Hasil untuk "Mechanical industries"

Michele T. Byrne, Y. Gun’ko

J. Atencia, D. Beebe

I. Yadroitsev, A. Gusarov, I. Yadroitsava et al.

A. Papadopoulos

L. F. Silva, A. Öchsner, R. Adams

Jun Li, C. Nagamani, Jeffrey S. Moore

A. Uriondo, M. Esperon-Miguez, S. Perinpanayagam

This paper reviews recent improvements in additive manufacturing technologies, focusing on those which have the potential to produce and repair metal parts for the aerospace industry. Electron beam melting, selective laser melting and other metal deposition processes, such as wire and arc additive manufacturing, are presently regarded as the best candidates to achieve this challenge. For this purpose, it is crucial that these technologies are well characterised and modelled to predict the resultant microstructure and mechanical properties of the part. This paper presents the state of the art in additive manufacturing and material modelling. While these processes present many advantages to the aerospace industry in comparison with traditional manufacturing processes, airworthiness and air transport safety must be guaranteed. The impact of this regulatory framework on the implementation of additive manufacturing for repair and production of parts for the aerospace industry is presented.

M. Pouranvari, S. Marashi

S. Sen, Shradha V Patil, D. Argyropoulos

M. Awalludin, O. Sulaiman, R. Hashim et al.

Hongye Zhao, Yi Zhao, Chengzhi Zhang

Academia and industry each possess distinct advantages in advancing technological progress. Academia's core mission is to promote open dissemination of research results and drive disciplinary progress. The industry values knowledge appropriability and core competitiveness, yet actively engages in open practices like academic conferences and platform sharing, creating a knowledge strategy paradox. Highly novel and publicly accessible knowledge serves as the driving force behind technological advancement. However, it remains unclear whether industry or academia can produce more novel research outcomes. Some studies argue that academia tends to generate more novel ideas, while others suggest that industry researchers are more likely to drive breakthroughs. Previous studies have been limited by data sources and inconsistent measures of novelty. To address these gaps, this study conducts an analysis using four types of fine-grained knowledge entities (Method, Tool, Dataset, Metric), calculates semantic distances between entities within a unified semantic space to quantify novelty, and achieves comparability of novelty across different types of literature. Then, a regression model is constructed to analyze the differences in publication novelty between industry and academia. The results indicate that academia demonstrates higher novelty outputs, which is particularly evident in patents. At the entity level, both academia and industry emphasize method-driven advancements in papers, while industry holds a unique advantage in datasets. Additionally, academia-industry collaboration has a limited effect on enhancing the novelty of research papers, but it helps to enhance the novelty of patents. We release our data and associated codes at https://github.com/tinierZhao/entity_novelty.

Sae Young Moon, Myeongjun Erik Jang, Haoyan Luo et al.

Topic modeling has extensive applications in text mining and data analysis across various industrial sectors. Although the concept of granularity holds significant value for business applications by providing deeper insights, the capability of topic modeling methods to produce granular topics has not been thoroughly explored. In this context, this paper introduces a framework called TIDE, which primarily provides a novel granular topic modeling method based on large language models (LLMs) as a core feature, along with other useful functionalities for business applications, such as summarizing long documents, topic parenting, and distillation. Through extensive experiments on a variety of public and real-world business datasets, we demonstrate that TIDE's topic modeling approach outperforms modern topic modeling methods, and our auxiliary components provide valuable support for dealing with industrial business scenarios. The TIDE framework is currently undergoing the process of being open sourced.

Chao Li, Jiawei He, Tingzhe Pan et al.

As renewable energy penetration continues to rise, enhancing power system flexibility has become a critical requirement. Photovoltaic–storage–charging stations (PSCSs) are key components for enhancing local regulation capability and promoting renewable integration. However, evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge. This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary (PEB) model. Then, an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region (AFR) model, which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy. To solve this formulation, it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution. Finally, a multi-station adjustable capability aggregation method considering security constraints is introduced. Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries, providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.

Yunjie Yang, Junxin Chen, Sai Liu et al.

Proton exchange membranes (PEMs) play a central role in determining the efficiency, durability, and operational flexibility of PEM fuel cells (PEMFCs). However, conventional PEMs exhibit strong temperature-dependent proton-transport behavior, which limits their ability to support both rapid start-up at low temperatures and stable operation at elevated temperatures. Water-mediated PEMs show excellent conductivity under low-temperature and high-humidity conditions but suffer from dehydration and structural instability in the high-temperature regime. In contrast, water-independent PEMs, particularly phosphoric-acid-doped systems, conduct protons efficiently under anhydrous high-temperature conditions yet experience acid leaching that hampers room-temperature start-up and long-term durability. This review summarizes the fundamental proton-transport mechanisms that govern temperature-dependent performance and discusses recent advances in materials design aimed at enabling wide-temperature-range PEM operation. For water-mediated membranes, strategies such as incorporating hydrophilic fillers, constructing confined hydrophilic domains, and introducing additional proton-transfer sites have been developed to mitigate water loss and stabilize proton conduction. For water-independent membranes, approaches including strengthening polymer–acid interactions, engineering nanoscale confinement, designing multilayer architectures, and constructing multi–proton-carrier networks effectively improve acid retention and broaden operational temperature windows. Emerging fixed-carrier systems based on phosphonic-acid-grafted polymers, metal–organic frameworks, and covalent organic frameworks offer new pathways for stable anhydrous proton conduction across a wide temperature range. We conclude by outlining key challenges and future research opportunities, including reducing the dependence on volatile or leachable proton carriers, developing adaptive nanochannel architectures, improving anhydrous high-temperature conduction, and establishing scalable membrane fabrication methods. Continued innovation in these directions is expected to enable next-generation wide-temperature-range PEMs capable of flexible, high-efficiency operation from sub-zero to high-temperature conditions.

Kikmo Wilba Christophe, Mah Charitos Serges, Abanda Andre et al.

We present a novel integrated multiscale, multiphysics, and data-driven framework for predictive modeling and process optimization of glass fiber cable composites. Our hybrid model synergistically couples physics-based simulations with machine learning corrections through a regularized monolithic formulation, ensuring consistency with governing equations and experimental data. This coupling significantly reduces predictive uncertainty, achieving up to a 25% improvement in curing kinetics calibration and a 40% decrease in porosity-related defects compared to traditional models, while accurately capturing thermo-chemo-mechanical fields. We validate our numerical simulations against high-fidelity datasets and demonstrate concurrent optimization of stiffness, lightweight performance, and structural durability. Our methodology enables reliable, adaptive modeling and intelligent control of advanced composite manufacturing processes, thereby laying the groundwork for next-generation design and monitoring strategies in aerospace, automotive, and space industries.

Danny Awty‐Carroll, Paul R. H. Robson, Kai‐Uwe Schwarz et al.

ABSTRACT More and new sources of biomass are needed for renewable energy and renewable products for the bioeconomy. A leading new source of biomass is the highly sustainable perennial grass crop Miscanthus. The majority of the Miscanthus crop comprises a clone of Miscanthus × giganteus (M × g) of limited genetic variation and poor yield under dry growth conditions. The parental species of M × g, M. sacchariflorus and M. sinensis, are distributed over a large geographical range in Eastern Asia and may be used to improve on M × g. From breeding trials, we selected seven novel hybrids and two control genotypes including M × g. We grew these in a field experiment on drought‐prone soil in Germany with and without irrigation. To identify superior Miscanthus types, we estimated radiation use efficiency (RUE), yield and water use efficiency (WUE) from within‐season measurements made over three contrasting growing seasons. Temporal variations in RUE and WUE for different genotypes varied significantly and two novel hybrids, WAT6 and WAT8, achieved the highest yields. To achieve goodness of fit to yield measurements, genotype‐specific parameters for process descriptions in the model MiscanFor were adjusted for the two superior genotypes. These parameters included earlier shooting and an increased threshold of overheating. When the model was run over ten years, despite generating the highest yield values, WAT8 accumulated less biomass than WAT6 over the longer term. The response of WUE to variation in soil capillary pressure and vapour pressure deficit was examined. WUE of M × g increased with the severity of water stress then declined again. The superior yielding genotypes were more able to sustain biomass accumulation and/or water use under the highest stress. We believe that combining physiology with crop modelling is a powerful way to inform genetic and agronomic improvements needed to secure the future supply of biomass for the bioeconomy.

A. Karimzadeh, M. Aliofkhazraei, F. Walsh

Abstract Ni Co alloy electrodeposits have been widely employed in industry due to their good corrosion and wear resistance, high mechanical strength, moderate thermal conductivity and outstanding electrocatalytic and magnetic properties. This review aims to provide an insight into the mechanism of electrodeposition and effect of operational parameters and deposit microstructure, together with the mechanical, electrochemical and tribological characteristics of Ni Co alloys and included particle, composite deposits. Potential applications of the coatings have also been considered in applications as diverse as additive manufacturing, micro-tools, micro-sensors, electronic imaging and electrochemical energy conversion.

João Reis, N. Melão, Juliana Salvadorinho et al.

Abstract Services are changing at an impressive pace boosted by the technological advances felt in Robotics, Big Data, and Artificial Intelligence (AI) that have uncovered new research opportunities. Our objective is to contribute to the literature by exploring the pros and cons of the use of service robots in the hospitality industry and to practice, by presenting the architectural and technological characteristics of a fully automated plant based on a relevant case. To achieve such goal, this article uses a systematic literature review to assess the state-of-the-art, characterize the unit of analysis, and find new avenues for further research. The results indicate that, in high customer contact settings, service robots tend to outperform humans when performing standardized tasks, because of their mechanical and analytical nature. Evidence also shows that, in some cases, service robots have not yet achieved the desired technological maturity to proficiently replace humans. In other words, the technology is not quite there yet, but this does not contradict the fact that new robot technologies, enabled by AI, will be able to replace the employees’ empathetic intelligence. In practical terms, organizations are facing challenges where they have to decide whether service robots are capable of completely replacing human labor or if they should rather invest in balanced options, such as human-robot systems, that seem to be a much more rational choice today.

Shuai Li, Chen Yizhe, Li Dong et al.

The application of artificial intelligence (AI) in industry is accelerating the shift from traditional automation to intelligent systems with perception and cognition. Vision language-action (VLA) models have been a key paradigm in AI to unify perception, reasoning, and control. Has the performance of the VLA models met the industrial requirements? In this paper, from the perspective of industrial deployment, we compare the performance of existing state-of-the-art VLA models in industrial scenarios and analyze the limitations of VLA models for real-world industrial deployment from the perspectives of data collection and model architecture. The results show that the VLA models retain their ability to perform simple grasping tasks even in industrial settings after fine-tuning. However, there is much room for performance improvement in complex industrial environments, diverse object categories, and high precision placing tasks. Our findings provide practical insight into the adaptability of VLA models for industrial use and highlight the need for task-specific enhancements to improve their robustness, generalization, and precision.

Rania Ahmed, Eman Ahmed, Ahmed Elbarbary et al.

The fashion industry is an extremely profitable market that generates trillions of dollars in revenue by producing and distributing apparel, footwear, and accessories. This systematic literature review (SLR) seeks to systematically review and analyze the research landscape about the Generative Artificial Intelligence (GAI) and metaverse in the fashion industry. Thus, investigating the impact of integrating both technologies to enhance the fashion industry. This systematic review uses the Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology, including three essential phases: identification, evaluation, and reporting. In the identification phase, the target search problems are determined by selecting appropriate keywords and alternative synonyms. After that 578 documents from 2014 to the end of 2023 are retrieved. The evaluation phase applies three screening steps to assess papers and choose 118 eligible papers for full-text reading. Finally, the reporting phase thoroughly examines and synthesizes the 118 eligible papers to identify key themes associated with GAI and Metaverse in the fashion industry. Based on Strengths, Weaknesses, Opportunities, and Threats (SWOT) analyses performed for both GAI and metaverse for the fashion industry, it is concluded that the integration of GAI and the metaverse holds the capacity to profoundly revolutionize the fashion sector, presenting chances for improved manufacturing, design, sales, and client experiences. Accordingly, the research proposes a new framework to integrate GAI and metaverse to enhance the fashion industry. The framework presents different use cases to promote the fashion industry using the integration. Future research points for achieving a successful integration are demonstrated.