Advanced Manufacturing Sectors Research Articles

Research on risk identification of manufacturing enterprises' Internet strategic transformation.

The Communist Party of China's 19th National Congress underlined the necessity of speeding the development of a manufacturing powerhouse and advanced manufacturing sector by supporting the deep integration of the Internet, big data, artificial intelligence, and the real economy. This study employed principal component analysis to extract the prominent risk factors from questionnaire data in order to manage the risks connected with the Internet strategic transformation of manufacturing firms. To confirm the major risk factors, a structural equation modeling was created using Amos-24 software. The findings revealed that risk factors of Internet strategic transformation in manufacturing businesses are mostly expressed in equipment flexibility risks, organizational versatility risks, smart technology risks, Internet technology risks, flexible management risks, and financing management risks. The paper offers useful theoretical and practical insights into the risks of China's manufacturing businesses' Internet strategic transformation. The findings can assist manufacturing firms in better identifying and managing these risks, supporting their smooth transition to the Internet economy.

Untapped Opportunities in Additive Manufacturing with Metals: From New and Graded Materials to Post-Processing

Metal additive manufacturing (AM) is an innovative manufacturing method with numerous metallurgical benefits, including fine and hierarchical microstructures and enhanced mechanical properties, thanks to the utilization of a local heat source and the rapid solidification nature of the process. High levels of productivity, together with the ability to produce complex geometries and large components, have added to the versatile applicability of metal AM with applications already implemented in various sectors such as medicine, transportation, and aerospace. To further enhance the potential benefits of AM in the context of small- to medium-scale bulk production, metallurgical complexities should be determined and investigated. Hence, this review paper focuses on three significant metallurgical aspects of metal AM processes: in situ alloying, functionally graded materials, and surface treatments for AM parts. The current text is expected to offer insights for future research works on metal AM to expand its potential applications in various advanced manufacturing sectors.

VR/MR systems integrated with heat transfer simulation for training of thermoforming: A multicriteria decision-making user study

The emerging Industry 5.0 paradigm emphasizes the importance of collaboration between machines and human operators in smart factories, thereby preventing full automation and elimination of the skilled workforce. One technology that has been proposed recently as a means of achieving this collaboration, is the Extended Reality (XR), particularly for operators training and upskilling. However, current XR applications in advanced manufacturing sector are rather limited, mainly focusing on maintenance or sequential training. Additionally, most of earlier studies in the field have examined the use of one type of XR environment solely, such as Virtual Reality (VR), Augmented Reality (AR), or Mixed Reality (MR) in a respective application. The present study aims to develop and compare the performance of both MR and VR environments for training operators during the monitor and control of a given thermoforming manufacturing process. To achieve this, Meta Quest 2 (VR headset) and Microsoft HoloLens 2 (MR headset) were utilized in combination with heat transfer numerical simulations of the process. A video training tool was also created and employed as a reference/conventional training method, for comparisons. A user study involving 26 participants (with a mix of prior experience) was conducted, assessing different performance criteria including the usefulness, trust, reliability, user satisfaction, training effectiveness, and overall user preference over each training tool. Results, using statistical analysis along with five Multiple Criteria Decision Making (MCDM) algorithms, collectively indicated that the users preferred MR over VR and video training in the present case study; particularly as MR provided greater presence experience and satisfaction, higher user-friendliness and reliability. A demonstration of the developed applications can be found in the Supplementary Material.

Mechanism and evolution trend of digital green fusion in China's regional advanced manufacturing industry

This paper has observed pivotal changes in innovative frameworks at the intersection of the digital revolution and sustainable initiatives. Within Industry 4.0, the fusion between intelligent manufacturing and green innovation has become a central driver for sustainability. Integrating these two pivotal forces to harness their collective efficiency is crucial. However, current literature offers limited insights into their combined impact, and the direction of their evolving trends still needs to be defined. Considering this, the research elucidates the core concepts and traits of digital-green fusion (DGF) within regional advanced manufacturing (RAMIDGF). Moreover, this research proposes a double-helix fusion mechanism model. Utilizing data from the advanced manufacturing sectors in six key Chinese urban clusters, this paper adopts a comprehensive analytical toolkit that includes the Coupling Modified Model, Kernel Density Estimation, Markov Chain algorithms, and the Dagum Gini Coefficient for trend analysis. The findings indicate that between 2009 and 2021, RAMIDGF exhibited a trend of initial growth followed by a decline, showing a strong correlation with per capita GDP (RGDP). The principal source of variation in RAMIDGF stems from differences between urban agglomerations, with the Yangtze River Delta and the Beijing-Tianjin-Hebei clusters exhibiting transitional behavior and a ‘ladder-type trend’ in RAMIDGF. As metropolitan clusters become more economically integrated, the probability of transitional behavior in RAMIDGF heightens. However, achieving elevated leapfrog development proves challenging, with an inherent risk of decline. Spatial spillover implications, agglomeration characteristics, and club convergence tendencies mark the RAMIDGF process. These findings expand upon new paradigms for regional sustainable development, offering novel avenues for realizing high-quality growth.

Metal Additive Manufacturing and Its Post-Processing Techniques

Metal additive manufacturing has made substantial progress in the advanced manufacturing sector with competitive advantages for the efficient production of high-quality products [...]

Analysis and Control of Macroeconomic Trends Based on the Leontief Model

In the present study, we consolidate the forty-five industrial sectors delineated in the U.S. input-output tables, as disseminated by the OECD, into three overarching sectors: advanced manufacturing, modern services, and a residual category termed ’others.’ We adopt gross fixed capital formation as a proxy for the proportion of net profit allocated to investment, positing that the investment requisite for augmenting output is commensurate with the requisite capital intensity. This framework enables us to forecast the trajectory of total output and GDP, taking into account the interplay of multiple determinants. In addressing the inherent linear control dynamics of the input-output model, we apply classical control theory to regulate the advanced manufacturing sector. By deriving control equations that accommodate multifactorial influences, we substantiate the efficacy of this control mechanism through rigorous numerical analysis. Moreover, we reconceptualize the dynamic input-output system as a game-theoretic model characterized by a saddle-point equilibrium. By leveraging the saddle-point equilibrium strategy, we pioneer an innovative approach to resolving the complexities of dynamic input-output analysis. This methodological innovation not only enhances the precision of our predictions but also contributes a novel perspective to the literature on economic modeling and control theory.

Brexit, Trade and UK Advanced Manufacturing Sectors: A Midlands' Perspective

Brexit, Trade and UK Advanced Manufacturing Sectors: A Midlands' Perspective

Transformative role of big data through enabling capability recognition in construction

Big data application is a significant transformative driver of change in the retail, health, engineering, and advanced manufacturing sectors. Big data studies in construction are still somewhat limited, although there is increasing interest in what big data application could achieve. Through interviews with construction professionals, this paper identifies the capabilities needed in construction firms to enable the accrual of the potentially transformative benefits of big data application in construction. Based on previous studies, big data application capabilities, needed to transform construction processes, focussed on data, people, technology, and organisation. However, the findings of this research suggest a critical modification to that focus to include knowledge and the organisational environment along with people, data, and technology. The research findings show that construction firms use big data with a combination strategy to enable transformation by (a) driving an in-house data management policy to rolling-out the big data capabilities; (b) fostering collaborative capabilities with external firms for resource development, and (c) outsourcing big data services to address the capabilities deficits impacting digital transformation.

Perceiving and managing Brexit risk in UK manufacturing: evidence from the midlands

ABSTRACT This paper assesses the risk implications of Brexit for UK-based, manufacturers, drawing on data generated from semi-structured interviews with senior managers and directors in the advanced manufacturing sector of the West Midlands region of the UK in 2021. The UK’s departure from the EU has led to increased socio-economic risk for manufacturing businesses, requiring careful management by the latter. This paper draws on elements of the Kasperson et al. [1988. The social amplification of risk: A conceptual framework. Risk Analysis, 8(2), 177–187] Social Amplification of Risk Framework (SARF) to explore the communication of risk and uncertainty to businesses, during and post-Brexit discussions. This paper then examines the extent to which risk arises from changes to supply chains and production regimes and in turn examines consequences for the management of risk.

Глобальные рынки передового производства — новая возможность для технологического обновления России

New technologies, including Industry 4.0, are rapidly changing traditional and high-tech industries, and forming the advanced manufacturing sector within the industrial complex. By now Russia has been characterized by a modest presence in the world advanced manufacturing markets – Russia’ share is less than 0.6% in certain markets and less than 0.4% in global advanced manufacturing. This is partially explained by the scarce commodity range in the Russian export basket, which determines weak representation of Industry 4.0 goods. Large part in the Russian advanced manufacturing exports is traditional for the Russian economy goods — airplanes, turbojet engines, fuel rods. However, we observe positive structural changes in Russian exports caused by the COVID-19 pandemic. Russia has increased exports of goods with bio- and additive technologies, optoelectronics. It seems that the entry to new advanced manufacturing markets for Russia can form the basis for long-term growth. International experience shows that advanced manufacturing exports are often supported by advanced manufacturing imports. We find that Russian economy significantly underutilizes this channel. Although Russian advanced manufacturing imports are gradually growing, it is focused primarily on final consumer goods. We consider industrial robots as a case of advanced manufacturing imports that deserves special attention as a widespread cross-cutting technology that can significantly transform the technological level of industries. Our estimates show that, although the robotics market in Russia is relatively small and has low growth rates relatively to investment in fixed assets, companies importing industrial robots are larger and more productive. This evidence allows us to determine the import of industrial robotics as one of the priority directions of modernization of the Russian manufacturing. Based on the analysis we identify and discuss three growth opportunities for Russia in global advanced manufacturing: 1) support of exports of services in optoelectronics and ICT through the use of accumulated human capital and competencies and taking into account fast transformation of business models in industry, 2) support of exports of biotechnology products, taking into account positive reputational effects and expanding Russian pharmaceutical exports under the COVID-19 pandemic; 3) support of technology companies in wide number of advanced manufacturing taking into account current favorable environment for the birth of tech startups in Russia.

James K. Galbraith Comment on Comparing COVID-19 Control in the Asia-Pacific and North Atlantic Regions

James K. Galbraith Comment on Comparing COVID-19 Control in the Asia-Pacific and North Atlantic Regions

The value of firm linkages in the age of industry 4.0: a qualitative comparative analysis

Over the years, manufacturing in advanced economies has been the object of intense reorganization driven crucially by the international strategies of multinational enterprises (MNEs), and more recently, by technological disruptions powering a new manufacturing model, defined as Industry 4.0 (I4.0). This paper aims to explore firm-based, place-based and global drivers that can determine high levels of companies’ performance in the context of the emerging manufacturing model ‘I4.0’. In particular, our article tests the relative importance of and balance between three determinants of MNEs’ performance: (i) MNEs’ internal operations and R&D capabilities; (ii) reliance on local external economies and co-location with high-value service and technological competence; and (iii) the extent of MNEs’ production in terms of spread across global value chains. We empirically address this issue by surveying top managers of MNEs operating in four advanced manufacturing industries (biotech, engineering, fashion, and new materials) and located in five European countries (Germany, Italy, Spain, Sweden and the United Kingdom). We adopt fuzzy-set qualitative comparative analysis, a configurational, case-oriented approach. MNEs can be highly profitable when they follow different, but equally successful, paths. Our findings shed light on which balance between firm-based, place-based and global drivers positively impacts on companies’ performance in European advanced manufacturing sectors. In particular, we find that companies that collaborate with local suppliers of enabling technologies linked to I4.0 - with regard to the variety and intensity of collaborations- show high levels of performance. Policy implications are drawn in the concluding remarks.

Structural change in the Chinese economy and changing trade relations with the world

This paper examines the impact of structural change in China, in particular a reduction in the savings rate, an increase in the share of skilled workers, and an increase in productivity in technologically advanced manufacturing sectors targeted by Made in China 2025. Baseline projections until 2040 are generated with the WTO Global Trade Model, a dynamic computable general equilibrium model. With the modelled structural changes, the Chinese economy is projected to reorient its focus increasingly onto the domestic economy, raising the share of private household and government consumption in GDP, turning China's trade surplus into a trade deficit, reducing China's share in global exports, raising the share of services in both production and exports, shifting the destination markets of Chinese exports from developed to developing countries, and changing its pattern of comparative advantage away from sectors like light and heavy manufacturing to electronic and machinery equipment. The large bilateral trade surplus vis-a-vis the United States is projected to fall to almost zero.

Integration of Simulation Driven DfAM and LCC Analysis for Decision Making in L-PBF

Laser based powder bed fusion (L-PBF) is used to manufacture parts layer by layer with the energy of laser beam. The use of L-PBF for building functional parts originates from the design freedom, flexibility, customizability, and energy efficiency of products applied in dynamic application fields such as aerospace and automotive. There are challenges and drawbacks that need to be defined and overcome before its adaptation next to rivaling traditional manufacturing methods. Factors such as high cost of L-PBF machines, metal powder, post-preprocessing, and low productivity may deter its acceptance as a mainstream manufacturing technique. Understanding the key cost drivers of L-PBF that influence productivity throughout the whole lifespan of products will facilitate the decision-making process. Functional and operational decisions can yield profitability and increase competitiveness among advanced manufacturing sectors. Identifying the relationships between the phases of the life cycle of products influences cost-effectiveness. The aim of the study is to investigate the life cycle cost (LCC) and the impact of design to it in additive manufacturing (AM) with L-PBF. The article provides a review of simulation driven design for additive manufacturing (simulation driven DfAM) and LCC for metallic L-PBF processes and examines the state of the art to outline the merits, demerits, design rules, and life cycle models of L-PBF. Practical case studies of L-PBF are discussed and analysis of the interrelating factors of the different life phases are presented. This study shows that simulation driven DfAM in the design phase increases the productivity throughout the whole production and life span of L-PBF parts. The LCC model covers the whole holistic lifecycle engineering of products and offers guidelines for decision making.

Geographic differences in the distribution of manufacturing firms in Ontario, Canada

For at least the past 20 years, the Province of Ontario – as well as other advanced economic regions – has experienced a period of transition, with traditional manufacturing declining and advanced manufacturing firms and sectors emerging. Concurrently, there has been a concerted policy effort emphasising the development of industry clusters within the province, though key issues of governance and where and how to invest public funds remain. This paper presents research on the spatial configuration of firms in 26 manufacturing sub‐sectors, using point density analysis of the basis for determining the presence and spatial configuration of firms. This allows for the comparison of patterns observed in traditional, advanced, and evolving sub‐sectors. The findings show that there are patterns of clustering in all sub‐sectors, though different spatial configurations are apparent between traditional, advanced, and evolving sub‐sectors. These differences have implications for both investment and governance. Based on the findings, investment needs to be directed towards areas with locational advantages, while regional perspectives and initiatives on cluster governance are needed.

Laser Induced Phased Arrays (LIPA) to detect nested features in additively manufactured components

Additive manufacturing (AM) has the capability to build complex parts with internal features, which have many advantages over conventionally manufactured parts. This makes AM an alternative for advanced manufacturing sectors. AM components suffer from defects due to the lack of understanding in the build process. This makes the adaptation of AM in safety-critical industries, such as aerospace, problematic. The current AM work flow calls for costly off-line inspections to qualify components as defect-free. The layer by layer nature of the AM provides an opportunity for an on-line inspection to take place. This can provide early detection of defects as well as information for optimization and repair of the build. Laser Induced Phased Arrays (LIPA) present themselves as a viable remote, non-destructive, ultrasonic technique capable of being implemented as part of an on-line inspection of AM. Lasers are used to generate and detect ultrasound and a phased array is synthesized in post-processing. This paper demonstrates the capability of LIPA to successfully detect and locate features within AM components off-line. Cylindrical features as small as 0.2 mm in diameter and 26 mm above the inspection surface were detected using LIPA and verified using X-ray computed tomography (XCT).

Does spatial proximity raise firm productivity? Evidence from British manufacturing

AbstractThe UK’s economy is one of the most regionally imbalanced in Europe. The government’s recent industrial strategy discusses various means of addressing this, one of which is the strengthening of existing clusters. Using plant-level indices of spatial proximity derived from postcode district data, this article investigates the extent of spatial concentration and its impact on total factor productivity in advanced manufacturing sectors in Great Britain. The results from estimation of production functions indicate that, in most advanced manufacturing sectors, spatial concentration has a negative impact on productivity in small plants and a positive effect in larger plants. Large plants likely benefit more from knowledge spillovers due to their higher levels of absorptive capacity.

Uncovering the impacts of industrial transformation on low-carbon development in the Yangtze River Delta

In China, industrial transformation have received attention as an effective means of CO2 emissions abatement. In our study, industrial transformation has a more generalized meaning including investment structure, trade structure, final demand structure, intensity structure and production structure. We built up a comprehensive analysis framework to evaluate how the industrial transformation process impact on CO2 emissions from the sectoral perspective, and applied it to the Yangtze River Delta, which is a leading region in terms of economy, industrial, and relatively low-carbon development within China. The results indicate the Yangtze River Delta has gradually developed toward an industrialization structure dominated by the service and advanced manufacturing sectors such as machinery manufacturing, leading to a slow growth in CO2 emissions during 2002–2012. The improvement of CO2 intensity and production structure in the service and construction sectors, and in machinery manufacturing particularly, has mainly led to this slow growth. Moreover, substantial CO2 emissions were avoided by imports from resource-related manufacturing and mining sectors. Within this region, the differences in improvement of CO2 intensity and production structure in machinery manufacturing, services sectors led to the gap in CO2 emissions between Shanghai and Zhejiang from 2002 to 2012. Meanwhile, swift investment, exports and inconspicuous improvement of CO2 intensity and production structure in machinery manufacturing and construction sectors widened the gap in CO2 emissions between Jiangsu and two other regions. Further, optimizing CO2 intensity and production structure is a feasible way to realize regional low-carbon development.

Ecological network analysis of an energy metabolism system based on input-output tables: Model development and case study for Guangdong

Rapid urbanization results in energy shortage and unreasonable energy metabolism structure. The goal of this research is to take Guangdong, China as a special case study to illustrate the influence of energy classification differences on the energy metabolism system. To do so, we introduced the concept of “urban metabolism”, and treated sectors and energy flows as nodes and paths in a network model. We used the input output analysis to compile the physical input output table through the embodied energy element intensity. Building on this, we used ecological network analysis to quantify the urban metabolic processes and energy metabolism levels within the urban system. In addition, the alternative indicators are first introduced to explore the best alternative energy in various sectors to avoid a short-term energy crisis. In this paper, different energy groups are considered on the energy metabolism system, including all energy, primary energy, secondary energy and six specific energy, which will fill the research gap about the influence of energy classification on urban energy metabolism. It is found that the energy metabolism of Guangdong is now in the state of sub-health. The energy metabolism hierarchy atlas shows that the pulling force is hardly affected by the energy classification but the driving force is very sensitive, which further illustrate that producers can choose different energy according to their production structure. Facing the shortage of energy supply, the secondary energy with the highest substitutability of all energy value is the better alternative energy for advanced manufacturing sector (containing twelve industries such as Manufacture of transportation equipment and Manufacture of metal products). More specifically, the nonrenewable properties of primary energy make it particularly important to find the corresponding alternative energy. Heat is the best alternative energy for crude oil, while electricity is irreplaceable. It is expected that the results will provide scientific support to guide the reform of urban energy metabolic system in an attempt to coordinate the energy development strategy, improve the energy consumption structure and maintain energy security and stability.

Feasibility Study of Construction Project in Compliance with Bank Investment Supervision Requirements

On the basis of the 12-year author's practice of Bank Investment Supervision developed methodology significant construction projects risks have been identified and measured: risks of the highest impact values and risks of the biggest likelihood appearance. The research has been recorded in 400 - 450 reports of 42 investment projects in advanced manufacturing, commercial, residential, hotels and apartment housing sectors. At least one risk of the highest measured level of significance has been highlighted at each phase of investment process: design, construction and maintenance. A reasonable level of risks significance has been determined which stands for not more than 1/3 of possible significance in “risks monitoring” strategy. Engineering, Project and Construction Management (EPCM) approach to investment process and solid, consequent, regular construction projects monitoring executed by professional Banking Supervision Inspector (BSI) make possible to minimise any faults of inappropriate financing of construction projects.