Spatial Patterns and Drivers of Intelligent Manufacturing from a‘Glob-allocal'Perspective:A Study of China's Industrial Robotics

The advancement of the intelligent manufacturing industry(IMI)represents the future direction for the world's manufactur-ing sector,offering a promising avenue to bolster national competitiveness and enhance industrial manufacturing efficiency.In this study,we took the industrial robot industry(IRI)as a case study to elucidate the spatial distribution and interconnections of IMI from a geographical perspective,and the modified diamond model(DM)was used to analyze the influencing factors.Results show that:1)the spatial pattern of IRI with various investment attributes in different industrial chain links is generally similar,centered in the southeast.Key investment areas are in the east and south.The spatial distribution of China's IRI covers a multitude of provinces and obtains differ-ent scales of investment in different countries(regions).2)The spatial correlation between foreign investors and China's provincial-level administrative regions(PARs)forms a network,and the network of foreign-invested enterprises is more stable.Different countries(regions)have distinct location preferences in China,with significant spatial differences in correlation degrees.3)Overall,the interac-tion of these factors shapes the location decisions and correlation patterns of industrial robot enterprises.This study not only contributes to our theoretical knowledge of the industrial spatial structure and industrial economy but also offers valuable references and sugges-tions for national IMI planning and relevant industry investors.

Challenges and Opportunities of China's Refractory Industry

This paper reviews the current development status and achievements of China's refractory industry,summarizing the significant progress made by China's refractory industry over the past 40 years in energy conservation,environmental protection,green and low-carbon development,and intelligent manufacturing.It analyzes the challenges and difficulties faced by China's refractory industry currently,focusing on how the current adjustment cycle in China's steel industry provides new opportunities for China's refractory sector.China's refractory industry must adhere to the path of innovationdriven,intelligent manufacturing,green and low-carbon.We should seek and seize new opportunities for transformation and upgrading,continuously optimize the industrial structure,enhance product and service quality,and carefully balance the domestic and international markets.This approach aims to form a new capacity management mechanism that includes market competition and constraints from both energy consumption and carbon emission,with government supervision and industry self-discipline.

Virtual manufacturing in Industry 4.0:A review

Virtual manufacturing is one of the key components of Industry 4.0,the fourth industrial revolution,in improving manufacturing processes.Virtual manufacturing enables manufacturers to optimize their production processes using real-time data from sensors and other connected devices in Industry 4.0.Web-based virtual manufacturing platforms are a critical component of Industry 4.0,enabling manufacturers to design,test,and optimize their processes collaboratively and efficiently.In Industry 4.0,radio frequency identification(RFID)technology is used to provide real-time visibility and control of the supply chain as well as to enable the automation of various manufacturing processes.Big data analytics can be used in conjunction with virtual manufacturing to provide valuable insights and optimize production processes in Industry 4.0.Artificial intelligence(AI)and virtual manufacturing have the potential to enhance the effectiveness,consistency,and adaptability of manufacturing processes,resulting in faster production cycles,better-quality products,and lower prices.Recent developments in the application of virtual manufacturing systems to digital manufacturing platforms from different perspectives,such as the Internet of things,big data analytics,additive manufacturing,autonomous robots,cybersecurity,and RFID technology in Industry 4.0,are discussed in this study to analyze and develop the part manufacturing process in Industry 4.0.The limitations and advantages of virtual manufacturing systems in Industry 4.0 are discussed,and future research projects are also proposed.Thus,productivity in the part manufacturing process can be enhanced by reviewing and analyzing the applications of virtual manufacturing in Industry 4.0.

Research on the Digital Economy,Technological Innovation,and Transformation and Upgrading of the Manufacturing Industry in Shandong Province

Based on panel data from 16 cities in Shandong Province from 2013 to 2022,and grounded in theoretical analysis,this paper constructs a benchmark regression model,a mediating effect model,and a heterogeneity test for empirical analysis.The results show that:(1)the digital economy has a significant positive effect on promoting the transformation and upgrading of the manufacturing industry in Shandong Province;(2)the digital economy can drive the transformation and upgrading of the manufacturing industry through technological innovation;and(3)the impact of the digital economy on the transformation and upgrading of the manufacturing industry in Shandong Province is evidently heterogeneous.

The Application of Knowledge Management(KM)by Small and Medium-Sized Enterprises(SME)in Manufacturing Industry

To accelerate the digital transformation of small and medium-sized manufacturing enterprises(SMEs),this study delves into the primary challenges encountered in adopting knowledge management(KM)within these organizations and identifies the essential methods for successful implementation.The objective is to provide practical recommendations for the effective adoption of KM.This research suggests that enterprises should promote knowledge management through three key approaches:enhancing employees’cognitive understanding,standardizing knowledge systems,and tailoring business scenarios to meet diverse needs.These findings offer valuable insights into the digital transformation of SMEs in the manufacturing sector,ultimately helping these businesses to remain competitive and innovative in a rapidly changing market.By addressing the specific needs and challenges faced by SMEs,this study aims to contribute to a more comprehensive understanding of how knowledge management can be leveraged to drive digital transformation and improve overall business performance.

Empirical analysis of carbon tariff's effect on the export structure of China's manufacturing industry and social welfare based on the GTAP model

In recent years,carbon emissions have gradually evolved from an environment issue into a political and economic one.Carbon tariff has brought about new trade barriers of developed countries,and in order to enhance the industrial competitiveness of developed countries,it will produce unfavorable impact on developing countries.Concentrated on the manufacturing industry,which is the most intensive high-carbon industry in China's export structure,this article studies the relationship between carbon tariff policy and industry structure of export trade and builds up a relation between climate change and international trade.First,by means of establishing a partial equilibrium model,it applies geometric analysis and mathematical analysis to compute the impact on China's manufacturing export trade and the consequences of the introduction of the US carbon tariff to China's manufacturing industry that has already imposed a domestic shipping carbon tax.Furthermore,with the application of the GTAP model,it estimates the overall economic and welfare effects on China's manufacturing industry if the US and Europe introduce carbon tariff by means of four ways,and then analyzes the influence on China's manufacturing industry export structure and social welfare as well.The result shows that the introduction of the US carbon import tariff lowers China's export price and export volume,and the implementation of a domestic carbon tax justifies a higher export price and a lower export volume for China.However,the degree of export reduction is smaller than that under the effect of the US carbon tariff.In the case of developed countries imposing carbon tariff on China's energy-intensive industries,such as chemical rubber products,oil and coal-processing industry and paper industry,whose export would be reduced,the negative impact on the paper industry is the severest,which will decrease the paper industry's export ranging from 1.79%to 6.05%,whereas the other industries' export will increase.Anyhow,it will promote China's manufacturing industry to adjust the export structure to a certain extent.In addition,it will lead to a decrease in China's welfare,with a decrease between $2,134 billion and $8,347 billion.Finally,this paper provides information on international coordination,export structure adjustment and green manufacturing adjustment as a reference for the development of China's manufacturing industry.

Spatial Organization of Innovation in the Oil Equipment Manufacturing Industry: Case of Dongying, China

As innovation and technological change have become increasingly important for the competitiveness and sustainable growth of firms,cooperative innovation is now crucial for traditional industries in the context of globalization.This paper proposes a framework for analyzing the spatial pattern of cooperative innovation for traditional industries in developing countries.Based on in-depth interviews with 35 firms in the oil equipment manufacturing industry in Dongying City,China,this study argues that different firms in the innovation pyramid have various innovation activity preferences and spatial patterns.Firms with high innovation abilities tend to cooperate with various partners that are geographically dispersed and continuously expanding,while firms with inferior abilities usually cooperate with nearby fixed partners.Due to the differences in innovation environment and actor locations,firms tend to make different choices regarding innovation types and models,which highlight the importance of personnel training and basic scientific research at the global scale and practical product research and development at the national scale.Additionally,talent flow is the most important way to realize relationships for firm innovation activity.

Effects of Global Value Chain Position on the Carbon Emissions of Manufacturing Industry in China: An Empirical Study Based on the STIRPAT Model

Based on the input-output data from the World Input-Output Database( WIOD),the global value chain( GVC) position of China's manufacturing industry from 2003 to 2014 was calculated,and the relationship between the carbon emissions and global value chain position of China's manufacturing industry was studied based on the improved STIRPAT model. The results show that the improvement of global value chain position could significantly reduce the carbon emissions of China's manufacturing industry. In addition,foreign investment and energy structure hindered the low-carbon development of China's manufacturing industry. The effects of population size and research intensity on the carbon emissions of manufacturing industry were not significant. In the process of participating in the global value chain,China's manufacturing industry should effectively reduce carbon emissions by strengthening environmental regulation,optimizing energy structure and improving production technology.

Development on manufacturing technology of railway locomotive and rolling stock industry in China

This paper described progress and development on the welding technology and vehicle manufacture during last decade, which promoted the technical progress for development and creation a considerable variety of high quality products in railway locomotive and rolling stock industry.

Current Status of the Integrated Circuit Industry in China--IC Manufacturing Industry

Editorial Introduction: China's IC industry has been flourishing in recent years, huge market demand together with government investments are the major driving forces for this development. The status and development momentum of the Chinese IC industry also attracted wide interest and attention of international counterparts. A group of domestic IC experts are invited by the JoMM to write a series of articles about China's IC industry, including the history, current status, development, and related government policies. Information in these articles is all from public data from recent years. The purpose of these articles is to enhance mutual understanding between the Chinese domestic IC industry and international IC ecosystem. The following article is the third one of this series, the status quo of China's IC industry. The IC industry chain is very long including design, manufacturing, special equipment, materials, packaging and testing. The article series are arranged in accordance with this scope.

Research on the Industrial Transfer and Restructuring Path of the Energy-Intensive Manufacturing Industry in Western China

The orderly transfer of the manufacturing industry is a major action in China’s industrial restructuring.From the perspective of industrial transfer,we used the concentration ratio to depict the trend of the industrial transfer of energy-intensive manufacturing in the eastern,central,and western regions since the policy of large-scale development of western China was implemented.We measured the total factor productivity(TFP)of western China using the DEAMalmquist index method.We conducted a regression analysis to measure the effect of western China’s undertaking of the transfer of the energy-intensive manufacturing industry.The findings of this study show that during 2000–2019,eleven provinces(as well as autonomous regions and municipalities)in western China undertook the transfer of the energy-intensive manufacturing industry from the eastern and central regions to varying degrees,exhibiting significant phase features regarding the rate and scale of transfers.Further investigation also demonstrated that the transfer of energy-intensive manufacturing industries has a U-shaped enabling effect on TFP in western China with the scale effect greater than the technology effect.Therefore,it is necessary to transition from“extensive industrial transfer”at the cost of the labor force,land,and resources to“modern industrial transfer”featured by technology and efficiency improvements to contribute to industrial restructuring in western China effectively.

Should China's Manufacturing Industry Transition Towards Both Ends of the "Smiling Curve" ?——A Comparative Analysis between China and Traditional Manufacturing Powers

The manufacturing sector in China has surpassed that of the United States in terms of scale.Yet it still suffers from the shocks of an international economic downturn,the lack of core technologies,and the impact of "re-industrialization" of the developed economies.Based on an evaluation of the "smiling curve" theory and selected trade data from 1991 to 2011,this paper performs a comparative analysis of the differences between the manufacturing sectors of China and those of the traditional manufacturing powers in terms of product categories and architecture.This analysis is conducted in order to explore the question of whether China should transition from being the "world's manufacturing plant" to both ends of the "smiling curve".The paper then introduces Japan's "inverted smiling curve " to explore whether profit margins remain in the manufacturing sector.Research shows that China's manufacturing capacity,especially its "integrated" product assembly capacity,has not been fully realized,and that the development of the manufacturing sector can still yield high market returns.As a result,it is necessary for China to continue the path of being the "world's manufacturing plant".

Technological Innovation Efficiency Evaluation of Equipment Manufacturing Industry--An Empirical Study of Shandong Province in China

Based on the statistical data of eight sub-sectors of equipment manufacturing industry in Shandong province from 2012-2016,DEA and Malmquist index were used to give the static and dynamic evaluation of technological innovation efficiency.The results show that the overall technological innovation efficiency of Shandong equipment manufacturing industry is higher due to the high pure technical efficiency and scale efficiency.As the technical regress and inefficient allocation of resources deepened,the total factor productivity of Shandong equipment manufacturing industry presents a dropped tendency.According to the innovation efficiency and its changes,different industries should adopt the specific development strategies.

The Wolf Is Coming?——Multinationals's Entry and Effect on China's Manufacturing Industry

Nowadays,China has become the country that introduces the largest amount of foreign capital.Up to June 2008,the accumulative total number of foreign- invested enterprises in China is over 632 thousand:the total amount of actual use of foreign capital is over US$582 billion.There are over 400 multination- als of top 500 investing in China,30 of which set up regional headquarters。

Review of China's Hydropower Manufacturing Industry

China's hydropower equipment manufacturing technology has benef ited from the policy of reform and opening-up and the "Three Gorges Model." The latter means an approach of self-supply of hydropower equipment. Based on the foundations laid through independent research and development, by way of digesting, absorbing and innovating the technologies introduced from abroad for the Left Bank Station of the Three Gorges Hydropower Station, domestic suppliers independently designed and manufactured large hydropower units for the Right Bank Station of the Three Gorges and many other large hydropower stations in China.

Intelligent Manufacturing in the Context of Industry 4.0： A Review

Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.

Fundamental Theories and Key Technologies for Smart andOptimal Manufacturing in the Process Industry

Given the significant requirements for transforming and promoting the process industry, we present themajor limitations of current petrochemical enterprises, including limitations in decision-making, produc-tion operation, efficiency and security, information integration, and so forth. To promote a vision of theprocess industry with efficient, green, and smart production, modern information technology should beutilized throughout the entire optimization process for production, management, and marketing. To focuson smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of themanufacturing process, operating mode, and supply chain management, we put forward several key scien-tific problems in engineering in a demand-driven and application-oriented manner, namely：intelligentsensing and integration of all process information, including production and management information; collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; cooperative control and optimization of plant-wide production processes via human-cyber-physical in-teraction; and Q life-cycle assessments for safety and environmental footprint monitoring, in addition totracing analysis and risk control. In order to solve these limitations and core scientific problems, we furtherpresent fundamental theories and key technologies for smart and optimal manufacturing in the processindustry. Although this paper discusses the process industry in China, the conclusions in this paper can beextended to the larocess industry around the world.

Intelligent Manufacturing for the Process Industry Driven by Industrial Artificial Intelligence

Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.

Opportunities and Challenges of Artificial Intelligence for Green Manufacturing in the Process Industry

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.