Intelligent Manufacturing Systems in COVID‑19 Pandemic and Beyond:Framework and Impact Assessment

Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks.The intelligent manufacturing(IM)systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms.The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network,which mitigates the severity of industrial chain disruption.In this study,we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks.Considering the constraints of the IM resources,we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.

Smart Design and Manufacturing the Welded Q350 Steel Frames via Lifecycle Management Strategy of Digital Twin

Artificial intelligent aided design and manufacturing have been recognized as one kind of robust data-driven and data-intensive technologies in the integrated computational material engi-neering(ICME)era.Motivated by the dramatical developments of the services of China Railway High-speed series for more than a decade,it is essential to reveal the foundations of lifecycle man-agement of those trains under environmental conditions.Here,the smart design and manufacturing of welded Q350 steel frames of CR200J series are introduced,presenting the capability and opportu-nity of ICME in weight reduction and lifecycle management at a cost-effective approach.In order to address the required fatigue life time enduring more than 9×10^(6)km,the response of optimized frames to the static and the dynamic loads are comprehensively investigated.It is highlighted that the maximum residual stress of the optimized welded frame is reduced to 69 MPa from 477 MPa of previous existing one.Based on the measured stress and acceleration from the railways,the fatigue life of modified frame under various loading modes could fulfil the requirements of the lifecycle man-agement.Moreover,our recent developed intelligent quality control strategy of welding process mediated by machine learning is also introduced,envisioning its application in the intelligent weld-ing.

Knowledge expression,numerical modeling and optimization application of ethylene thermal cracking:From the perspective of intelligent manufacturing

Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and intelligence.For ethylene thermal cracking,knowledge expression,numerical modeling and intelligent optimization are key steps for intelligent manufacturing.This paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking;introduces the frameworks,methods and algorithms that have been proposed over the past10 years and discusses the advantages,limitations and applications in industrial practice.An entire set of molecular-level modeling approaches from feedstocks to products,including feedstock molecular reconstruction,reaction-network auto-generation and cracking unit simulation are described.Multilevel control and optimization methods are exhibited,including at the operational,cycle,plant and enterprise level.Relevant software packages are introduced.Finally,an outlook in terms of future directions is presented.

Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

Upgrading Pathways of Intelligent Manufacturing in China:Transitioning across Technological Paradigms

Intelligent technologies are leading to the next wave of industrial revolution in manufacturing.In developed economies,firms are embracing these advanced technologies following a sequential upgrading strategy-from digital manufacturing to smart manufacturing(digital-networked),and then to newgeneration intelligent manufacturing paradigms.However,Chinese firms face a different scenario.On the one hand,they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies;thus,they may not follow an identical upgrading pathway.On the other hand,Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners;thus,the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging,if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies.This study addresses the following question by conducting multiple case studies:Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies?The data sources include semistructured interviews and archival data.This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in nonconsecutive ways.This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics;furthermore,this finding can be extended to other catching-up economies.This paper provides a strategic roadmap as an explanatory guide to manufacturing firms,policymakers,and investors.

From Mind to Products:Towards Social Manufacturing and Service

After reviewing the development of industrial manufacturing, a novel concept called social manufacturing(SM) and service are proposed as an innovative manufacturing solution for the coming personalized customization era. SM can realize a customer's requirements of "from mind to products", and fulfill tangible and intangible needs of a prosumer, i.e., producer and consumer at the same time. It represents a manufacturing trend,and is expected to become popular in more and more industries.First, a comparison between mass customization and SM is given out, and the basis and motivation from social network to SM is analyzed. Then, its basic theories and supporting technologies,like Internet of Things(Io T), social networks, cloud computing,3 D printing, and intelligent systems, are introduced and analyzed,and an SM platform prototype is developed. Finally, three transformation modes towards SM and 3 D printing are suggested for different user cases.

Research on the Application of Intelligent Construction Technology in Hangzhouxi Railway Station

Relying on the construction management of Hangzhouxi Railway Station,this paper analyses the comprehensive application of intelligent construction technology and the establishment of the common data environment(CDE)by using BIM technology.This paper gives the idea that such issues are deeply explored as large-span curved surface structure improvement,steel structure construction monitoring,special-shaped ticket check canopy construction,prefabricated machine room construction,grid construction management,etc.so as to form an intelligent construction management system based on BIM technology.The system has achieved good application results in economic benefits,social benefits and environmental benefits,which can promote the gradual transformation to a more digitalized,networked and intelligent Hangzhouxi Railway Station,and lay a solid foundation for achieving the construction goals of controllable construction period,excellent quality,green and low carbon,etc.

Virtual CIM and Digital Manufacturing

Manufacturing enterprises play an important role in improving the economic environment of a country.Today,the capability to produce high quality products with shorter delivery time and the ability to produce according to the diverse customer requirements has become the characteristics of successful manufacturing industries. Application of intelligent manufacturing systems and Computer integrated manufacturing (CIM) are the most effective methods for overcoming the issues faced by present day manufactures while retaining the employment level and revenue of a country in today’s highly competitive global market. With the developments taking place in CIM and its related technologies,the application of CIM in manufacturing enterprises has become a reality from the dream. This paper highlights the historical developments towards automation and the need for CIM systems. Furthermore,it analyses some new terms such as agile manufacturing,digital manufacturing,agent-based manufacturing and others,which have been emerging recently,and argues all these new technologies are the subsystems of CIM. In addition,this paper provides a new direction in CIM to fulfil the emerging challenges in today’s global market and to satisfy the emerging need of virtual enterprises in the form of Virtual CIM.

AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes

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.

Generative Adversarial Networks Based Digital Twin Channel Modeling for Intelligent Communication Networks

Integration of digital twin(DT)and wireless channel provides new solution of channel modeling and simulation,and can assist to design,optimize and evaluate intelligent wireless communication system and networks.With DT channel modeling,the generated channel data can be closer to realistic channel measurements without requiring a prior channel model,and amount of channel data can be significantly increased.Artificial intelligence(AI)based modeling approach shows outstanding performance to solve such problems.In this work,a channel modeling method based on generative adversarial networks is proposed for DT channel,which can generate identical statistical distribution with measured channel.Model validation is conducted by comparing DT channel characteristics with measurements,and results show that DT channel leads to fairly good agreement with measured channel.Finally,a link-layer simulation is implemented based on DT channel.It is found that the proposed DT channel model can be well used to conduct link-layer simulation and its performance is comparable to using measurement data.The observations and results can facilitate the development of DT channel modeling and provide new thoughts for DT channel applications,as well as improving the performance and reliability of intelligent communication networking.

新质生产力的演化:维度、结构及路径

新质生产力体现为全方位、系统性、持续性的变革过程,其不仅能优化经济基础的应用场景和能力层级,而且能推进产业协同升级和整体跃迁,其发展进程呈现动态性和加速性,可对已有高质量发展范式、路径进行破坏性创新、爆发性升级、动态性更迭。新质生产力是“制度型生产力→干预型生产力→跨越式生产力→信息化生产力→新质生产力”和“结构型生产力→市场型生产力→可持续生产力→信息化生产力→新质生产力”的有机统一。新质生产力是对信息化生产力的继承和发展,是一种更为先进的生产力形态,具有更新颖的数智技术革命背景、更复杂的内在运作机理、更前瞻性的经济系统以及更深邃的演化路径,也更能代表生产力的最新发展趋势。

面向智能制造仿真实验的产线数字孪生建模

针对智能制造领域人才培养中,实践教学存在的成本高、安全保证难等问题,该研究构建了智能制造仿真实验系统。首先,以智能产线为基础、车间信息化平台为桥梁,融合产线数字孪生技术,构建了面向智能制造仿真实验的数字孪生系统框架;其次,对系统中包含的产线物理实体模型、数据采集及车间信息化平台、数字孪生产线的多维度模型及智能制造仿真实验平台展开了详细阐述;最后设计产线生产调度优化实验,验证了该数字孪生仿真实验系统的有效性。

基于数字孪生的模块化生产系统实践教学平台设计与实现

该文将数字孪生技术应用于模块化生产系统(modular production system,MPS)的智能化改造中,构建了基于数字孪生的MPS实践教学平台。依托监控系统和虚实交互等关键技术,增加了MPS数字孪生体的虚拟建模、虚实联调和PLC程序软件在环/硬件在环调试等实训环节;验证了MPS实践教学平台设计方案的可行性;制定了新的教学框架及详细的实训内容和考核方案。最后,将实训内容与大学生竞赛相结合,提高了学生对智能制造、工业生产的认知能力和实践动手能力。

基于区块链的城市智能交通网络均衡分配方法

为了提高城市智能交通网络的应用效率,有效分配网络中存在的资源,同时保证网络资源分配的均衡度。因此,提出区块链技术下城市智能交通网络均衡分配方法。通过建立城市智能交通网络模型,分析用户在交通网络中的资源需求。根据用户的需求,采用区块链技术分配网络中的资源,通过引入椭圆曲线数字签名算法,对需求和资源的发布信息加密处理,并根据资源需求与资源供应之间的匹配,完成城市智能交通网络资源的均衡分配。实验结果表明,所提方法的用户吞吐率高,且Jain公平指数在0.8以上,表明所提方法的资源分配合理性高。

数字孪生在制造业中实现的关键技术及典型应用综述

数字孪生技术是实现智能制造和工业数字化转型的关键技术,受到学术界和产业界的广泛关注和研究。近十年来,随着数据采集技术、计算机性能和相关智能算法的迅速发展,数字孪生技术的研究及应用取得了巨大进展。针对数字孪生技术应用领域的多样性和对象层级的复杂性,本文回顾了数字孪生基本概念和模型的发展历程,综述了数字孪生技术在制造业应用的关键技术及其发展成果。在此基础上,阐述了数字孪生技术在制造业三个层级的应用现状以及数字孪生赋能智能制造的新范式。最后,展望了制造业数字孪生技术未来发展趋势,为后续研究提供参考。

机械设计与低温锂电池全流程数字化智能制造的联系及应用

随着现代制造技术、信息技术和数字化技术的飞速发展,低温锂电池生产迎来了技术升级。对此本文综述了机械设计与低温锂电池数字化智能制造的联系以及技术优化进展。首先分析了低温锂电池产业数字化、智能化的发展流程,包括低温锂电池数字化制造和二阶段的智能化制造;然后重点探讨了机械设计为低温锂电池数字化智能制造产业带来的优化变革。从产业发展角度来看,与机械设计技术深度融合,可以从多个方面优化现有的低温锂电池数字化智能制造技术,对后者的产业结构调整和技术升级具有重要的指导作用。

基于数字孪生和深度强化学习的矿井超前液压支架自适应抗冲支护方法

受深部开采冲击地压等地质灾害扰动的影响,存在矿井超前支护系统自感知能力差、智能抗冲自适应能力弱、缺乏决策控制能力等问题。针对上述问题,提出了一种基于数字孪生和深度强化学习的矿井超前液压支架自适应抗冲支护方法。通过多源传感器感知巷道环境和超前液压支架支护状态,在虚拟世界中创建物理实体的数字孪生模型,其中物理模型精确展现超前液压支架的结构特征和细节,控制模型实现超前液压支架的自适应控制,机理模型实现对超前液压支架自适应支护的逻辑描述和机理解释,数据模型存储超前液压支架实体运行数据和孪生数据,仿真模型完成超前液压支架立柱仿真以实现超前液压支架与数字孪生模型虚实交互。根据基于深度Q网络(DQN)的超前液压支架自适应抗冲决策算法,对仿真环境中巷道抗冲支护进行智能决策,并依据决策结果对物理实体和数字孪生模型下达调控指令,实现超前液压支架智能控制。实验结果表明:立柱位移与压力变化一致,说明超前液压支架立柱仿真模型设计合理,从而验证了数字孪生模型的准确性;基于DQN的矿井超前液压支架自适应抗冲决策算法可通过调节液压支架控制器PID参数,自适应调控立柱压力,提升巷道安全等级,实现超前液压支架自适应抗冲支护。

高性能液压缸数智化设计与制造平台的构建与应用

高性能液压缸的生产工艺柔性大,加工周期长,其生产属于典型的非标、单件小批量离散型制造模式,在设计和生产中难以优化和控制。针对液压缸生产企业在使用数字化设计和流程管控软件时软件集成度低和耦合度高的问题,设计了一种高性能液压缸数智化设计与制造平台。通过可重构中间件技术,该平台集成了AutoCAD、SolidWorks等软件接口,并在融合神经网络算法和多目标优化技术的同时,构建了图库、工时预测、柔性工艺规划等数字化设计和生产管控模块。该数智化设计与制造平台可以实现设计与制造过程的全生命周期管控,为制造企业实现数智化转型提供有力支撑。

数字化创新、企业边界重塑与智能制造企业高质量发展——来自专利文本信息机器学习的经验证据

信息进行学习,进一步将数字化创新专利划分为设计重组和使用重组两类,以考察二者对智能制造企业高质量发展的影响及作用机制。结果表明:设计重组和使用重组能够显著促进智能制造企业高质量发展,且使用重组的影响效应更显著。在作用机制方面,数字化创新可以通过缩小企业纵向边界和扩大企业横向边界促进智能制造企业高质量发展。进一步分析发现,对处于技术快速变化行业和高市场化水平区域的智能制造企业而言,数字化创新的经济效应更为显著。结论可为智能制造企业数字化创新提供启示,对进一步推动我国制造企业高质量发展具有重要意义。

活动理论视角下高校数字劳动教育的优化路径研究

数字化智能制造产业的不断升级发展,意味着未来生产劳动中将会出现越来越多的数字化、智能化、虚拟化数字劳动,但这并未引发研究者对数字劳动教育的广泛关注,导致鲜有研究从全局视角探究数字劳动教育的优化路径,而活动理论的引入为此研究提供了可能。基于此,文章首先阐述数字劳动、数字劳动教育与数字化劳动教育的相关理论,梳理数字劳动教育在高校层面的实践情况;然后,文章基于全国高校劳动教育实施推进情况的研究成果,分析了80所高校的劳动教育实施方案相关数据,透视高校数字劳动教育的发展问题;最后,文章基于活动理论与数字劳动人才培养机制的耦合关系,提出了高校数字劳动教育的优化路径,即形成面向数字资源创生的育人平台、建立面向个性教育指导的育人规制、构成面向师资群体演进的育人主体、实现面向教育价值形塑的育人生态,以期为教育数字化转型发展与数字劳动教育育人实践提供参考。