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Technological and Economical Logic for Intelligent Manufacturing

Guo Zhaohui

Strategic Study of CAE 2018, Volume 20, Issue 4,   Pages 97-100 doi: 10.15302/J-SSCAE-2018.04.016

Abstract:

Focusing on the difficulties domestic industrial enterprises are facing

Keywords： smart manufacture     industrial Internet     Industrial 4.0     Cyberspace    

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Study on “Industrial Internet” and “Industrie 4.0”

Yan Jianlin, and Kong Dejing

Strategic Study of CAE 2015, Volume 17, Issue 7,   Pages 141-140

Abstract: “Industrial Internet” from the U.S. and “Industrie 4.0” from Germany should be

Keywords： industrial internet     Industrie 4.0     mode transformation     “Made in China 2025”    

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From total quality management to Quality 4.0: A systematic literature review and future research agenda

Frontiers of Engineering Management 2023, Volume 10, Issue 2,   Pages 191-205 doi: 10.1007/s42524-022-0243-z

Abstract: Quality 4.0 is an emerging concept that has been increasingly appreciated because of the intensificationIt deals with aligning quality management practices with the emergent capabilities of Industry 4.0 toThis article aims to comprehensively review extant studies related to Quality 4.0 to uncover currentThen, the selected articles were analyzed and classified according to four research themes: Quality 4.0concept, Quality 4.0 implementation, quality management in Quality 4.0, and Quality 4.0 model and application

Keywords： quality management     Quality 4.0     Industry 4.0     literature review     predictive quality    

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Intelligent Manufacturing in the Context of Industry 4.0: A Review

Ray Y. Zhong, Xun Xu, Eberhard Klotz, Stephen T. Newman

Engineering 2017, Volume 3, Issue 5,   Pages 616-630 doi: 10.1016/J.ENG.2017.05.015

Abstract:

Our next generation of industry—Industry 4.0—holds the promise of increased flexibilityIntelligent manufacturing plays an important role in Industry 4.0.In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper providesconcepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial

Keywords： Intelligent manufacturing     Industry 4.0     Internet of Things     Manufacturing systems     Cloud manufacturing     Cyber-physical    

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Energy 4.0： Constructing the economic structure， internet technology and smart energy

Gu Weidong

Strategic Study of CAE 2015, Volume 17, Issue 3,   Pages 4-9

Abstract:

The concept of energy 4.0， which adapts to industry 4.0 is proposed in this work.& industry internet is a high efficiency， low cost， sustainable， and regulatory network. energy 4.0

Keywords： energy 4.0； the energy & industry internet； high energy consuming industries； peak shaving    

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Remanufacturing in Industry 4.0

Ming-zhou Liu,Cong-hu Liu,Mao-gen Ge,Yuan Zhang,Qing-hua Zhu

Frontiers of Engineering Management 2016, Volume 3, Issue 2,   Pages 144-146 doi: 10.15302/J-FEM-2016020

Abstract: of human blood circulation system, the authors explore the importance of remanufacturing in Industry 4.0Furthermore, this paper discusses the development direction of remanufacturing engineering in Industry 4.0

Keywords： remanufacturing     Industry 4.0     sustainable development    

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An Industry 4.0 Approach to the 3D Printing of Composite Materials

Bronwyn Fox, Aleksander Subic

Engineering 2019, Volume 5, Issue 4,   Pages 621-623 doi: 10.1016/j.eng.2019.06.003

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Understanding of a New Generation of Intelligent Manufacturing based on RAMI 4.0

Zhao Min

Strategic Study of CAE 2018, Volume 20, Issue 4,   Pages 90-96 doi: 10.15302/J-SSCAE-2018.04.015

Abstract: adopts the method of deconstruction and reconstruction, to analyze the Reference Architecture Model of Industrial4.0 (RAMI 4.0) of Germany, and compared with the general architecture of intelligent manufacturing proposed

Keywords： RAMI 4.0     cyber-physics system (CPS)     basic paradigm     new-generation artificial intelligence     architecture    

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Flexible Resource Scheduling for Software-Defined Cloud Manufacturing with Edge Computing Article

Chen Yang,Fangyin Liao,Shulin Lan,Lihui Wang,Weiming Shen,George Q. Huang

Engineering 2023, Volume 22, Issue 3,   Pages 60-70 doi: 10.1016/j.eng.2021.08.022

Abstract:

This research focuses on the realization of rapid reconfiguration in a cloud manufacturing environment to enable flexible resource scheduling, fulfill the resource potential and respond to various changes. Therefore, this paper first proposes a new cloud and software-defined networking (SDN)-based manufacturing model named software-defined cloud manufacturing (SDCM), which transfers the control logic from automation hard resources to the software. This shift is of significance because the software can function as the “brain” of the manufacturing system and can be easily changed or updated to support fast system reconfiguration, operation, and evolution. Subsequently, edge computing is introduced to complement the cloud with computation and storage capabilities near the end things. Another key issue is to manage the critical network congestion caused by the transmission of a large amount of Internet of Things (IoT) data with different quality of service (QoS) values such as latency. Based on the virtualization and flexible networking ability of the SDCM, we formalize the time-sensitive data traffic control problem of a set of complex manufacturing tasks, considering subtask allocation and data routing path selection. To solve this optimization problem, an approach integrating the genetic algorithm (GA), Dijkstra’s shortest path algorithm, and a queuing algorithm is proposed. Results of experiments show that the proposed method can efficiently prevent network congestion and reduce the total communication latency in the SDCM.

Keywords： Cloud manufacturing     Edge computing     Software-defined networks     Industrial internet of things     Industry4.0    

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Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

Frontiers of Engineering Management 2018, Volume 5, Issue 2,   Pages 202-213 doi: 10.15302/J-FEM-2017024

Abstract: Understanding the holistic relationship between refinery production scheduling (RPS) and the cyber-physical production environment with smart scheduling is a new question posed in the study of process systems engineering. Here, we discuss state-of-the-art RSPs in the crude-oil refining field and present examples that illustrate how smart scheduling can impact operations in the high-performing chemical process industry. We conclude that, more than any traditional off-the-shelf RPS solution available today, flexible and integrative specialized modeling platforms will be increasingly necessary to perform decentralized and collaborative optimizations, since they are the technological alternatives closer to the advanced manufacturing philosophy.

Keywords： cyber-physical systems     optimization     petrochemical industry     scheduling     smart manufacturing    

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Balancing resilience and efficiency in supply chains: Roles of disruptive technologies under Industry 4.0

Frontiers of Engineering Management   Pages 171-176 doi: 10.1007/s42524-022-0247-8

Abstract: In the Industry 4.0 era, disruptive technologies such as big data analytics, blockchain, Internet-of-Things

Keywords： disruptive technologies     supply chain     resilience     efficiency     paradox     balance    

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Framework and case study of cognitive maintenance in Industry 4.0 Special Feature on Industrial Internet

Bao-rui Li, Yi Wang, Guo-hong Dai, Ke-sheng Wang,kesheng.wang@ntnu.no

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 11,   Pages 1493-1504 doi: 10.1631/FITEE.1900193

Abstract: We present a new framework for (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent approaches and intelligent decision-making techniques, which can be used by maintenance professionals who are working with . 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 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.

Keywords： 认知维护；工业4.0；尖端设备；深度学习；绿色监视器；智能制造工厂    

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Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Pai ZHENG, Honghui WANG, Zhiqian SANG, Ray Y. ZHONG, Yongkui LIU, Chao LIU, Khamdi MUBAROK, Shiqiang YU, Xun XU

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 137-150 doi: 10.1007/s11465-018-0499-5

Abstract: and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrialproduction (i.e., Industry 4.0).To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systemsfor Industry 4.0.First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented.

Keywords： Industry 4.0     smart manufacturing systems     Internet of Things     cyber-physical systems     big data analytics    

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Smart Manufacturing and Intelligent Manufacturing: A Comparative Review Review

Baicun Wang, Fei Tao, Xudong Fang, Chao Liu, Yufei Liu, Theodor Freiheit

Engineering 2021, Volume 7, Issue 6,   Pages 738-757 doi: 10.1016/j.eng.2020.07.017

Abstract: provided, which is increasingly important because the trend to merge both terminologies rises in Industry 4.0

Keywords： Smart manufacturing     Intelligent manufacturing     Industry 4.0     Human–cyber–physical system (HCPS)    

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Environmental Information: Systems Paving the Path for Digitally Facilitated Water Management (Water 4.0

Olaf Kolditz, Karsten Rink, Erik Nixdorf, Thomas Fischer, Lars Bilke, Dmitri Naumov, Zhenliang Liao, Tianxiang Yue

Engineering 2019, Volume 5, Issue 5,   Pages 828-832 doi: 10.1016/j.eng.2019.08.002

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Title Author Date Type Operation

Technological and Economical Logic for Intelligent Manufacturing

Guo Zhaohui

Journal Article

Study on “Industrial Internet” and “Industrie 4.0”

Yan Jianlin, and Kong Dejing

Journal Article

From total quality management to Quality 4.0: A systematic literature review and future research agenda

Journal Article

Intelligent Manufacturing in the Context of Industry 4.0: A Review

Ray Y. Zhong, Xun Xu, Eberhard Klotz, Stephen T. Newman

Journal Article

Energy 4.0： Constructing the economic structure， internet technology and smart energy

Gu Weidong

Journal Article

Remanufacturing in Industry 4.0

Ming-zhou Liu,Cong-hu Liu,Mao-gen Ge,Yuan Zhang,Qing-hua Zhu

Journal Article

An Industry 4.0 Approach to the 3D Printing of Composite Materials

Bronwyn Fox, Aleksander Subic

Journal Article

Understanding of a New Generation of Intelligent Manufacturing based on RAMI 4.0

Zhao Min

Journal Article

Flexible Resource Scheduling for Software-Defined Cloud Manufacturing with Edge Computing

Chen Yang,Fangyin Liao,Shulin Lan,Lihui Wang,Weiming Shen,George Q. Huang

Journal Article

Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

Journal Article

Balancing resilience and efficiency in supply chains: Roles of disruptive technologies under Industry 4.0

Journal Article

Framework and case study of cognitive maintenance in Industry 4.0

Bao-rui Li, Yi Wang, Guo-hong Dai, Ke-sheng Wang,kesheng.wang@ntnu.no

Journal Article

Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

Pai ZHENG, Honghui WANG, Zhiqian SANG, Ray Y. ZHONG, Yongkui LIU, Chao LIU, Khamdi MUBAROK, Shiqiang YU, Xun XU

Journal Article

Smart Manufacturing and Intelligent Manufacturing: A Comparative Review

Baicun Wang, Fei Tao, Xudong Fang, Chao Liu, Yufei Liu, Theodor Freiheit

Journal Article

Environmental Information: Systems Paving the Path for Digitally Facilitated Water Management (Water 4.0

Olaf Kolditz, Karsten Rink, Erik Nixdorf, Thomas Fischer, Lars Bilke, Dmitri Naumov, Zhenliang Liao, Tianxiang Yue

Journal Article