Hasil untuk "Production capacity. Manufacturing capacity"

Shivnath Tathe

Fixed representational capacity is a fundamental constraint in continual learning: practitioners must guess an appropriate model width before training, without knowing how many distinct concepts the data contains. We propose LACE (Loss-Adaptive Capacity Expansion), a simple online mechanism that expands a model's representational capacity during training by monitoring its own loss signal. When sustained loss deviation exceeds a threshold - indicating that the current capacity is insufficient for newly encountered data - LACE adds new dimensions to the projection layer and trains them jointly with existing parameters. Across synthetic and real-data experiments, LACE triggers expansions exclusively at domain boundaries (100% boundary precision, zero false positives), matches the accuracy of a large fixed-capacity model while starting from a fraction of its dimensions, and produces adapter dimensions that are collectively critical to performance (3% accuracy drop when all adapters removed). We further demonstrate unsupervised domain separation in GPT-2 activations via layer-wise clustering, showing a U-shaped separability curve across layers that motivates adaptive capacity allocation in deep networks. LACE requires no labels, no replay buffers, and no external controllers, making it suitable for on-device continual learning under resource constraints.

Yukitaka Ito, Sou Nakamura, N. Sugimoto et al.

The ex vivo generation of platelets from human-induced pluripotent cells (hiPSCs) is expected to compensate donor-dependent transfusion systems. However, manufacturing the clinically required number of platelets remains unachieved due to the low platelet release from hiPSC-derived megakaryocytes (hiPSC-MKs). Here, we report turbulence as a physical regulator in thrombopoiesis in vivo and its application to turbulence-controllable bioreactors. The identification of turbulent energy as a determinant parameter allowed scale-up to 8 L for the generation of 100 billion-order platelets from hiPSC-MKs, which satisfies clinical requirements. Turbulent flow promoted the release from megakaryocytes of IGFBP2, MIF, and Nardilysin to facilitate platelet shedding. hiPSC-platelets showed properties of bona fide human platelets, including circulation and hemostasis capacities upon transfusion in two animal models. This study provides a concept in which a coordinated physico-chemical mechanism promotes platelet biogenesis and an innovative strategy for ex vivo platelet manufacturing.

Mustika Mustika, Nurhayati, Muh Dahkan Thalib

Purpose: This study aims to reconceptualize linear programming not merely as a technical optimization tool, but as an analytical framework for ethical deliberation in faith-based manufacturing organizations. Existing operations research literature predominantly emphasizes efficiency and cost minimization, while religious studies often examine ethical values without formal decision models. This study addresses the gap between these domains by exploring how production constraints function simultaneously as operational limits and moral boundaries shaped by religious doctrines and faith-based organizational norms within managerial decision-making. Method: The research employs a quantitative operations research approach through a constraint-based linear programming model of production scheduling. The objective function minimizes production cost, while constraints represent capacity, labor availability, and demand requirements. A representative faith-based manufacturing context is used to illustrate model formulation and solution interpretation. Rather than focusing solely on optimal numerical outcomes, the analysis emphasizes the role of binding constraints as sites of ethical consideration, where managerial decisions must balance efficiency objectives with institutional religious commitments. Findings: The findings reveal that binding constraints exert a decisive influence on production decisions, not only by limiting feasible solutions but also by shaping ethical trade-offs faced by managers. The results indicate that efficiency gains are negotiated within predefined moral boundaries, where certain technically optimal options are constrained by religious commitments. This demonstrates that linear programming models can illuminate how ethical considerations are embedded within operational structures rather than treated as external or abstract norms. Significance: This study contributes to religious-oriented operations research by integrating formal optimization models with ethical analysis grounded in faith-based organizational contexts. By framing constraints as moral as well as technical determinants, the study extends the interpretive scope of linear programming and offers a novel analytical bridge between operations research systems and religious studies. The findings provide meaningful insights for scholars and practitioners seeking to align operational efficiency with religious and ethical accountability.

Roland Wölfle, Irina Saur-Amaral, Leonor Teixeira

The development of personalized drugs introduces new uncertainties and risks in production machinery design, which can be mitigated through structured workflows. As the commonly used V-Model approach has limitations in dealing with complex multi-domain problems, it is essential to address traceability and relationships between requirements and solutions in a regulated environment to ensure product quality. This study focuses on the conceptual design phase and develops a design methodology called the Case-based Axiomatic Design Assistant (CADA) to address this type of problem. It takes, as a starting point, Axiomatic Design (AD), due to its simplicity and graphical tools for quality evaluation, and Case-Based Reasoning (CBR), due to its capacity to integrate data structures and continuously improve. This combination is put into practice through a visual assistant that utilizes a knowledge graph to represent design elements comprehensively. This article describes the development, implementation, and testing process of CADA, which includes examples of the conceptual design for pharmaceutical manufacturing. The proposed CADA method facilitates systematic requirements analysis, structured reasoning, and solution evaluation, and overcomes the limitations of previous methodologies. It represents a novel approach with an intuitive workflow and advanced graphical capabilities, exemplified in the context of a conceptual design for pharmaceutical manufacturing. The inclusion of intrinsic data labeling capabilities and inference visualization enhances its relevance.

Cameron Webb, S. Ip, N. V. Bathula et al.

The coronavirus disease of 2019 (COVID-19) pandemic launched an unprecedented global effort to rapidly develop vaccines to stem the spread of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2). Messenger ribonucleic acid (mRNA) vaccines were developed quickly by companies that were actively developing mRNA therapeutics and vaccines for other indications, leading to two mRNA vaccines being not only the first SARS-CoV-2 vaccines to be approved for emergency use but also the first mRNA drugs to gain emergency use authorization and to eventually gain full approval. This was possible partly because mRNA sequences can be altered to encode nearly any protein without significantly altering its chemical properties, allowing the drug substance to be a modular component of the drug product. Lipid nanoparticle (LNP) technology required to protect the ribonucleic acid (RNA) and mediate delivery into the cytoplasm of cells is likewise modular, as are technologies and infrastructure required to encapsulate the RNA into the LNP. This enabled the rapid adaptation of the technology to a new target. Upon the coattails of the clinical success of mRNA vaccines, this modularity will pave the way for future RNA medicines for cancer, gene therapy, and RNA engineered cell therapies. In this review, trends in the publication records and clinical trial registrations are tallied to show the sharp intensification in preclinical and clinical research for RNA medicines. Demand for the manufacturing of both the RNA drug substance (DS) and the LNP drug product (DP) has already been strained, causing shortages of the vaccine, and the rise in development and translation of other mRNA drugs in the coming years will exacerbate this strain. To estimate demand for DP manufacturing, the dosing requirements for the preclinical and clinical studies of the two approved mRNA vaccines were examined. To understand the current state of mRNA-LNP production, current methods and technologies are reviewed, as are current and announced global capacities for commercial manufacturing. Finally, a vision is rationalized for how emerging technologies such as self-amplifying mRNA, microfluidic production, and trends toward integrated and distributed manufacturing will shape the future of RNA manufacturing and unlock the potential for an RNA medicine revolution.

C. Ghisetti, S. Mancinelli, M. Mazzanti et al.

Ali Tahmasbi, Jean Brice Mandatsy Moungomo, Agnes M. Samuel et al.

The present study focuses on the dry and wet end milling of three distinct Aluminum 7075 alloys: A7075, A7075–Sc (with a 0.18% Sc addition), and A7075–Li–Sc (containing 2.2% Li and 0.18% Sc additions). The main objective is to explore how cutting parameters (cutting speed and feed rate), heat treatment, alloy composition, and cooling methods influence A lcutting force. In the initial phase of the investigation, all three alloys underwent heat treatment. Subsequently, the machining process centered on the softest and hardest conditions, aiming at analyzing the impact of hardness on machinability behavior of the three studied alloys, using the same milling tool and a consistent depth of cut under both dry and wet conditions. The investigations also highlight the role of Li and Sc additions on the quality of surface finish, as well as burr and chip formation. In total, a sum of 108 operations have been performed on the present alloys.

Johannes Friedlein, Max Böhnke, Malte Schlichter et al.

Similar to bulk metal forming, clinch joining is characterised by large plastic deformations and a variety of different 3D stress states, including severe compression. However, inherent to plastic forming is the nucleation and growth of defects, whose detrimental effects on the material behaviour can be described by continuum damage models and eventually lead to material failure. As the damage evolution strongly depends on the stress state, a stress-state-dependent model is utilised to correctly track the accumulation. To formulate and parameterise this model, besides classical experiments, so-called modified punch tests are also integrated herein to enhance the calibration of the failure model by capturing a larger range of stress states and metal-forming-specific loading conditions. Moreover, when highly ductile materials are considered, such as the dual-phase steel HCT590X and the aluminium alloy EN AW-6014 T4 investigated here, strong necking and localisation might occur prior to fracture. This can alter the stress state and affect the actual strain at failure. This influence is captured by coupling plasticity and damage to incorporate the damage-induced softening effect. Its relative importance is shown by conducting inverse parameter identifications to determine damage and failure parameters for both mentioned ductile metals based on up to 12 different experiments.

Steffen Globisch, Markus Friedrich, Nils Heidemann et al.

In tool and mold making, components are typically first pre-machined in a soft state with residual stock allowance, as economical production is not possible in a hardened state due to the enormous tool wear. This extends the process chain and therefore also the throughput times. This paper presents an innovative tool concept for a solid carbide end mill in order to be able to carry out roughing and finishing in a hardened state. First, the structure of the innovative solid carbide end mill is described. Afterwards, the results of experimental tests are presented and discussed. These describe the suitability of the tool concept and include further investigations that examine the influence of the helix angle on the process behavior during the machining of the tool steel Toolox 44. To evaluate the process behavior, the development of process forces, chip formation, tool wear and component quality over the tool life are analyzed.

Irina Sviridova, Hendrik Holling, Wenchao Tang et al.

This paper presents a comprehensive analysis of the utilization of 3D printing technology for the fabrication of ceramic shells in the context of investment casting. This study encompasses an exploration of various 3D printing techniques such as binder jetting technology and lithography-based ceramic manufacturing applied to ceramic materials tailored for investment casting applications for different materials. Comparative analyses between conventionally manufactured shells and those produced through 3D printing techniques are presented, shedding light on the potential advantages and challenges associated with the adoption of additive manufacturing in investment casting processes. The findings of this study reveal that both methods offer viable solutions for creating ceramic materials suitable as shells for investment casting. Both lithography-based ceramic manufacturing and binder jetting technology exhibit unique advantages and challenges. Lithography-based ceramic manufacturing demonstrates a superior surface finish and resolution, making it particularly suitable for intricate designs and fine details. On the other hand, binder jetting technology presents advantages in terms of speed and scalability, allowing for the rapid production of larger components.

Fangqi Li, Haodong Zhao, Wei Du et al.

To trace the copyright of deep neural networks, an owner can embed its identity information into its model as a watermark. The capacity of the watermark quantify the maximal volume of information that can be verified from the watermarked model. Current studies on capacity focus on the ownership verification accuracy under ordinary removal attacks and fail to capture the relationship between robustness and fidelity. This paper studies the capacity of deep neural network watermarks from an information theoretical perspective. We propose a new definition of deep neural network watermark capacity analogous to channel capacity, analyze its properties, and design an algorithm that yields a tight estimation of its upper bound under adversarial overwriting. We also propose a universal non-invasive method to secure the transmission of the identity message beyond capacity by multiple rounds of ownership verification. Our observations provide evidence for neural network owners and defenders that are curious about the tradeoff between the integrity of their ownership and the performance degradation of their products.

Tomasz Grzywny, Julia Lenczewska

In this article, we introduce and study capacities related to nonlocal Sobolev spaces, with focus on spaces corresponding to zero-order nonlocal operators. In particular, we prove Hardy-type inequalities to obtain Sobolev embeddings and use them to estimate the nonlocal capacities of a ball.

Martina Calzavara, D. Battini, D. Bogataj et al.

The workforce ageing phenomenon is recently affecting most of the Organisation for Economic Co-operation and Development (OECD) member countries, due to a general ageing of their populations and a higher average retirement age of the workforce. In this paper, the topic of ageing workforce management is addressed from a production research standpoint, with the aim of understanding how older workers can be supported and involved in a manufacturing system. First, the current state of the art related to the ageing workforce in production systems is presented. This is structured according to four main topics: (1) analysis and evaluation of ageing workers’ functional capacities, (2) consideration of ageing workers’ capacities in industrial system modelling and management, (3) analysis and exploitation of ageing workers’ expertise, (4) acknowledgement, analysis, design and integration of supporting technologies. Next, the discussion on the impact of the ageing workforce on manufacturing systems’ performances leads to the comparison of some technological advances that are related to the Industry 4.0 paradigms. Finally, a future research agenda on this topic is proposed, based on the same topics classification proposed for the literature analysis. Five different research areas are derived, suggesting future directions for appropriate research concerning the employ of older workers in production environments.

E. Kallitsis, A. Korre, G. Kelsall et al.

Abstract Advances in lithium-ion battery (LIB) technology, offering higher mass specific energies, volumetric energy densities, potential differences and energy efficiencies, are key enablers of the large-scale uptake of electric vehicles (EVs). Nickel-cobalt-manganese oxide (NCM) cathode formulations have emerged as the dominant choice in the battery industry. Further performance improvements are expected from the introduction of silicon-graphite composite anodes and nickel-rich cathodes alongside cost reductions achieved through upscaling the battery manufacturing. This work presents results of life cycle assessments concerning the environmental burdens associated with the production of novel electrode batteries and the impacts of the Chinese domination in lithium-ion battery manufacturing. The production of LIBs in China was shown to come at a high environmental cost of 40% higher Global Warming Potential (GWP) than earlier literature suggests. The novel batteries were shown to exhibit similar threats to humans and ecosystems as the commercialised ones, occurring mainly from the metals used in the battery cells; environmental impact reductions are shown to occur as a result of the increased nominal storage capacities of novel battery technologies. The replicable model presented provides the means to quantify the environmental impacts of production of LIBs including those with novel electrode chemistries and offers robust means of decision making that complement scientific and engineering developments targeting LIB performance improvements and cost reductions.

M. Nowroozipour, R. Tabatabaei koloor, A. Motevali

IntroductionThe world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly in light of the pressing need to mitigate environmental impact and promote the use of renewable energy. The purpose of this research is to investigate and compare the environmental effects of electricity production from two wind power plants, Aqkand and Kahak, using wind turbines with a capacity of 2.5 megawatts for a period of three different lifetimes (20, 25, and 30 years).Materials and MethodsThe present study investigates the environmental effects of electricity generation during the life cycle of wind farms (Kahak and Aqkand) during the construction and operation of these power plants and the cumulative exergy demand index. The specifications of the wind turbines used in the current research are: turbine capacity of 2.5 MW, rotor diameter of 103 meters, rotor weight of 56 tonnes, three blades, each blade is 50.3 meters long and weighs 34.8 tonnes. The turbines are manufactured by Mapna and used in dry conditions. A functional unit of one kilowatt of electricity was selected and the data were analyzed in SIMAPRO software using IMPACT2002+ method with 15 midpoint indicators and four final indicators.Results and DiscussionThe results showed that the stage of raw materials and production has the highest impact on the creation of midpoint indicators, which is due to extraction, manufacturing, and production of parts such as steel casting using non-renewable energy and activities such as high-temperature welding. The total environmental index of Aqkand and Kahak wind power plants for 1 kWh of generated electricity was 5.84 and 4.45 μPt respectively, more than half of which belongs to the damage to human health category. The investigation of the ionizing radiation index showed that the use of diesel fuel in the installation phase resulted in the highest amount of emissions in both of the power plants, so the share of pollutant emissions in the raw materials and production phase is more than 40%, and in the installation phase due to diesel fuel consumption was more than 48%. The investigation of the eutrophication index showed that the raw materials and production stage accounted for more than 95% of the damage to the ecosystem quality category, and in the meantime, copper and electrical components had the highest amount of contribution to the raw materials and production stage. Additionally, diesel fuel accounted for the largest part of the result in the installation stage, and the transportation and maintenance stage included less than 1% of this result. The investigation of the renewable energy consumption index showed that the stage of raw materials and turbine production in the Aqkand power plant with a share of 68% and the Kahak power plant with a share of 70% had the greatest effect on the category of resource damage. Also, the installation and commissioning phase was the second most effective factor in the category of resource damage due to the use of diesel fuel. The study of the cumulative exergy demand index showed that non-renewable-fossil resources had the largest share in exergy demand (0.15 MJ) to produce one kilowatt of electricity generated from power plants.ConclusionIn this study, the results showed that in both plants, about 70% of various respiratory effects, 60% of human health issues, and 25% of acidification and global warming are caused in the raw materials and manufacturing phase. Furthermore, the installation phase is responsible for 17% and 16% of climate change in the Aqkand and Kahak power plants respectively, and between 14% and 26% of other environmental factors.

Niklas Grambow, Lennart Hinz, Christian Bonk et al.

The increasing demand for electric drives challenges conventional powertrain designs and requires new technologies to increase production efficiency. Hairpin stator manufacturing technology enables full automation, and quality control within the process is particularly important for increasing the process capacity, avoiding rejects and for safety-related aspects. Due to the complex, free-form geometries of hairpin stators and the required short inspection times, inline reconstruction and accurate quantification of relevant features is of particular importance. In this study, we propose a novel method to estimate the creepage distance, a feature that is crucial regarding the safety standards of hairpin stators and that could be determined neither automatically nor accurately until now. The data acquisition is based on fringe projection profilometry and a robot positioning system for a highly complete surface reconstruction. After alignment, the wire pairs are density-based clustered so that computations can be parallelized for each cluster, and an analysis of partial geometries is enabled. In several further steps, stripping edges are segmented automatically using a novel approach of spatially asymmetric windowed local surface normal variation, and the creepage distances are subsequently estimated using a geodesic path algorithm. Finally, the approach is examined and discussed for an entire stator, and a methodology is presented that enables the identification of implausible estimated creepage distances.

Juan Carlos Pereira, Mari Carmen Taboada, Andrea Niklas et al.

Nickel-based Ni-Cr-Si-B self-fluxing alloys are excellent candidates to replace cobalt-based alloys in aeronautical components. In this work, metal additive manufacturing by directed energy deposition using a laser beam (DED-LB, also known as LMD) and gas-atomized powders as a material feedstock is presented as a potential manufacturing route for the complex processing of these alloys. This research deals with the advanced material characterization of these alloys obtained by LMD and the study and understanding of their solidification paths and strengthening mechanisms. The as-built microstructure, the Vickers hardness at room temperature and at high temperatures, the nanoindentation hardness and elastic modulus of the main phases and precipitates, and the strengthening mechanisms were studied in bulk cylinders manufactured under different chemical composition grades and DED-LB/p process parameter sets (slow, normal, and fast deposition speeds), with the aim of determining the influence of the chemical composition in commercial Ni-Cr-Si-Fe-B alloys. The hardening of Ni-Cr-Si-Fe-B alloys obtained by LMD is a combination of the solid solution hardening of gamma nickel dendrites and eutectics and the contribution of the precipitation hardening of small chromium-rich carbides and hard borides evenly distributed in the as-built microstructure.

Mona A. Aboueleaz, Noha Naeim, Islam H. Abdelgaliel et al.

This research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI 316 with those obtained for AISI 304, as previously reported in the literature. The experimental work is conducted through a full factorial experimental design of five running parameters with different levels: applied voltage, transverse feed, pulse-on/pulse-off times and current intensity. The machined workpieces are analyzed using an image processing technique in order to evaluate the size of cut slots to allow the calculation of the MRR. Followed by the characterization of the surface roughness along the side walls of the slots. Different mathematical regression techniques were developed to represent the multi-response of both materials using the MATLAB regression toolbox. It was found that WEDM process parameters have a fuzzy influence on the responses of both material models. This allowed for multi-objective optimization of the regression models using four different techniques: multi-objective genetic algorithm (MOGA), multi-objective pareto search algorithm (MOPSA), weighted value grey wolf optimizer (WVGWO) and osprey optimization algorithm (OOA). The optimization results reveal that the optimal WEDM parameters of each response are inconsistent to the others. Hence, the optimal results are considered a compromise between the best results of different responses. Noteworthily, the multi-objective pareto search algorithm outperformed the other candidates. Eventually, the optimal results of both materials share the high voltage, high transverse feed rate and low pulse-off time parameters; however, AISI 304 requires low pulse-on time and current intensity levels while AISI 316 optimal results entail higher pulse-on time and current levels.

Guilherme Pelegrini Brianez, Omar Jorge Sabbag

A pecuária leiteira é importante atividade do agronegócio brasileiro que apresenta desafios devido à heterogeneidade no perfil das propriedades, alto custo operacional e baixo retorno financeiro para a maioria dos pequenos produtores. O presente trabalho tem por objetivo avaliar a eficiência técnica de 12 propriedades leiteiras em regiões do estado de São Paulo, por meio da Análise Envoltória de Dados (DEA). Verificou-se relação de inovação tecnológica e não tecnológica nos índices de produção leiteira. As variáveis do estudo foram a produtividade diária de leite, área (hectares), número de animais lactantes e mão de obra. Assim, 33% das propriedades foram consideradas eficientes e 67%, ineficientes. Conclui-se que a capacitação técnica é diferencial, bem como o estímulo ao desenvolvimento tecnológico, não tecnológico e gerencial de forma individual e coletiva. Entidades públicas e privadas também são importantes para o avanço e para promover maior sustentabilidade aos produtores de leite.

Saurabh Amin, Patrick Jaillet, Haripriya Pulyassary et al.

We study a market mechanism that sets edge prices to incentivize strategic agents to efficiently share limited network capacity. In this market, agents form coalitions, with each coalition sharing a unit capacity of a selected route and making payments to cover edge prices. Our focus is on the existence and computation of market equilibrium, where challenges arise from the interdependence between coalition formation among strategic agents with heterogeneous preferences and route selection that induces a network flow under integral capacity constraints. To address this interplay between coalition formation and network capacity utilization, we introduce a novel approach based on combinatorial auction theory and network flow theory. We establish sufficient conditions on the network topology and agents' preferences that guarantee both the existence and polynomial-time computation of a market equilibrium. Additionally, we identify a particular market equilibrium that maximizes utilities for all agents and the outcome is equivalent to the classical Vickrey-Clarke-Groves mechanism. Furthermore, we extend our results to multi-period settings and general networks, showing that when the sufficient conditions are not met, an equilibrium may still exist but requires more complex, path-based pricing mechanisms that set differentiated prices based on agents' preference parameters.