Search | Engineering

订阅投稿

首页工程期刊工程焦点工程成就工程前沿关于我们 English

资源类型

期刊论文 761

年份

2024 2

2023 74

2022 74

2021 63

2020 80

2019 57

2018 67

2017 65

2016 37

2015 54

2014 13

2013 12

2012 10

2011 6

2010 11

2009 13

2008 16

2007 18

2006 14

2005 14

展开︾

关键词

智能制造 31

增材制造 29

制造业 15

新一代智能制造 10

3D打印 8

制造强国 8

人工智能 7

开放的复杂巨系统 7

智慧城市 6

绿色制造 5

4D打印 4

中国制造 4

互联网 4

复杂系统 4

质量 4

遗传算法 4

不确定性 3

发展战略 3

工业4.0 3

展开︾

检索范围：

排序：展示方式：

Exploring self-organization and self-adaption for smart manufacturing complex networks

《工程管理前沿（英文）》 2023年第10卷第2期页码 206-222 doi: 10.1007/s42524-022-0225-1

摘要： Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber–physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.

关键词： cyber–physical systems Industrial Internet of Things smart manufacturing complex networks self-organization and self-adaption analytical target cascading collaborative optimization

HTML PDF 收藏

Training for smart manufacturing using a mobile robot-based production line

Shuting WANG, Liquan JIANG, Jie MENG, Yuanlong XIE, Han DING

《机械工程前沿（英文）》 2021年第16卷第2期页码 249-270 doi: 10.1007/s11465-020-0625-z

摘要： Practice experimentation that integrates the manufacturing processes and cutting-edge technologies of smart manufacturing (SM) is essential for future academic and applied engineering personnel. The broadening efficacy of hands-on experience in SM engineering education has been manifested. In this regard, a reference practical system is proposed in this study for hands-on training in SM crucial advancements. The system constructs a mobile robot-based production line (MRPL) to increase participants’ interest in theoretical learning and professional skills. The MRPL-based reference system includes the comprehensive principles and processes involved in modern SM factories from warehousing to logistics, processing, and testing. With key features of modularity, integrability, customizability, and open architecture, this system has a threefold objective. First, it is an interdisciplinary subject that enables students to translate classroom learning into authentic practices, thus facilitating knowledge synthesis and training involvements. Second, it offers effective support to cultivate the attributions and behavioral competencies of SM talents, such as perseverance, adaptability, and cooperation. Third, it promotes students’ capacities for critical thinking and problem solving so that they can deal with the difficulties that physical systems have and motivates them to pursue careers with new syllabi, functions, and process technologies. The received positive evaluations and assessments confirm that this MRPL-based reference system is beneficial for modern SM talent training in higher engineering education.

关键词： smart manufacturing hands-on experience engineering education mobile robot-based production line

HTML PDF 收藏

Evaluation of the situational awareness eﬀects for smart distribution networks under the novel

Leijiao GE, Yuanliang LI, Suxuan LI, Jiebei ZHU, Jun YAN

《能源前沿（英文）》 2021年第15卷第1期页码 143-158 doi: 10.1007/s11708-020-0703-2

摘要： As a key application of smart grid technologies, the smart distribution network (SDN) is expected to have a high diversity of equipment and complexity of operation patterns. Situational awareness (SA), which aims to provide a critical visibility of the SDN, will enable a significant assurance for stable SDN operations. However, the lack of systematic evaluation through the three stages of perception, comprehensive, and prediction may prevent the SA technique from effectively achieving the performance necessary to monitor and respond to events in SDN. To analyze the feasibility and effectiveness of the SA technique for the SDN, a comprehensive evaluation framework with specific performance indicators and systematic weighting methods is proposed in this paper. Besides, to implement the indicator framework while addressing the key issues of human expert scoring ambiguity and the lack of data in specific SDN areas, an improved interval-based analytic hierarchy process-based subjective weighting and a multi-objective programming method-based objective weighting are developed to evaluate the SDN SA performance. In addition, a case study in a real distribution network of Tianjin China is conducted whose outcomes verify the practicality and effectiveness of the proposed SA technique for SDN operating security.

关键词： distribution networks operation and maintenance expert systems

HTML PDF 收藏

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： “Smart manufacturing” (SM)和“Intelligent manufacturing” (IM)这两个名词已被科研人员和制造业从业者作为专用术语广泛使用

关键词：智能制造工业4.0 人–信息–物理系统

HTML PDF 收藏

流程工业智能优化制造

柴天佑,丁进良

《中国工程科学》 2018年第20卷第4期页码 51-58 doi: 10.15302/J-SSCAE-2018.04.009

摘要：

本文在分析流程工业的特点、运行现状和国际智能制造发展状况的基础上，提出了我国流程工业智能制造的新模式——智能优化制造。在分析流程企业采用的由企业资源计划、制造执行系统、过程控制系统组成的三层架构和控制与管理信息化系统的发展状况基础上，提出了未来流程企业应采用的智能优化制造的架构和系统愿景功能，分析了实现愿景功能所需要攻克的关键共性技术和对自动化、计算机和通信、数据科学挑战的科学问题，提出了突出流程工业战略地位、实施战略规划与顶层设计等发展流程工业智能优化制造的建议。

关键词：流程工业智能优化制造发展愿景科学挑战

HTML PDF 收藏

流程工业智能优化制造的基础理论与关键技术

钱锋, 钟伟民, 杜文莉

《工程（英文）》 2017年第3卷第2期页码 154-160 doi: 10.1016/J.ENG.2017.02.011

摘要：

本文围绕流程工业转型升级的重大需求，剖析了当前流程工业在经营决策层面、生产运行层面、能效安环层面和信息集成层面存在的主要问题，提出了利用现代信息技术从生产、管理以及营销全过程优化出发，推进以高效化、绿色化和智能化制造为目标的流程工业智能优化制造的愿景目标。围绕制造过程从装备智能化到制造流程、操作模式、供应链管理等自适应智能优化，以需求驱动、应用导向为主，提出了当前亟须研究的核心工程科学问题，即：①生产与经营全过程信息智能感知与集成；②知识驱动的生产过程计划调度与管理决策；③人机物自然交互的生产过程全流程协同控制与优化；④全生命周期安全环境足迹监控与风险溯源分析及控制。并围绕核心科学问题进一步提出了拟突破的流程工业智能优化制造的基础理论与关键技术。

关键词：流程工业智能优化制造绿色制造高端制造最优性评价

HTML PDF 收藏

炼油和石化行业的智能制造

袁志宏, 覃伟中, 赵劲松

《工程（英文）》 2017年第3卷第2期页码 179-182 doi: 10.1016/J.ENG.2017.02.012

摘要：

智能制造将把炼油及石化行业转化成为一个相互关联的、信息驱动的行业链。通过应用实时和高位值支持系统，智能制造能够实现协调运作、绩效导向的制造企业，该企业可迅速回应客户需求，并且将能源和材料的消耗最小化。同时，智能制造还能从根本上改善企业的可持续发展能力、生产力、创新力和经济竞争力。本文展示了石化行业内称为“智能制造”的几个应用案例，如由大数据驱动的催化裂化装置故障检测、对炼油厂现场的规划和调度进行优化等。智能制造在化工和石化领域进一步发展中的关键科技因素和挑战已经明确。

关键词：智能制造石油化工数据/ 信息驱动环境

HTML PDF 收藏

流程工业智能制造的未来

钱峰

《工程（英文）》 2023年第22卷第3期页码 20-22 doi: 10.1016/j.eng.2022.04.029

HTML PDF 收藏

英国智能电网概述 Review

Nick Jenkins,Chao Long,Jianzhong Wu

《工程（英文）》 2015年第1卷第4期页码 413-421 doi: 10.15302/J-ENG-2015112

摘要：

本文为英国智能电网发展现状的概述。文中介绍了智能电网发展期间的相关定义、政策和技术驱动因素、激励机制、技术重点和行业发展情况，并特别详细说明了低碳网络基金和电网创新竞赛项目，展示了智能电表的相关部署情况。这些电力投资和智能电表安装将共同打造一个更加可测、可控的自动集成式电网。本文主要关注的是配电网络、受益于改进信息和通信技术的供电商与用户间的实时信息流及互动、有功潮流管理、需求管理和蓄能。从英国智能电网计划中取得的经验将为英国和其他国家未来智能电网的发展提供可贵的指导。

关键词：智能电网电力系统可再生能源低碳网络基金智能电表

HTML PDF 收藏

配方产品的智能流程制造 Perspective

James Litster, Ian David L. Bogle

《工程（英文）》 2019年第5卷第6期页码 1003-1009 doi: 10.1016/j.eng.2019.02.014

摘要：

文中概述了配方产品智能制造的挑战，这些产品通常是多组分、结构化和多相的。这些挑战主要存在于食品、制药、农用和专用化学品、能源储存和含能材料以及消费品行业，并且由快速变化的客户需求以及在某些情况下严格的监管框架所推动。本文论述了智能制造方面的进展，即数字化及使用含有预测模型和求解算法的大型数据集。虽然已经取得了一些进展，但仍然迫切需要对现实问题进行更多基于模型的工具演示，以证明其优势并突出系统性缺陷。

关键词：智能制造配方产品药品建模供应链集成不确定性

HTML PDF 收藏

复杂系统（产品）集成制造工程的技术研究与应用

夏国洪,李伯虎,唐晓青,朱文海,柴旭东

《中国工程科学》 2005年第7卷第9期页码 49-55

摘要：

基于现代集成制造的理念、方法、技术、工具，结合实践，提出并研究了一种能改善复杂产品研发时间（T）、质量（Q）、成本（C）、服务（S）的系统工程——称为“复杂系统（产品）集成制造工程”（简称COSIME）。阐述了它的内涵、系统框架和技术体系，并给出了其中具有特点的6类关键技术的阶段研究成果，包括基于人制管理及有关先进制造模式的复杂产品集成制造系统的经营管理模式；基于项目管理理念的异地企业间并行工程方法与技术；复杂产品虚拟样机工程方法与技术；基于分布仿真技术的复杂产品概念设计与性能评估系统；复杂产品质量控制与管理系统；基于PLM及网络技术的两种复杂产品全生命周期活动集成制造支撑平台等。

关键词：复杂系统（产品）集成制造工程复杂产品虚拟样机工程网格计算人制管理

HTML PDF 收藏

流程工业智能制造展望：过程系统工程师面临的挑战

Lockhart Bogle Ian David

《工程（英文）》 2017年第3卷第2期页码 161-165 doi: 10.1016/J.ENG.2017.02.003

摘要：

本文讨论了流程工业智能制造对过程系统工程(PSE) 研究人员提出的挑战。现有的研究在实现全厂和全站点优化方面已经取得了很大进展，进行基准化测试能够增加说服力。本文进一步讨论了过程系统工程师在开发可用工具和技术时遇到的技术性挑战，包括灵活性和不确定性，响应性和敏捷性，鲁棒性和安全性，混合物性质和功能的预测，以及新的建模和数学范式。利用大数据进行智能化开发来驱动系统灵活性需要面对新的挑战，例如，如何在漫长又复杂的供应链中确保数据的一致性和机密性。建模方面也存在很多挑战，涉及如何对所有的关键技术进行恰当的建模，特别是健康、安全和环境方面，需要在特定地点对微小却关键的量进行准确预测。对环境方面的关注要求我们紧密跟踪所有的分子种类，以便于它们能被最佳地用于创造可持续的解决方案。而源自于新型个性化产品的破坏性商业模式对环境的影响则难以预测。

关键词：智能制造过程系统工程不确定性灵活性优化基于模型的控制

HTML PDF 收藏

智能过程制造中的数据解析与机器学习——大数据时代的最新进展与展望 Perspective

尚超、 Fengqi You

《工程（英文）》 2019年第5卷第6期页码 1010-1016 doi: 10.1016/j.eng.2019.01.019

摘要：

安全、高效、可持续的运行是工业生产过程控制的主要目标。然而，目前的技术严重依赖人为干预，因此在实际应用中体现出明显的局限性。蓬勃发展的大数据时代对流程工业产生了巨大的影响，为实现智能制造提供了前所未有的机遇。这种新的生产方式不仅要求机器能够帮助人类减轻繁重的体力劳动，还要能有效地承担智力劳动，甚至能够实现自主创新。为了实现这一目标，数据分析与机器学习扮演着不可或缺的角色。在本文中，我们回顾了数据分析和机器学习在工业生产过程监控、控制和优化方面的最新进展，着重分析机器学习模型的可解释性和功能性。通过分析实际需求与研究现状之间的差距，为未来的研究方向给出了建议。

关键词：大数据机器学习智能制造过程系统工程

HTML PDF 收藏

流程工业制造系统智能化——人工智能与流程制造深度融合

钱锋

《工程（英文）》 2019年第5卷第6期页码 981-981 doi: 10.1016/j.eng.2019.10.002

HTML PDF 收藏

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