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Remanufacturing in Industry 4.0

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

《工程管理前沿（英文）》 2016年第3卷第2期页码 144-146 doi: 10.15302/J-FEM-2016020

摘要： Using the theory of human blood circulation system, the authors explore the importance of remanufacturing in Industry 4.0. In this paper, they draw analogies between smart factory and human heart, between smart products and blood, and, between product function and nutrition and oxygen in the blood. Remanufacturing is analogous to the ingestion of oxygen and nutrition in lesser circulation or systemic circulation. Remanufacturing well supports recycling production, which is significant in realizing intelligent industry. Furthermore, this paper discusses the development direction of remanufacturing engineering in Industry 4.0 ages.

关键词： remanufacturing Industry 4.0 sustainable development

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

《工程管理前沿（英文）》 doi: 10.1007/s42524-022-0243-z

摘要： Quality 4.0 is an emerging concept that has been increasingly appreciated because of the intensification of competition, continually changing customer requirements and technological evolution. It deals with aligning quality management practices with the emergent capabilities of Industry 4.0 to improve cost, time, and efficiency and increase product quality. This article aims to comprehensively review extant studies related to Quality 4.0 to uncover current research trends, distil key research topics, and identify areas for future research. Thus, 46 journal articles extracted from the Scopus database from 2017 to 2022 were collected and reviewed. A descriptive analysis was first performed according to the year-wise publication, sources of publication, and research methods. Then, the selected articles were analyzed and classified according to four research themes: Quality 4.0 concept, Quality 4.0 implementation, quality management in Quality 4.0, and Quality 4.0 model and application. By extracting the literature review findings, we identify the Quality 4.0 definitions and features, develop the quality curve theory, and highlight future research opportunities. This study supports practitioners, managers, and academicians in effectively recognizing and applying Quality 4.0 to enhance customer satisfaction, achieve innovation enterprise efficiency, and increase organizational competitiveness in the era of Industry 4.0.

关键词： quality management Quality 4.0 Industry 4.0 literature review predictive quality

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对工业4.0背景下的智能制造的回顾

钟润阳, 徐旬, Eberhard Klotz, Stephen T. Newman

《工程（英文）》 2017年第3卷第5期页码 616-630 doi: 10.1016/J.ENG.2017.05.015

摘要：

作为新一代工业模式的工业4.0旨在提升生产灵活性，也将继续提高企业生产效率，保证更高的产品质量以及培养承担大规模定制的能力。在工业4.0模式中，智能制造发挥着重要的作用。典型的资源被转换成智能实体，以便它们能够在智能环境中感知、行动和行为。为了能充分理解在在工业4.0背景下的智能制造，本文对智能制造、物联网（IoT）支持制造和云制造等相关课题进行了综合评述，在我们已有的分析基础上对其中的相似之处和不同点进行了重点探讨。

关键词：智能制造工业4.0 物联网制造系统物理信息系统

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工业4.0复合材料3D打印方法

Bronwyn Fox, Aleksander Subic

《工程（英文）》 2019年第5卷第4期页码 621-623 doi: 10.1016/j.eng.2019.06.003

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Refinery production scheduling toward Industry 4.0

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

《工程管理前沿（英文）》 2018年第5卷第2期页码 202-213 doi: 10.15302/J-FEM-2017024

摘要： 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.

关键词： cyber-physical systems optimization petrochemical industry scheduling smart manufacturing

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能源4.0：重塑经济结构——互联网技术与智慧能源

顾为东

《中国工程科学》 2015年第17卷第3期页码 4-9

摘要：

本文根据几十年系统研究，提出与工业4.0相适应的能源4.0概念，其特征是通过互联网与电网，将太阳能、风能、化石能源、核能等供电侧与电解铝、氯碱、大规模海水淡化、制氢、煤炭清洁化、煤化工、冶金等高耗能产业用电侧

关键词：能源4.0；产业能源互联网；高耗能产业；调峰

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Balancing resilience and efficiency in supply chains: Roles of disruptive technologies under Industry4.0

《工程管理前沿（英文）》页码 171-176 doi: 10.1007/s42524-022-0247-8

摘要： In the Industry 4.0 era, disruptive technologies such as big data analytics, blockchain, Internet-of-Things, and additive manufacturing have become major forces driving supply chain transformation. Under such circumstances, particular attention should be attached to balancing resilience and efficiency of the supply chain, especially in the presence of more turbulence. In this study, we first summarize the conflicts between supply chain efficiency and supply chain resilience regarding practices and objectives. Then, we discuss the positive effects of disruptive technologies in improving resilience and efficiency. Afterwards, we propose a research agenda that covers both the influence mechanism and trade-off mechanism of these technologies in terms of resilience and efficiency.

关键词： disruptive technologies supply chain resilience efficiency paradox balance

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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

《机械工程前沿（英文）》 2018年第13卷第2期页码 137-150 doi: 10.1007/s11465-018-0499-5

摘要：

Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrial production (i.e., Industry 4.0). The widespread application of CPS in manufacturing environments renders manufacturing systems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.

关键词： Industry 4.0 smart manufacturing systems Internet of Things cyber-physical systems big data analytics framework

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Atomic and close-to-atomic scale manufacturing—A trend in manufacturing development

Fengzhou FANG

《机械工程前沿（英文）》 2016年第11卷第4期页码 325-327 doi: 10.1007/s11465-016-0402-1

摘要：

Manufacturing is the foundation of a nation’s economy. It is the primary industry to promote economic and social development. To accelerate and upgrade China’s manufacturing sector from “precision manufacturing” to “high-performance and high-quality manufacturing”, a new breakthrough should be found in terms of achieving a “leap-frog development”. Unlike conventional manufacturing, the fundamental theory of “Manufacturing 3.0” is beyond the scope of conventional theory; rather, it is based on new principles and theories at the atomic and/or close-to-atomic scale. Obtaining a dominant role at the international level is a strategic move for China’s progress.

关键词： atomic manufacturing Manufacturing 3.0 Manufacturing 2025 Industry 4.0

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智能制造——比较性综述与研究进展 Review

王柏村, 陶飞, 方续东, 刘超, 刘宇飞, Theodor Freiheit

《工程（英文）》 2021年第7卷第6期页码 738-757 doi: 10.1016/j.eng.2020.07.017

摘要：随着工业4.0的发展，人工智能迅速地应用在现代制造业与人-信息-物理系统，SM与IM这两个概念有合二为一的发展趋势，因此深入理解SM和IM变得越来越重要，本研究将为此提供支撑。

关键词：智能制造工业4.0 人–信息–物理系统

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工业4.0中认知维护框架与案例研究 Special Feature on Industrial Internet

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

《信息与电子工程前沿（英文）》 2019年第20卷第11期页码 1493-1504 doi: 10.1631/FITEE.1900193

摘要：提出一种基于信息物理系统和先进人工智能技术的认知维护（CM）框架。CM系统架构集成了智能深度学习方法和智能决策技术，可服务于尖端设备的专业维护人员。该系统将为实时在线维护任务提供技术解决方案，避免因设备故障导致的停机，确保设备和制造资产的持续健康运行。CM实现框架由信息物理系统、物联网、数据挖掘和服务互联网4个模块组成。在数据挖掘模块中，采用深度学习方法实现故障诊断和预测。在实例分析中，以尖端机床侧隙误差为例。利用一个深度置信网络预测机床侧隙误差，预测机床可能发生的故障，实现机床的CM策略。通过案例分析，探讨了在尖端设备上实施CM的意义，并验证了CM实施框架。最后总结了CM系统在制造企业的一些应用经验。

关键词：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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Precision glass molding: Toward an optimal fabrication of optical lenses

Liangchi ZHANG,Weidong LIU

《机械工程前沿（英文）》 2017年第12卷第1期页码 3-17 doi: 10.1007/s11465-017-0408-3

摘要：

It is costly and time consuming to use machining processes, such as grinding, polishing and lapping, to produce optical glass lenses with complex features. Precision glass molding (PGM) has thus been developed to realize an efficient manufacture of such optical components in a single step. However, PGM faces various technical challenges. For example, a PGM process must be carried out within the super-cooled region of optical glass above its glass transition temperature, in which the material has an unstable non-equilibrium structure. Within a narrow window of allowable temperature variation, the glass viscosity can change from 10⁵ to 10¹² Pa·s due to the kinetic fragility of the super-cooled liquid. This makes a PGM process sensitive to its molding temperature. In addition, because of the structural relaxation in this temperature window, the atomic structure that governs the material properties is strongly dependent on time and thermal history. Such complexity often leads to residual stresses and shape distortion in a lens molded, causing unexpected changes in density and refractive index. This review will discuss some of the central issues in PGM processes and provide a method based on a manufacturing chain consideration from mold material selection, property and deformation characterization of optical glass to process optimization. The realization of such optimization is a necessary step for the Industry 4.0 of PGM.

关键词： precision glass molding optical lens constitutive modeling optimization manufacturing chain Industry 4.0

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一种新的流程工业企业智能制造准备度评估模型：流程工业智能制造准备度指数（PIMRI） Research Article

赵路军1,2,邵嘉铭2,3,祁雨奇2,褚健2,冯毅萍1

《信息与电子工程前沿（英文）》 2023年第24卷第3期页码 417-432 doi: 10.1631/FITEE.2200080

摘要：近年来，工业4.0的蓬勃发展在世界范围内已经成为了一个新的趋势，它给全球范围内的工业企业既带来了新的机遇也带来了新的挑战。因此，很多制造业企业开始尝试应用新兴的使能技术来推动自身的智能制造转型升级。尽管已经有学者提出了相关工业4.0准备度和成熟度评估的模型，但是目前还缺少流程工业企业的针对性评估模型。本文提出的流程工业智能制造准备度模型用6个层次来描述智能制造的不同发展阶段。

关键词：流程工业；工业4.0；准备度模型；智能制造；准备度指数

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Big data and machine learning: A roadmap towards smart plants

《工程管理前沿（英文）》页码 623-639 doi: 10.1007/s42524-022-0218-0

摘要： Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.

关键词： big data machine learning artificial intelligence smart sensor cyber–physical system Industry 4.0 intelligent system digitalization

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A discussion of objective function representation methods in global optimization

Panos M. PARDALOS, Mahdi FATHI

《工程管理前沿（英文）》 2018年第5卷第4期页码 515-523 doi: 10.15302/J-FEM-2018044

摘要：

Non-convex optimization can be found in several smart manufacturing systems. This paper presents a short review on global optimization (GO) methods. We examine decomposition techniques and classify GO problems on the basis of objective function representation and decomposition techniques. We then explain Kolmogorov’s superposition and its application in GO. Finally, we conclude the paper by exploring the importance of objective function representation in integrated artificial intelligence, optimization, and decision support systems in smart manufacturing and Industry 4.0.

关键词： global optimization decomposition techniques multi-objective DC programming Kolmogorov’s superposition space-filling curve smart manufacturing and Industry 4.0