Milani 《Open Journal of Composite Materials》 2021年第2期31-45,共15页
The manufacturing of composite structures is a highly complex task with inevitable risks, particularly associated with aleatoric and epistemic uncertainty of both the materials and processes, as well as the need for &... The manufacturing of composite structures is a highly complex task with inevitable risks, particularly associated with aleatoric and epistemic uncertainty of both the materials and processes, as well as the need for <i>in-situ</i> decision-making to mitigate defects during manufacturing. In the context of aerospace composites production in particular, there is a heightened impetus to address and reduce this risk. Current qualification and substantiation frameworks within the aerospace industry define tractable methods for risk reduction. In parallel, Industry 4.0 is an emerging set of technologies and tools that can enable better decision-making towards risk reduction, supported by data-driven models. It offers new paradigms for manufacturers, by virtue of enabling <i>in-situ</i> decisions for optimizing the process as a dynamic system. However, the static nature of current (pre-Industry 4.0) best-practice frameworks may be viewed as at odds with this emerging novel approach. In addition, many of the predictive tools leveraged in an Industry 4.0 system are black-box in nature, which presents other concerns of tractability, interpretability and ultimately risk. This article presents a perspective on the current state-of-the-art in the aerospace composites industry focusing on risk reduction in the autoclave processing, as an example system, while reviewing current trends and needs towards a Composites 4.0 future. 展开更多
关键词 Advanced Composites manufacturing Quality Control Uncertainty Knowledge Engineering industry 4.0 Machine Learning Limited Data Modeling
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工业4.0背景下数字技术在工业电气自动化系统中的应用
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作者 王勇 《现代工业经济和信息化》 2024年第9期77-80,共4页
随着全球制造业的深度发展,工业4.0代表着新一轮工业革命到来,核心是通过智能化技术与网络化手段实现制造业的高度数字化、网络化、智能化。工业4.0背景下工业电气自动化系统作为制造行业的重要组成部分,正面临前所未有的挑战与机遇。... 随着全球制造业的深度发展,工业4.0代表着新一轮工业革命到来,核心是通过智能化技术与网络化手段实现制造业的高度数字化、网络化、智能化。工业4.0背景下工业电气自动化系统作为制造行业的重要组成部分,正面临前所未有的挑战与机遇。数字技术,如物联网、云计算、大数据、数字孪生等,为工业电气自动化系统创新发展提供了新的动力。基于此,探讨了这些数字技术在工业电气自动化系统中的应用及实践案例,旨在助力工业产业企业实现高效、智能的生产目标。 展开更多
关键词 工业4.0 智能制造 工业物联网 电气自动化系统
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烟草工业4.0预测过程的自适应智能系统研究
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作者 李平 王勇 朱增福 《机电产品开发与创新》 2024年第2期118-120,共3页
当今制造业最大的创新是具有“自我意识”的智能生产系统,具备自我思考和自我维持“能力”。构建这样一个适应性强、可预测的智能系统,可以在机器的生产过程中提供优越能力。智能系统能够将各种技术结合起来,将统计数据和人工智能方法... 当今制造业最大的创新是具有“自我意识”的智能生产系统,具备自我思考和自我维持“能力”。构建这样一个适应性强、可预测的智能系统,可以在机器的生产过程中提供优越能力。智能系统能够将各种技术结合起来,将统计数据和人工智能方法混合在一起。选择卷烟生产是因为它具有高度的串行性,在这种生产中专家系统在这一领域的质量管理中的使用还不够发达,通过研究智能生产可实现直接管理,它可以节省大量费用。本文介绍了一个利用精益生产关键原理的智能系统的应用,在卷烟工业中,我们需要建立一个预测误差的自适应系统,以减少机器故障时间。 展开更多
关键词 烟草工业4.0 智能系统 预测过程 精益生产
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Industry 4.0 Application in Manufacturing for Real-Time Monitoring and Control
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作者 Debasish Mishra Ashok Priyadarshi +4 位作者 Sarthak M Das Sristi Shree Abhinav Gupta Surjya K Pal Debashish Chakravarty 《Journal of Dynamics, Monitoring and Diagnostics》 2022年第3期176-187,共12页
Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing ... Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments. 展开更多
关键词 CLOUD EDGE deep neural networks friction stir welding industry 4.0 internet of things machine learning manufacturing process control process monitoring signal processing
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德国工业4.0产教融合“智慧学习工厂”的构建理念与实施路径
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作者 李一 《职业技术教育》 北大核心 2023年第34期73-79,共7页
为应对工业4.0对职业教育的挑战,德国实施了职业教育4.0战略。在此背景下,德国工业4.0产教融合“智慧学习工厂”应运而生。“智慧学习工厂”以行为主义为指引,以学习者面向工业4.0的能力需求为目标,通过“教育层”“管理层”和“技术层... 为应对工业4.0对职业教育的挑战,德国实施了职业教育4.0战略。在此背景下,德国工业4.0产教融合“智慧学习工厂”应运而生。“智慧学习工厂”以行为主义为指引,以学习者面向工业4.0的能力需求为目标,通过“教育层”“管理层”和“技术层”三个层面的系统化设计,实现了工业4.0技术、智慧生产与教育的深度融合,形成了一套致力于培养智能工业时代高素质人才的有效方法,成为全球智能工业人才培养的经典范例,为我国职业教育产教融合、科教融汇的纵深推进及培养智能工业高素质人才提供了借鉴:明确智能工业人才能力培养目标;以产教融合平台为载体促进智能工业与教育的资源整合;实现智能工业教学实践平台管理与运营的系统化设计;加强智能工业数字技术与教育的系统集成。 展开更多
关键词 工业4.0 职业教育4.0 双元制 产教融合 “智慧学习工厂”
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Smart Manufacturing and Intelligent Manufacturing:A Comparative Review 被引量:32
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作者 Baicun Wang Fei Tao +3 位作者 Xudong Fang Chao Liu Yufei Liu Theodor Freiheit 《Engineering》 SCIE EI 2021年第6期738-757,共20页
The application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the world.However,different terminologies,namely smart manufacturing(SM)and intelligent manufact... The application of intelligence to manufacturing has emerged as a compelling topic for researchers and industries around the world.However,different terminologies,namely smart manufacturing(SM)and intelligent manufacturing(IM),have been applied to what may be broadly characterized as a similar paradigm by some researchers and practitioners.While SM and IM are similar,they are not identical.From an evolutionary perspective,there has been little consideration on whether the definition,thought,connotation,and technical development of the concepts of SM or IM are consistent in the literature.To address this gap,the work performs a qualitative and quantitative investigation of research literature to systematically compare inherent differences of SM and IM and clarify the relationship between SM and IM.A bibliometric analysis of publication sources,annual publication numbers,keyword frequency,and top regions of research and development establishes the scope and trends of the currently presented research.Critical topics discussed include origin,definitions,evolutionary path,and key technologies of SM and IM.The implementation architecture,standards,and national focus are also discussed.In this work,a basis to understand SM and IM is provided,which is increasingly important because the trend to merge both terminologies rises in Industry 4.0 as intelligence is being rapidly applied to modern manufacturing and human–cyber–physical systems. 展开更多
关键词 smart manufacturing Intelligent manufacturing industry 4.0 Human–cyber–physical system(HCPS)
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Parallel Manufacturing for Industrial Metaverses:A New Paradigm in Smart Manufacturing 被引量:11
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作者 Jing Yang Xiaoxing Wang Yandong Zhao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第12期2063-2070,共8页
To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operatio... To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social Systems(CPSSs) and the Internet of Minds(Io M) are regarded as its infrastructures and the "Artificial systems", "Computational experiments"and "Parallel execution"(ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R&D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation(KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations(DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case,especially the unmanned production line named Flex Vega. 展开更多
关键词 Parallel manufacturing Digital Workers CPSS smart manufacturing Industrial Metaverses
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Opportunities and Challenges of Artificial Intelligence for Green Manufacturing in the Process Industry 被引量:15
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作者 Shuai Mao Bing Wang +1 位作者 Yang Tang Feng Qian 《Engineering》 SCIE EI 2019年第6期995-1002,共8页
Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety... Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context. 展开更多
关键词 Process industry smart manufacturing Green manufacturing Artificial intelligence
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Challenges and Requirements for the Application of Industry 4.0:A Special Insight with the Usage of Cyber-Physical System 被引量:5
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作者 Egon Mueller Xiao-Li Chen Ralph Riedel 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第5期1050-1057,共8页
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
关键词 Industrie 4.0 - Internet of Things Cyber-Physical System smart factory Reference architectureIntelligent sensor nets Robot control Synchronousproduction
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Industry 4.0: Architecture and Equipment Revolution 被引量:4
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作者 Ahmed Bashar Fakhri Saleem Latteef Mohammed +4 位作者 Imran Khan Ali Safaa Sadiq Basem Alkazemi Prashant Pillai Bong Jun Choi 《Computers, Materials & Continua》 SCIE EI 2021年第2期1175-1194,共20页
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
关键词 industry 4.0 big data smart manufacturing business model equipment revolution
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AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes 被引量:16
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作者 Mohammadhossein Ghahramani Yan Qiao +2 位作者 Meng Chu Zhou Adrian O’Hagan James Sweeney 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2020年第4期1026-1037,共12页
Smart manufacturing refers to optimization techniques that are implemented in production operations by utilizing advanced analytics approaches. With the widespread increase in deploying industrial internet of things(I... Smart manufacturing refers to optimization techniques that are implemented in production operations by utilizing advanced analytics approaches. With the widespread increase in deploying industrial internet of things(IIOT) sensors in manufacturing processes, there is a progressive need for optimal and effective approaches to data management.Embracing machine learning and artificial intelligence to take advantage of manufacturing data can lead to efficient and intelligent automation. In this paper, we conduct a comprehensive analysis based on evolutionary computing and neural network algorithms toward making semiconductor manufacturing smart.We propose a dynamic algorithm for gaining useful insights about semiconductor manufacturing processes and to address various challenges. We elaborate on the utilization of a genetic algorithm and neural network to propose an intelligent feature selection algorithm. Our objective is to provide an advanced solution for controlling manufacturing processes and to gain perspective on various dimensions that enable manufacturers to access effective predictive technologies. 展开更多
关键词 Artificial intelligence(AI) cyber physical systems feature selection genetic algorithms(GA) industrial internet of things(IIOT) machine learning neural network(NN) smart manufacturing
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Smart manufacturing of nonferrous metallurgical processes:Review and perspectives 被引量:3
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作者 Bei Sun Juntao Dai +2 位作者 Keke Huang Chunhua Yang Weihua Gui 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2022年第4期611-625,共15页
The nonferrous metallurgical(NFM)industry is a cornerstone industry for a nation’s economy.With the development of artificial technologies and high requirements on environment protection,product quality,and productio... The nonferrous metallurgical(NFM)industry is a cornerstone industry for a nation’s economy.With the development of artificial technologies and high requirements on environment protection,product quality,and production efficiency,the importance of applying smart manufacturing technologies to comprehensively percept production states and intelligently optimize process operations is becoming widely recognized by the industry.As a brief summary of the smart and optimal manufacturing of the NFM industry,this paper first reviews the research progress on some key facets of the operational optimization of NFM processes,including production and management,blending optimization,modeling,process monitoring,optimization,and control.Then,it illustrates the perspectives of smart and optimal manufacturing of the NFM industry.Finally,it discusses the major research directions and challenges of smart and optimal manufacturing for the NFM industry.This paper will lay a foundation for the realization of smart and optimal manufacturing in nonferrous metallurgy in the future. 展开更多
关键词 nonferrous metallurgical industry smart and optimal manufacturing online perception intelligent control operational optimiza-tion automation of knowledge-based work
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