On the Digital Transformation of the Automobile Manufacturing Industry in the Chengdu-Chongqing Economic Circle:Mechanism of Action and Feasible Paths

With a long industrial chain and a powerful ability to drive other industries,the automobile manufacturing industry has a prominent strategic position in the national economy.In recent years,many countries have put on their agenda the digitalization of the automobile manufacturing industry,leading to an connected,autonomous,shared,and electric(also known as CASE)①development trend in the industry.As one of the six major automobile industry clusters in China,the Chengdu-Chongqing economic circle has achieved initial results in the digital transformation of the automobile manufacturing industry.However,the region is still faced with some constraints,such as insufficient digital infrastructure,relatively slow development of new automobile products,insufficient innovation ability of the automobile industry,and complex digital transformation of small and medium-sized automobile enterprises(automobile SMEs).This paper intends to construct a framework for the mechanism of action of the digital transformation in the automobile manufacturing industry,analyze the effects of the digital transformation of the automobile manufacturing industry in the Chengdu-Chongqing economic circle,and propose feasible paths for the digital transformation of the automobile manufacturing industry in the region by drawing on domestic and international experience in this regard.The specific paths include:(a)Smoothing the“dual-core”data chain to facilitate the digital transformation of the automobile manufacturing industry;(b)Developing the new energy vehicle(NEV)industry to upgrade the quality of automobile products;(c)Achieving corner overtaking in the digital transformation of the automobile manufacturing industry with digital technology;(d)Jointly building the automobile industrial park to promote the digital transformation of the industry;(e)Addressing problems facing automobile SMEs in digital transformation via targeted policy tools.

Future Digital Design and Manufacturing: Embracing Industry 4.0 and Beyond

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].

Special Issue on Future Digital Design and Manufacturing:Embracing Industry 4.0 and Beyond-Part Ⅱ

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）.

Cogitation on the digital transformation of the process manufacturing industry triggered by the practices of the PIDAS

Digital transformation is the process of an industry moving to a digital business of continuous growth and improvement with digital technologies.It is an important path for the manufacturing industry to reconstruct and upgrade the existing operation mode to achieve efficiency, effectiveness, and product quality improvement.In this study, we analyze why the successful digital transformation practice is scarcely found in the core business of process manufacturing industries, such as the steel and cement industries.By introducing the development and application of the Process Intelligent Data Application System(PIDAS),which is the digital platform of heavy plates in Baosteel, the concepts, ideas, and development experience of the digital transformation of the process manufacturing are summarized.Moreover, the core issues worthy of attention are pointed out.Finally, a feasible route for the digital transformation of the process manufacturing is proposed.

Comprehensive Survey of the Landscape of Digital Twin Technologies and Their Diverse Applications

The concept of the digital twin,also known colloquially as the DT,is a fundamental principle within Industry 4.0 framework.In recent years,the concept of digital siblings has generated considerable academic and practical interest.However,academia and industry have used a variety of interpretations,and the scientific literature lacks a unified and consistent definition of this term.The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature,beginning with its origins in the aerospace domain and extending to its contemporary interpretations in the manufacturing industry.Notably,this investigationwill focus on the research conducted on Industry 4.0 and smartmanufacturing,elucidating the diverse applications of digital twins in fields including aerospace,intelligentmanufacturing,intelligent transportation,and intelligent cities,among others.

Parallel Manufacturing for Industrial Metaverses:A New Paradigm in Smart Manufacturing

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.

Process Digital Twin and Its Application in Petrochemical Industry

Digital twin (DT) is drawing significant attention both from the academia, industry and government. However, people from different fields have different understandings and cognitions about DT. In addition, most of the DT application scenarios discussed belong to discrete manufacturing and are not suitable for process manufacturing. Petrochemical industry is a typical process manufacturing with multi-scale hierarchical and functional structure in space and time. This contribution focuses on topics on the application of DT in petrochemical industry including: 1) The specific DT definition by process industry. 2) The three key elements and design of chemical DT. 3) Features and application scenarios of chemical DT from the view of model precision, model scale and asset life cycle. 4) The Four P’s maturity framework of chemical DT, and 5) Prospects for the development of chemical DT.

Improve the industrial digital transformation through Industrial Internet platforms

1 Introduction 1.1 Definition and stakeholders of the Industrial Internet The Industrial Internet is a novel network technology system that applies the Internet of Things(IoT)to the manufacturing and industrial sectors.It facilitates the connection of various sensors,devices,systems,factories,and enterprises,enabling the sharing and exchange of data to improve production efficiency,reduce costs,enhance product quality,and enable smart manufacturing.The Industrial Internet serves as a crucial cornerstone and essential support for the Fourth Industrial Revolution,offering specific approaches for industrial digital transformation.Through the comprehensive interconnection of people,machines,and things,the Industrial Internet analyzes various data from intelligent feedback,fostering the development of a new manufacturing and service system.

中国数字经济与制造业绿色发展耦合协调研究

文章基于数字经济与制造业绿色发展的耦合机理,构建评价指标体系,运用熵权法测度了中国30个省份2013—2021年的数字经济发展水平与制造业绿色发展水平,利用耦合协调度模型探讨数字经济与制造业绿色发展的时空演化特征,利用障碍度模型分析耦合协调进程中的障碍因子,并实证分析了两者耦合协调的影响因素。研究发现:中国数字经济与制造业绿色发展存在较强的耦合互动关系,耦合协调度呈上升趋势,但整体水平不高且局部不均衡;数字经济与制造业绿色发展受到经济发展水平、政府参与程度、城镇化发展的正向影响。

数字化转型、平台化变革与企业创新绩效——基于“技术—组织—创新”范式的分析

在数字经济和实体经济深度融合、全球创新竞争加剧的背景下,加快数字化转型和平台化变革,塑造多元互动和整体进化的创新生态系统,是增强制造业企业自主创新能力的重要途径。在传统技术经济范式中引入数字要素和平台理念,构建“技术—组织—创新”理论框架,分析数字化转型促进组织平台化变革进而提升企业创新绩效的作用机制。在理论分析的基础上,基于2014—2021年中国制造业上市公司的面板数据,实证检验了数字化转型、平台化变革与企业创新绩效之间的关系。研究结果表明:数字化转型对企业创新绩效的提升具有普遍的促进作用,并且对数字化水平更高和股权集中度更高的企业效果更显著;数字化转型促进了企业组织的平台化变革,基于数字平台形成创新生态系统进而增强了企业自主创新能力;数字化对企业平台化的推动作用主要通过专业化分工和企业互联互通实现,这是工业互联网平台发挥作用的两个重要维度。推动制造业企业的数字化转型和平台化变革,充分发挥数字平台的创新基础设施作用,能够提升企业创新绩效,推动制造业高质量发展。

全球价值链数字化对中国制造业企业国际分工地位的影响

数字技术发展使全球价值链分工体系向数字化重构并深刻影响中国制造业高质量发展。本文基于K-T数理模型分析开放经济条件下数字中间品投入、出口国内增加值与国际分工地位的相互关系,构建全球价值链数字化与企业国际分工地位的理论分析机制。研究发现:全球价值链数字化通过全要素生产率、贸易成本、产品质量和创新能力这4个渠道提升中国制造业企业国际分工地位;全球价值链数字化对资本密集型企业、一般贸易企业及非国有企业的国际分工地位提升效应较强;全球价值链数字化对知识产权保护较好且研发投入较多地区的企业国际分工地位提升效应较显著。因此,建议从加大国内数字技术研发力度、采用差异化战略引导及加强数字技术知识产权保护等方面激发企业参与全球价值链数字化分工活力,提升企业国际竞争力,促进中国制造业高质量发展。

数字贸易、产业结构升级与制造业高质量发展--基于长三角样本的分析

基于2012-2021年长三角地区的相关数据,构建数字贸易、制造业高质量发展的指标评价体系,运用中介效应模型,对数字贸易作用于产业结构升级、推动长三角地区制造业高质量发展问题进行研究。结果表明,一方面数字贸易对长三角制造业高质量发展具有显著直接的促进效应;另一方面产业结构升级能够发挥部分中介效应,助推数字贸易对长三角制造业高质量发展产生正向影响。研究结论为数字贸易发展对长三角制造业的影响及相关政策制定提供了支撑和参考,对长三角制造业实现高质量发展有着一定的启示作用。

数字经济对制造业技术创新绩效的影响

选取2010—2021年省级数字经济指数以及沪深A股制造业上市企业数据,实证检验数字经济与制造业技术创新绩效的关系。研究发现:数字经济能显著提高制造业技术创新绩效,且该结论在经过增加控制变量、缩尾处理等一系列检验后依然稳健;数字经济能通过产业结构升级,间接提升制造业技术创新绩效。异质性检验结果显示,在地区发展方面,数字经济对东部地区、一线城市内制造业企业技术创新绩效的促进作用更强;在企业性质方面,数字经济对成熟期、国有、高密度人力资本型、资本密集型制造业技术创新绩效的促进作用更大。据此,提出加强数字经济基础建设、推进制造业产业结构数字化升级、实施差异化数字经济发展策略的建议,以充分发挥数字经济的促进效应,提升制造业技术创新绩效。

自由贸易试验区设立对制造业企业韧性的影响机制及其效应研究

制造业是立国之本、兴国之器、强国之基。增强制造业韧性是促进工业高质量发展的重要基石。基于2006—2020年中国沪深两市A股上市企业的面板数据,结合理论分析与实证检验,本文系统研究了自贸试验区设立对制造业企业韧性的影响机制及其效应。研究表明:自贸试验区设立对制造业企业韧性提升存在积极影响。机制分析表明:创新要素集聚在自贸试验区设立对制造业企业韧性影响中发挥了中介作用,其间接效应占总效应的9.62%;数字化转型、三类不同的产业集聚与自贸试验区设立的协同效应均在不同程度上强化了自贸试验区设立对制造业企业韧性的促进作用。异质性分析表明:对于东部地区,自贸试验区设立对制造业企业韧性存在明显的积极影响;随着与自贸试验区距离的增加,自贸试验区对周边城市制造业企业韧性的车头效应会呈现出“先增后减,再增再减,最终趋于0”的波浪式收敛变化趋势;对于初创期制造业企业,自贸试验区设立对其韧性水平有明显提升作用。

“数据要素×”赋能制造业:理论逻辑与实现路径

数据要素在工业制造领域具有很大的应用空间,《“数据要素×”三年行动计划(2024—2026年)》将工业制造作为发挥数据要素乘数效应的重点领域。从理论上看,数据要素在制造业领域的乘数效应发挥,其理论基础是数据化理论、工业互联网理论、数据生态理论、数据驱动决策理论、商业模式创新理论。数据要素赋能制造业,可以从制造业的研发、生产制造与服务能力等流程全面应用数据要素实现,也可以从数据要素为制造业提供模拟、仿真、优化、控制、预测等维度来实现。在政策上,要强化数据文化,推动数据互通、共享、复用;在制造业数据相关的底层技术方面加大研发投入,开发出适用制造业数据开发的通用工具;推动算力、算法、存储等相关配套设施与数据要素协同,支持数据要素相关的数据经纪人、数商、交易服务机构等协同发展,建立健全良好的数据生态;推动建设国家制造业数据中心,完善国家、地方、行业、团体的分级体系,对公共数据、企业数据、个人数据形成区别化的分级分类制度;强化制造业数据的安全保护标准,引导、推动行业协会等社会组织加强数据安全自律,完善数据安全体系建设。

长三角地区数字经济对高端装备制造业高质量发展的影响研究——基于有调节的中介效应分析

借助数字经济实现高端装备制造业高质量发展是中国式现代化建设的重要议题。本文基于长三角地区面板数据,利用有调节的中介效应模型检验了数字经济对高端装备制造业高质量发展的影响。结果发现:数字经济可以显著促进高端装备制造业高质量发展,稳健性检验后仍然成立;数字经济通过技术创新正向促进高端装备制造业高质量发展,且技术创新发挥部分中介效应;政府支持对技术创新的中介效应发挥正向调节作用;进一步异质性检验发现,数字经济对不同地区、不同细分行业高质量发展的影响存在显著差异。最后,从三个方面提出相关建议:构建全方位的区域协调发展机制,提升融合效能;聚焦重点领域,推动核心技术突破创新;聚焦制度创新,释放政策红利。

数字经济赋能长三角制造业高质量发展——空间溢出与机制识别

基于2011—2021年长三角地区41个城市的面板数据,采用主成分分析法和空间杜宾模型等方法实证检验数字经济对长三角制造业高质量发展的赋能效应及多重路径的综合作用效果。结果表明:长三角地区数字经济不仅能显著赋能本地制造业高质量发展,还对邻近地区制造业高质量发展有显著的促进作用,空间溢出效应占比为79.4%;数字经济赋能制造业高质量发展主要依赖于人力资本和物质资本积累,且人力资本与物质资本呈协同效应,消费能力路径与人力资本、物质资本均呈背离效应。

数字经济促进制造业升级研究

随着信息通信产业的繁荣发展,数字经济已经走入了公众视野,促进数字经济与实体经济交相融合已成为新时代的新方略。以河南省为例,从产业数字化、数字产业化的角度厘清了数字经济赋能制造业升级的作用机制,并借助河南省地级市面板数据探析数字经济的影响效应。研究结果表明,数字经济对制造业升级影响显著,尤其随着数字化程度提升,正向效应进一步增强;市场活力、技术创新的调节效应显著,在活力市场和创新环境下推动制造业升级更有效。这一结果在豫北、豫中和豫南地区影响相近,无明显差异。据此,应健全数字化创新支持政策,加强数字知识产权保护,降低数字企业市场准入标准,促进制造业更好地利用“数字红利”实现转型升级。

数字产业与制造业协同集聚对企业绿色创新的影响研究

基于马歇尔集聚经济理论,依据中国工业企业数据和城市面板数据,运用固定效应模型,考量数字产业与制造业协同集聚对企业绿色创新的影响。结果显示,数字产业与制造业协同集聚通过人力资本外部性、知识溢出效应机制促进企业绿色创新,但规模经济效应机制不成立,且该结果在更换核心变量指标、考虑极端值、替换固定效应及内生性问题后依然稳健。鉴于此,应因地施策,加快推动区域内数字产业与制造业协同集聚,提升软环境建设水平,促进企业绿色化发展。

数字经济对生产性服务业和制造业融合发展的影响研究

数字经济对促进生产性服务业与制造业的融合具有重要意义,基于2011-2020年中国31个省份的面板数据,通过运用固定效应模型、中介效应模型和面板门槛模型等进行实证检验,探索数字经济对生产性服务业与制造业融合的影响机制。研究发现:①数字经济能够显著促进生产性服务业与制造业融合,经过稳健性检验之后结论仍成立;②数字经济随着生产性服务业和制造业的发展水平的提高对“两业”融合程度的促进更为显著;③数字经济通过技术引进和自主研发正向促进“两业”融合;④数字经济发展对“两业”融合度的促进作用呈现出“边际效应”递增的非线性特征;⑤不同区域间数字经济发展对“两业”融合程度的影响存在差异,东部地区在数字经济促进“两业”融合度上领先于中部和西部地区。