Lithium metal battery (LMB) possessing a high theoretical capacity is a promising candidate of advanced energy storage devices. However, its safety and stability are challenged by lithium dendrites and the leakage of liquid electrolyte. Here, a self‐enhancing gel polymer electrolyte (GPE) is created by in situ polymerizing 1,3‐dioxolane (DOL) in the nanofibrous skeleton for enabling safe LMB. The nanofiber membrane possesses a better affinity with poly‐DOL (PDOL) than commercial separator for constructing homogeneous GPE with enhanced ion conductivity. Furthermore, polydopamine is introduced on nanofiber membrane to form hydrogen bonding with PDOL and bis((trifluoromethyl)sulfonyl)imide anion, dramatically improving the mechanical strength, ionic conductivity, and transference number of GPE. Besides, molecular dynamic simulation is used to reveal the intrinsic factors of high ionic conductivity and reinforcing effect in the meantime. Consequently, the LiFePO4//Li batteries using self‐enhancing GPE show extraordinary cyclic stability over 800 cycles under high current density of 2 C, with a capacity decay of 0.021% per cycle, effectively suppressing the growth of lithium dendrites. This ingenious strategy is expected to manufacture advanced performance and high safety LMBs and compatible with the current battery production.
The rise in prices of traditional energy sources, the high dependence of many countries on their import, and the associated need for security of supply have led to large investments in new capacity of wind power plants. Although wind power generation is a mature technology and levelized cost of electricity low, there is still room for its improvement. A review of available literature has indicated that wind turbine development in the coming decade will be based on upscaling wind turbines and minor design improvements. These include further improvements in rotor blade aerodynamics, active control of the rotor blade rotation system, and aerodynamic brakes that will lead to increased power generation efficiency. Improvements in system maintenance and early diagnosis of transmission and power-related faults and blade surface damage will reduce wind turbine downtime and increase system reliability and availability. The manufacture of wind turbines with larger dimensions presents problems of transportation and assembly, which are being addressed by manufacturing the blades from segments. Numerical analysis is increasingly being used both in wind turbine efficiency analysis and in stress and vibration analysis. Direct drive is becoming more competitive with traditional power transmission through a gearbox. The trend in offshore wind farms is to increase the size of wind turbines and to place them farther from the coast and in deeper water, which requires new forms of floating foundations. Due to the different work requirements and more difficult conditions of the marine environment, optimization methods for the construction of offshore substructures are currently being developed. There are plans to use 66-kV cables for power transmission from offshore wind farms instead of the current 33-kV cables. Offshore wind farms can play an important role in the transition to a hydrogen economy. In this context, significant capacity is planned for the production of “green” hydrogen by electrolysis from water. First-generation wind turbines are nearing the end of their service life, so strategies are being developed to repower them, extend their life or dismantle and recycle them.
Oluwole Joseph Oladunni, Oluwole Joseph Oladunni, Carman K. M. Lee
et al.
Background and ObjectiveAdditive Manufacturing (AM), driven by digital 3D design data, is a transformative technology that holds significant potential to revolutionize the construction industry. Its untapped capacity to optimize material utilization, enhance design flexibility, and substantially reduce greenhouse gas (GHG) emissions emplaces it as key enabler to sustainable construction. Although being adopted in biomedical, aerospace, and automotive industries, AM remains underexplored in construction. This study systematically evaluates the role of AM in advancing sustainable construction, particularly its impact on reducing GHG emissions.Materials and methodsSystematic research was conducted using resourceful methodologies. These are to include PRISMA meta-analysis, Cochrane Collaboration, EPPI-Reviewer 4, VOSviewer, and Databases with Search Engines. The tools were employed to synthesize, organize, and to deduce relevant materials and literature, facilitating comparative analyses of AM and traditional (conventional) subtractive manufacturing (TSM). The systematic review essentially concentrates on metrics such as design process efficiency, cost-effectiveness, production rates, and material sustainability. Furthermore, on diverse AM techniques, and materials, to include concrete, composites, and polymers, being evaluated for their potential to mitigate carbon emissions.ResultsQuantitatively, the results connote that AM can better enhance energy efficiency by up to 60%, reduce material waste by 90%, and cushioned to lower GHG emissions by 80%, while achieving labour and cost savings of 50%–60%, and sustainability by 75% in specific design standards. Furthermore, AM enables the production of complex geometrical designs that are unfeasible with conventional methods, improving both structural and mechanical performance, and sustainability.ConclusionThis study expounds the environmental, social and economic benefits of AM, providing highly valuable insights to further incorporate AM to contemporary construction as viable alternative solutions, and sustainable supplements to TSM. Additive manufacturing innovations are deduced to be well positioned as significant strategic driver for eco-friendly built environment, supporting global efforts toward carbon neutrality and sustainable urban developments.
Engineering (General). Civil engineering (General), City planning
[Objective] In the context of “dual carbon” strategic goals and the development of new-quality productivity, this study explores how digital transformation drives the development of green productivity in manufacturing enterprises, providing an micro-level theoretical basis for developing new-quality productivity through digitalization and greening in manufacturing industry. [Methods] Using data from A-share listed manufacturing enterprises in China from 2007 to 2021, the global super-efficiency slacks-based measure (GS-SBM) model was employed to establish and calculate carbon emission efficiency indicators, so as to measure the levels of enterprise green productivity. An empirical examination was conducted to examine the effect of digital transformation on green productivity and its mechanisms. Then an analysis was carried out on the structural heterogeneity of the driving effect of digitization and the backward spillover effects in the industry and supply chains. [Results] (1) Digital transformation significantly enhanced the carbon emission efficiency in manufacturing enterprises, effectively promoting the development of green productivity. (2) The empowerment of green productivity development through digitalization in manufacturing enterprises was primarily achieved through dual mechanisms: green technological innovation and total factor productivity improvement. (3) The empowering effect of digitalization exhibited structural heterogeneity. Compared to the consumer end, digital transformation at the production end had more significant influences on improving carbon emission efficiency. Across the sub-dimensions of digital transformation, a U-shaped relationship existed between digital transformation driven by modern information system and carbon emission efficiency. This improvement effect of carbon efficiency manifested only when enterprises entered the stage of productivity transformation with data as a factor of production. (4) The backward spillover effects of digital empowerment were observed, where the digital transformation of downstream manufacturing enterprises drove improvements in carbon emission efficiency for upstream enterprises. [Conclusion] Digital transformation of manufacturing enterprises can significantly enhance green productivity development. Therefore, manufacturing firms should prioritize the development of digital capacity across production and productive service scenarios. Meanwhile, digital coordination across the industry chain should be strengthened, and staged and incremental approaches to transform data into productivity should be promoted. Governments should actively cultivate digital transformation service providers, improve innovation efficiency support mechanisms, and build data-sharing platforms to facilitate a qualitative leap in the productivity of manufacturing enterprises.
Metal additive manufacturing (MAM) has advanced significantly, yet accurately predicting clad characteristics from processing parameters remains challenging due to process complexity and data scarcity. This study introduces a novel hybrid machine learning (ML) framework that integrates validated multi-physics computational fluid dynamics simulations with experimental data, enabling prediction of clad characteristics unattainable through conventional methods alone. Our approach uniquely incorporates physics-aware features, such as volumetric energy density and linear mass density, enhancing process understanding and model transferability. We comprehensively benchmark ML models across traditional, ensemble, and neural network categories, analyzing their computational complexity through Big O notation and evaluating both classification and regression performance in predicting clad geometries and process maps. The framework demonstrates superior prediction accuracy with sub-second inference latency, overcoming limitations of purely experimental or simulation-based methods. The trained models generate processing maps with 0.95 AUC (Area Under Curve) accuracy that directly guide MAM parameter selection, bridging the gap between theoretical modeling and practical process control. By integrating physics-based simulations with ML techniques and physics-aware features, our approach achieves an R<sup>2</sup> of 0.985 for clad geometry prediction and improved generalization over traditional methods, establishing a new standard for MAM process modeling. This research advances both theoretical understanding and practical implementation of MAM processes through a comprehensive, physics-aware machine learning approach.
Type of the article: Research ArticleAbstractExport performance has become crucial for Vietnamese manufacturing SMEs as they face digital transformation and stronger global competition. This study investigates how resource-based determinants affect the export performance of Vietnamese manufacturing SMEs, with absorptive capacity (mediation) and international competition (moderation). Cross-sectional survey data from 420 manufacturing SMEs in Vietnam were collected during February–August 2025 and completed by authorized firm representatives (owners/directors/senior managers). Partial least squares structural equation modeling (SmartPLS 4.1) with 5,000 bootstraps was employed. Digital transformation (β = 0.304, p &lt; 0.01), logistics infrastructure (β = 0.289, p &lt; 0.01), and human capital (β = 0.284, p &lt; 0.001) are the strongest predictors; marketing capability (β = 0.124, p &lt; 0.01) and access to finance (β = 0.108, p &lt; 0.01) are positive. Absorptive capacity positively affects exports (β = 0.161, p &lt; 0.01) and mediates four determinants (the most significant for human capital, indirect β = 0.046, p &lt; 0.01). International competition strengthens the effect of human capital (β = 0.115, p &lt; 0.01) but weakens marketing capability (β = –0.102, p &lt; 0.01). The model explains 57.3% of the variance in export performance. These findings highlight the need for policies promoting digital adoption, logistics upgrades, and human-capital development, while firms should enhance learning capabilities and recalibrate marketing strategies under increasing competitive pressure.
The rise of online marketplaces has raised customer expectations regarding customization and lead time. It poses significant challenges to manufacturing firms and prompts a move from make-to-stock to a more flexible make-to-order system. Compared to make-to-stock settings, make-to-order systems cannot smooth fluctuations in demand using available stock. While viewing dynamic pricing as a useful strategy to balance supply with demand, many manufacturing firms can also create capacity flexibility. In that scenario, system costs could be cut by managing capacity and demand simultaneously. In this paper, we consider a make-to-order production environment with base and surge capacity as well as the ability to adjust product pricing. Our main focus is on operational decision-making, assuming that the base capacity and surge capacity are fixed, but activating the surge capacity incurs a setup cost. Initially, we propose a stochastic control model to reflect this complex decision problem. However, our initial model leads to an intractable dynamic programming problem. To overcome this, we convert the problem to a more tractable diffusion control problem. This approach helps to reveal the conditions under which utilizing flexible capacity is more advantageous than relying solely on fixed capacity. When flexible capacity is advantageous, we provide a solution to the diffusion control problem that can guide optimal capacity and price adjustments. We discover an interesting interplay between capacity adjustment and dynamic pricing. In particular, we find that the price, which aims at reducing congestion, may not monotonically increase with the congestion level when capacity adjustments incur a fixed cost.
<b>Background:</b> The emergence of chimeric antigen receptor T-cell (CAR-T) immunotherapy holds great promise in treating hematologic malignancies. While advancements in CAR design have enhanced therapeutic efficacy, the time-consuming manufacturing process has not been improved in the commercial production of CAR-T cells. In this study, we developed a “DASH CAR-T” process to manufacture CAR-T cells in 72 h and found the excelling anti-tumor efficacy of DASH CAR-T cells over conventionally manufactured CAR-T cells. <b>Methods:</b> Four different CAR-T manufacturing processes were first proposed and examined by flow cytometry in regard to cell viability, T-cell purity and activation, CAR expression, and cell apoptosis. The selected two processes, 48H DASH CAR-T and 72H DASH CAR-T, were applied to the subsequent functional assessments, including T-cell differentiation, antigen-dependent cytotoxicity and expansion, cytokines secretion profile, and in vivo anti-tumor efficacy. <b>Results:</b> We demonstrated that rapidly manufactured CAR-T cells generated within 48–72 h was feasible and exhibited increased naïve and memory T-cell ratios, a distinctive secretory profile, superior expansion capacity, and enhanced in vitro and in vivo anti-tumor activity compared to conventionally manufactured CAR-T cells. <b>Conclusions:</b> Our findings suggest that “DASH CAR-T” process is a valuable platform in reducing CAR-T manufacturing time and producing high-efficacy CAR-T cells for future clinical application.
The friction/adhesion between the tool and chip is generally large in metal cutting, and it causes many problems such as high cutting energy/rough surface finish. To suppress this, cutting fluid and tool coating are used in practice, but they are high in energy/cost and environmentally unfriendly. Therefore, this paper investigates the extraordinarily high-speed cutting (EHS cutting) mechanics of mainly soft and highly heat-conductive materials and proposes their application to solve the friction/adhesion problem in an environmentally friendly manner. In order to clarify the EHS cutting mechanics, a simple analytical model is constructed and experiments are conducted with measurement of the cutting temperature and forces. As a result, the following points are clarified/found: (1) heat softening at the secondary plastic deformation zone rather than the primary plastic deformation zone, (2) friction coefficient drop to 0.170 in EHS cutting, and (3) gradually increasing trend of cutting temperature in EHS cutting. Finally, EHS cutting is applied to dry cutting of aluminum alloys with a non-coated carbide tool and compared to conventional wet cutting with a DLC-coated carbide tool, and it is shown that a coating/coolant can be omitted in this region to achieve environmentally friendly cutting.
Luciana Santos Costa Vieira da Silva, Fabíola Kaczam, Deoclécio Júnior Cardoso da Silva
et al.
O objetivo deste artigo é desenvolver uma Revisão Sistemática de Literatura (RSL) sobre a relação entre inovação e desempenho financeiro em startups. Foram selecionados 49 artigos nas bases de dados Scopus e Web of Science. As análises foram apoiadas nas três leis da bibliometria clássica. O período de 2011 a 2020 foi definido para a elaboração deste estudo. Há necessidade de as startups adotarem uma cultura organizacional que adote práticas inovadoras e norteie o ambiente interno na adoção de comportamentos inovadores, bem como estreite as relações entre as universidades, incubadoras e fontes de financiamento com formação de alianças fortes para a promoção da inovação além de um amadurecimento maior nas redes de cooperação entre as empresas. A contribuição consiste em oferecer evidências sobre os resultados dos estudos, que podem sustentar a tomada de decisão de gestores de startups e gestores públicos, na criação de estratégias e políticas orientada a competitividade.
Production management. Operations management, Production capacity. Manufacturing capacity
The impact of technology on public transport has led to a new online transportation service. Its emergence makes the competition increasingly competitive. Therefore, customer loyalty becomes an important aspect of winning the competition. This research analyzed the effect of customer service, service delivery, onboard experience, public image, service value, and customer satisfaction on customer loyalty to online transportation. 517 respondents were obtained and divided into two groups: captive rider and choice rider. Data processing is carried out using a multigroup SEM technique. The results showed that there was a significant moderation effect of the different characteristics of users. In the captive rider group, onboard experience and service value did not affect customer satisfaction, and service value did not affect customer loyalty. Customer satisfaction influenced customer loyalty, and the effect was more robust than the choice rider group. In the choice rider group, the public image did not affect customer satisfaction, but service value influenced customer loyalty. Factors proven to influence customer loyalty significantly can be developed by companies to improve their competitive advantage in an increasingly competitive market of online transportation services.
Industrial engineering. Management engineering, Production capacity. Manufacturing capacity
The effects of a digital technologies uptake on firm efficiency in the Nigerian manufacturing sector were examined. The combined application of data envelopment analysis and the Tobit regression methods were employed to analyze the cross-sectional survey data derived from a sample of manufacturing firms. The research results showed that the uptake of digital technologies was still skewed to the low-end appliances/devices, whereas the uptake of the high-end digital technologies required to forge the digital transformation of firms was still low. Manufacturing firms in Nigeria need to make a quick transition to high-end digital technologies in order for them to increase their efficiency and competitiveness in the global marketplace. Challenges to the uptake of digital technologies need to be addressed as well. The training/retraining of personnel need be scaled up so as to build the digital capacity of the sector, bolster efficiency and improve the productivity of operations. The importation of digital devices may be an option in the short run, but local production should be ramped up in the long run.
Kimberley Rooney, Yu Dong, Alokesh Pramanik
et al.
The advent of additive manufacturing (AM) in Australian small and medium-sized enterprises offers the direct benefits of time-saving and labour cost-effectiveness for Australian manufacturing to be highly competitive in global markets. Australian local businesses can tailor their products to a diverse range of customers with a quicker lead time on the sophisticated design and development of products under good quality control in the whole advanced manufacturing process. This review outlines typical AM techniques used in Australian manufacturing, which consist of vat polymerisation (VP), environmentally friendly AM, and multi-material AM. In particular, a practical case study was also highlighted in the Australian jewellery industry to demonstrate how manufacturing style is integrated into their manufacturing processes for the purpose of reducing lead time and cost. Finally, major obstacles encountered in AM and future prospects were also addressed to be well positioned as a key player in the revolutionised Industry 4.0.
Wolfgang Tillmann, Dominic Stangier, Alexander Meijer
et al.
New manufacturing technologies, such as Sheet-Bulk Metal Forming, are facing the challenges of highly stressed tool surfaces which are limiting their service life. For this reason, the load-adapted design of surfaces and the subsurface region as well as the application of wear-resistant coatings for forming dies and molds made of high-speed steel has been subject to many research activities. Existing approaches in the form of grinding and conventional milling processes do not achieve the surface quality desired for the forming operations and therefore often require manual polishing strategies afterward. This might lead to an unfavorable constitution for subsequent PVD coating processes causing delamination effects or poor adhesion of the wear-resistant coatings. To overcome these restrictions, meso- and micromilling are presented as promising approaches to polishing strategies with varying grain sizes. The processed topographies are correlated with the tribological properties determined in an adapted ring compression test using the deep drawing steel DC04. Additionally, the influence of the roughness profile as well as the induced residual stresses in the subsurface region are examined with respect to their influence on the adhesion of a wear-resistant CrAlN PVD coating. The results prove the benefits of micromilling in terms of a reduced friction factor in the load spectrum of Sheet-Bulk Metal Forming as well as an improved coating adhesion in comparison to metallographic finishing strategies, which can be correlated to the processed roughness profile and induced compressive residual stresses in the subsurface region.
Sliding friction diamond burnishing is a finishing machining operation whose purpose is to improve the surface integrity of previously machined surfaces and increase their surface hardness. When analyzing a complex process involving plastic deformation, friction, and the interaction between solids, finite element models (FEMs) involve a significant amount of simplification. The aim of this study is to investigate a 2D FEM of the residual stress occurring during diamond burnishing. Before burnishing, the samples were processed by fine turning. Based on the simulations and laboratory experiments performed, it can be concluded that the diamond burnishing process can be modeled with relatively good approximation using two-dimensional modeling. It was also concluded that it is important to consider the initial surface topography in two-dimensional tests. The results indicate that the diamond burnishing process improved the residual stress properties of EN 1.4301 austenitic stainless steel by creating relatively high compressive stress, whose magnitude was between 629 and 1138 MPa depending on the applied force. However, the stress distribution is not uniform; it is mostly concentrated under the roughness peaks.
M. Jiménez‐Rosado, L. S. Zárate-Ramírez, A. Romero
et al.
Abstract Recently, bioplastic have generated an increasing interest as an alternative to conventional plastics. For this reason, their manufacture using the traditional techniques used for the production of plastics, such as extrusion, would help transferring bioplastics production to an industrial scale. In this way, the preparation of wheat gluten bioplastics by extrusion was the main objective of this research, modifying their structure by varying the pH value or by incorporating additives (glyoxal or xanthan gum). These bioplastics were characterized by the measurement of their mechanical properties and their water uptake capacity, proving that the modification of bioplastics cause variations in their properties. Thus, extrusion resulted in a greater gluten-plasticizer compatibility compared to compression, as denoted the temperature ramp tests, especially in the presence of additives (ie. Xanthan gum, glyoxal). Moreover, tensile strength was enhanced at pH 9, probably due to bonding promotion at alkaline conditions. These results demonstrate the great potential of these materials for the replacement of conventional plastics.
Ingrid Rebouças de Moura, Luís Henrique Gonçalves Costa, Enilson Medeiros dos Santos
et al.
A escolha de um aeroporto hub por uma empresa aérea garante uma série de benefícios relacionados à movimentação de passageiros, o que implica em um estudo detalhado quanto a demanda, localização geográfica e infraestrutura aeroportuária disponível para acomodar esse novo modelo de operação de voos. Neste sentido, este artigo tem como objetivo realizar um estudo quanto às principais características para que um aeroporto se estabeleça como um hub, firmando a importância que um componente tem sobre outro, como fator de instalação do sistema, na visão de especialistas. A metodologia da pesquisa está baseada na utilização do Analytical Hierarchy Process (AHP) para determinar a relevância dos componentes para escolha de um aeroporto hub. O resultado do trabalho caracteriza os principais indicadores e determina os critérios mais relevantes para a avaliação do potencial de um dado aeroporto para abrigar operações de hub.
Production management. Operations management, Production capacity. Manufacturing capacity
Benjamin James Ralph, Karin Hartl, Marcel Sorger
et al.
The shot peening process is a common procedure to enhance fatigue strength on load-bearing components in the metal processing environment. The determination of optimal process parameters is often carried out by costly practical experiments. An efficient method to predict the resulting residual stress profile using different parameters is finite element analysis. However, it is not possible to include all influencing factors of the materials’ physical behavior and the process conditions in a reasonable simulation. Therefore, data-driven models in combination with experimental data tend to generate a significant advantage for the accuracy of the resulting process model. For this reason, this paper describes the development of a grey-box model, using a two-dimensional geometry finite element modeling approach. Based on this model, a Python framework was developed, which is capable of predicting residual stresses for common shot peening scenarios. This white-box-based model serves as an initial state for the machine learning technique introduced in this work. The resulting algorithm is able to add input data from practical residual stress experiments by adapting the initial model, resulting in a steady increase of accuracy. To demonstrate the practical usage, a corresponding Graphical User Interface capable of recommending shot peening parameters based on user-required residual stresses was developed.
The article covers the tasks of developing practical skills of the students through cooperation between higher education institutions and manufacturing enterprises. It has been stated that practical skills are mainly formed by consolidating the acquired theoretical knowledge in the process of internship in production. There are shown purposes and processes which lead to achieve them. It has been emphasized that professional activity in students is formed by completing tasks that require complex skills. There are some recommendations for organizing and holding internship at a stand. This article is defined experimental works on progressing professional capacity in process of practical training. The changes in the evaluation process at the final stage of the production internship and the levels of mastery introduced are discussed. According to the students, the internship process in the production has intensively increased their professional and practical skills. It is stated that during the internship, students were divided into two groups and experimental work was carried out in these two groups. It is also stated that the theoretical knowledge acquired by students is intended to develop practical skills through practical training. During the internship the groups were divided into a control group and an experimental group. It is stated that the internship was organized among the students. It was noted that the practical training of students in the control groups was traditionally organized, and the internship of the experimental groups was improved.