Hasil untuk "Manufacturing industries"

Tarekul Islam, M. Repon, T. Islam et al.

De-Graft Joe Opoku, S. Perera, R. Osei–Kyei et al.

Abstract The construction industry is faced with numerous challenges including low productivity, lack of research and development, and poor technology advancements. Advances in digital technologies such as digital twin (DT) has seen enormous utilisations in digitally advanced industries including the manufacturing and automotive industries. It presents an opportunity for the integration of the physical world to the digital world. DT technology has the potential to transform the construction industry and provide responses to some of its challenges. As a result, the concept of DT has attracted much attention and is developing at a rapid pace. The overarching aim of this study was to analyse the current state of DT applications in the construction industry. This study comprehensively reviews and analyses DT concept, technologies, and application in the construction industry using a systematic review methodology while incorporating the science mapping method. After a complete search of several databases and careful selection in line with the proposed criteria, 22 academic publications about DT application in the construction industry were identified and classified accordingly. The research analysed in detail the status, evolution of the concept, key technologies, and six areas of application in the lifecycle phases of a project: building information modeling, structural system integrity, facilities management, monitoring, logistics processes, and energy simulation. This research shows that there is a high potential for DT to enable solutions to the numerous challenges in the construction industry. Thus, this study raises the level of awareness and need for the application of DT in the construction industry.

Y. Tay, B. Panda, S. Paul et al.

S. Rosenthal, W. Strange

A. Levinson, M. Taylor

G. Nicoletti, S. Scarpetta

The authors look at differences in the scope and depth of pro-competitive regulatory reforms and privatization policies as a possible source of cross-country dispersion in growth outcomes. They suggest that, despite extensive liberalization and privatization in the OECD area, the cross-country variation of regulatory settings has increased in recent years, lining up with the increasing dispersion in growth. The authors then investigate empirically the regulation-growth link using data that cover a large set of manufacturing and service industries in OECD countries over the past two decades and focusing on multifactor productivity (MFP), which plays a crucial role in GDP growth and accounts for a significant share of its cross-country variance. Regressing MFP on both economywide indicators of regulation and privatization and industry-level indicators of entry liberalization, the authors find evidence that reforms promoting private governance and competition (where these are viable) tend to boost productivity. In manufacturing the gains to be expected from lower entry barriers are greater the further a given country is from the technology leader. So, regulation limiting entry may hinder the adoption of existing technologies, possibly by reducing competitive pressures, technology spillovers, or the entry of new high technology firms. At the same time, both privatization and entry liberalization are estimated to have a positive impact on productivity in all sectors. These results offer an interpretation to the observed recent differences in growth patterns across OECD countries, in particular between large continental European economies and the United States. Strict product market regulations-and lack of regulatory reforms-are likely to underlie the relatively poorer productivity performance of some European countries, especially in those industries where Europe has accumulated a technology gap (such as information and communication technology-related industries). These results also offer useful insights for non-OECD countries. In particular, they point to the potential benefits of regulatory reforms and privatization, especially in those countries with large technology gaps and strict regulatory settings that curb incentives to adopt new technologies.

K. Mathiyazhagan, K. Govindan, A. NoorulHaq et al.

Alberto Diez-Olivan, J. Ser, D. Galar et al.

The so-called “smartization” of manufacturing industries has been conceived as the fourth industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and progressive maturity o ...

Eric Fang, Robert W. Palmatier, J. Steenkamp

David H. Autor, David Dorn, Gordon H. Hanson et al.

In the past two decades, China’s manufacturing exports have grown spectacularly. U.S. imports from China have surged, while U.S. exports to China have increased more modestly, consistent with the two countries’ divergent current account imbalances. Using data on individual earnings by employer from the Social Security Administration, we examine how exposure to import competition aects the long-term earnings and employment trajectory of workers initially employed in manufacturing industries. We find that workers who in 1991 were employed in industries that experienced high subsequent levels of import growth garner lower cumulative earnings over the subsequent sixteen years (1992 through 2007) and are at substantially elevated risk of obtaining Social Security Disability Insurance benefits as the only recorded source of income in a given year. More exposed individuals spend less time working for their initial employers, less time working in their initial two-digit manufacturing industries, and more time working elsewhere in manufacturing and outside of manufacturing. Eects on earnings and employment are larger for individuals whose initial employers were relatively large, whose initial wages where below their firm’s average, and who in the pre-sample period worked part time or intermittently. We obtain similar results using alternative measures of trade exposure. Our findings suggest that there is significant worker-level adjustment cost to import shocks and that adjustment is highly uneven across individuals according their conditions of employment in the pre-shock period.

A. Gilchrist

Abirami Raja Santhi, Padmakumar Muthuswamy

The Industrial Revolution can be termed as the transformation of traditional industrial practices into new techniques dominated by the technologies available at that time. The first three industrial revolutions were driven respectively by mechanization, electrification, and automation which had gradually transformed the agrarian economy into a manufacturing-based economy. It helped in enhancing the lifestyle of the factory workers and the healthcare system, which improved the overall quality of living. The industries that adapted to the change witnessed a tremendous increase in the production of goods, competitive advantage, and cross-border business opportunities. While we are currently living to see the fourth industrial revolution (also known as Industry 4.0) unfolding around us, the world is poised for the next big leap, the fifth industrial revolution or Industry 5.0. Hence, the first half of the paper outlines the enabling technologies of Industry 4.0 and conceptualizes how they would act as the foundation for the fifth industrial revolution. The socio-economic challenges of the technologies and the need for Industry 5.0 technologies are also discussed. The second half of the paper outlines the prospective technologies of Industry 5.0, their potential applications from the perspective of industry leaders and scholars and conceptualizes how they can overcome the challenges of Industry 4.0. The definition of “sustainability trilemma” a new term coined by the authors, and the reasoning for calling the next industrial revolution “Industry 4.0S” (another new term) rather than Industry 5.0 are also presented.

Andrew B. Bernard, J. Jensen, Peter K. Schott

A. Bernard, Charles I. Jones

Yunlei Sun, Peng Dai, Yangxingyue Liu et al.

Engineering drawings are fundamental to industries such as oil and gas, construction, and manufacturing. However, current practices relying on manual design or rigid parametric templates often suffer from inefficiency and layout inconsistencies. To address these issues, the layout task is formulated as the Orthogonal Rectangle Packing Problem with Multiple Configurations and Complex Constraints (ORPPMC). The Deep Reinforcement Learning for Multi-Configuration Drawing Layout (DRL-MCDL) framework is proposed, which integrates the Pointer Network for Drawing Element Sequencing (PN-DES) with the Target-Type-Matching-based Multi-Pattern Positioning Strategy (TTM-MPPS). Within this framework, PN-DES employs deep reinforcement learning and feature fusion to combine element attributes with layout configurations for optimal sequence inference, while TTM-MPPS performs precise positioning in accordance with industrial rules to ensure strict adherence to aesthetic requirements. Ablation experiments validate the contribution of each module. Experimental results on real-world engineering drawings demonstrate that DRL-MCDL achieves a Feasibility Rate (FR) exceeding 98.5% on standard instances (12–40 elements), significantly outperforming traditional methods. Furthermore, it maintains a high inference efficiency with an Average Time (AT) of less than 0.3 s, striking an optimal balance between layout quality and computational speed.

Seungheon Shin, Byeonghyeon Goh, Youngtaek Oh et al.

Topology optimization produces designs with intricate geometries and complex topologies that require advanced manufacturing techniques such as additive manufacturing (AM). However, insufficient consideration of manufacturability during the optimization process often results in design modifications that compromise the optimality of the design. While multi-axis AM enhances manufacturability by enabling flexible material deposition in multiple orientations, challenges remain in addressing overhang structures, potential collisions, and material anisotropy caused by varying build orientations. To overcome these limitations, this study proposes a novel space-time topology optimization framework for multi-axis AM. The framework employs a pseudo-time field as a design variable to represent the fabrication sequence, simultaneously optimizing the density distribution and build orientations. This approach ensures that the overhang angles remain within manufacturable limits while also mitigating collisions. Moreover, by incorporating material anisotropy induced by diverse build orientations into the design process, the framework can take the scan path-dependent structural behaviors into account during the design optimization. Numerical examples demonstrate that the proposed framework effectively derives feasible and optimal designs that account for the manufacturing characteristics of multi-axis AM.

Sarow Saeedi

Digital Twin (DT) has gained great interest as an innovative technology in Industry 4.0 that enables advanced modeling, simulation, and optimization of service and manufacturing systems. This article provides an extensive review of the literature on digital twins (DTs) and their utilization at the levels of product/production line, production system, and enterprise, and considers how they have been applied under real industrial conditions. This article classifies the types of DTs as well as modeling technologies of DT and applications in different fields, with particular focus on the research of strengths and limitations of Discrete Event Simulation (DES) for systems modelling. A generic structure for DT is proposed, outlining the essential components and flow of data. Case studies demonstrate the benefits of DTs for increased efficiency, reduced downtime, and improved lifecycle management, as well as challenges caused by the complexity of data integration and cybersecurity risk, and high implementation costs. This paper contributes to the growing body of knowledge by identifying both the opportunities and barriers to widespread DT adoption. This study concludes that while DTs offer transformative capabilities for enhancing efficiency and decision-making, overcoming these challenges is crucial for realizing their widespread adoption and impact across service and manufacturing sectors.

Prof Dr Ray Wai Man Kong

There is applied research for the development of the Automated Stretch Elastic Waistband Sewing Machine represents a significant advancement in garment manufacturing, addressing the industry's need for increased efficiency, precision, and adaptability. This machine integrates innovative features such as a sensor-based automatic waistband expansion system, synchronized sewing speed and rolling wheel speed, and a differential feed top-loading mechanism. These enhancements streamline the sewing process, reduce manual intervention, and ensure consistent product quality. The machine's design incorporates both 3-wheel and 2-wheel rolling systems, each optimized for different elastic band dimensions and elongation factors. The 3-wheel rolling system accommodates a larger maximum boundary, while the 2-wheel rolling system offers a tighter operational range, providing flexibility to meet diverse manufacturing requirements. The Automated Stretch Elastic Waistband Sewing Machine has a design that controls the pulling apart force so as not to break the elastic waistband. It sets a new standard for quality and innovation, empowering manufacturers to meet the demands of a competitive market with precision and ease.

Goretti Cabaleiro-Cerviño, Pedro Mendi

This paper studies how the interplay between the cycle and firm-specific characteristics (firm size and exporting activities) shapes firms’ choice between exploratory and exploitative innovation investments. We analyze the PITEC database, a panel of Spanish firms in manufacturing and service industries with data spanning the 2005–2013 period, which includes the Great Recession years, characterized by sharp demand reductions and increased industry turnover. The results show that: 1) downturns affect exploration more than exploitation, making the probability of firms being classified as exploratory pro-cyclical; 2) the impact of downturns is stronger among small and medium enterprises (SMEs) than among large companies; and 3) exporting companies seem to be less affected by the cycle in their choice between exploration and exploitation. These results contribute to a deeper understanding of how external shocks interact with internal firm characteristics to shape innovation pathways.

I. I. Deren, V. V. Shmatkova

The Russian industry and its contribution to the country’s GDP have been analyzed, and the industrial sector by region has been studied. Statistical data and official reports of the Government of the Russian Federation for several years up to 2024 have been applied in order to track development trends. It has been estimated that the share of the industry in the country’s economy is about 30% of GDP and 22% of employment, reflecting its importance in the economy structure. In the context of foreign economic challenges and sanctions in 2022–2024, the industry has demonstrated adaptability through import substitution and government support, while maintaining its strategic importance. Industrial potential plays a key role in shaping the economic profile of Russian regions, especially in the Volga, Siberian, and Ural Districts. Despite the predominance of the service sector in the GDP structure (over 60%), the industry remains the most important sector. In 2023–2024, against the background of import substitution and digitalization measures, the manufacturing sector positions strengthened, reducing dependence on the raw material model. It has been recommended to pay more attention to industries that can provide domestic consumption of the country. The analysis gives an idea of the importance of industrial production for developing Russia’s economy and helps correctly prioritize the regulation and government support of these industries, but also pay attention to personnel training for these industries.