Hasil untuk "Production capacity. Manufacturing capacity"

Rafael P. Ferreira, Vinicius Lemes Jorge, Emil Schubert et al.

The performance of Gas Metal Arc-Directed Energy Deposition (GMA-DED) strongly depends on efficient path-planning strategies that balance trajectory quality and computational cost. With the purpose of developing a computationally faster and more scalable path-planning approach, this study introduces the Fast Advanced-Pixel strategy by integrating the <i>K</i>-means clustering algorithm into to the Advanced Pixel strategy version to reduce the dimensionality of an optimization problem. Computational validation was conducted on four geometrically distinct parts using different clustering configurations. Statistical analysis (ANOVA) was applied to assess the significance of the results. The findings revealed that by increasing the number of clusters, computational time is substantially reduced, achieving up to a twenty-fold improvement compared with the former strategy, while maintaining consistent trajectory quality. Experimental validation using complex parts, such as a “Jaw Gripper” and a “C-frame” of a resistance spot welding gun, confirmed defect-free deposition and dimensional agreement with the CAD models. Accordingly, within the scope of GMA-DED technology and pixel-based path-planning strategies, the Fast Advanced-Pixel approach demonstrates a significant improvement in computational efficiency while preserving trajectory quality, enabling the accurate and reliable fabrication of geometrically complex metallic parts.

Fuad Hasan, Abderrachid Hamrani, Tyler Dolmetsch et al.

Wire-directed energy deposition (W-DED) produces steep thermal gradients and rapid heating-cooling cycles due to the moving heat source, where modest variations in process parameters significantly alter heat input per unit length and therefore the full thermal history. This sensitivity makes process tuning by trial-and-error or repeated FE sweeps expensive, motivating inverse analysis. This work proposes an inverse thermal process design framework that couples single-track experiments, a calibrated finite element (FE) thermal model, and a parametric physics-informed neural network (PINN) surrogate. By using experimentally calibrated heat-loss physics to define the training constraints, the PINN learns a parameterized thermal response from physics alone (no temperature data in the PINN loss), enabling inverse design without repeated FE runs. Thermocouple measurements are used to calibrate the convection film coefficient and emissivity in the FE model, and those parameters are used to train a parametric PINN over continuous ranges of arc power (1.5–3.0 kW) and travel speed (0.005–0.015 m/s) without using temperature data in the loss function. The trained PINN model was validated against the calibrated FE model at 3 probe locations with different power and travel speed combinations. Across these benchmark conditions, the mean absolute errors are between 6.5–17.4 °C, with cooling-tail errors ranging from 1.8–12.1 °C. The trained surrogate is then embedded in a sampling-based inverse optimization loop to identify power-speed combinations that achieve prescribed interlayer temperatures at a fixed dwell time. For target interlayer temperatures of 100, 130, and 160 °C with a 10 s dwell time, the optimized solutions remain within 3.3–5.6 °C of the target according to the PINN, while FE verification is within 4.0–6.6 °C. The results demonstrate that a physics-only parametric PINN surrogate enables inverse thermal process design without repeated FE runs while establishing a single-track baseline for extension to multi-track and multi-layer builds.

Stavros K. Chionopoulos, Antonios Spyridakos

High-strength quenched and tempered steels such as EN 42CrMo4, widely used for marine shaft applications due to their high strength, toughness, and fatigue resistance, are nevertheless susceptible to surface degradation under severe dry sliding conditions. To enhance surface integrity and tribological performance, this study investigates laser-cladded AISI 410L and mixed AISI 410L/AISI 4140 (50/50 wt.%) coatings deposited on EN 42CrMo4 steel using a high-power diode laser (HPDL). Two-layer coatings were produced, and selected specimens underwent post-cladding stress-relief heat treatment to mitigate residual stresses and temper as-solidified microstructures. Microstructural characterization revealed refined dendritic and martensitic morphologies, while the mixed-alloy coatings showed increased carbide formation and improved hardness homogeneity. The mixed AISI 410L/AISI 4140 coatings achieved significantly higher microhardness values (≈530–555 HV) compared to single-alloy 410L coatings (≈310–420 HV). Tribological testing under dry sliding conditions (Al₂O₃ counterbody, 5 N load, 0.5 m/s sliding speed) demonstrated that the mixed-alloy coatings exhibited substantially lower steady-state friction coefficients (μ ≈ 0.65–0.69) and markedly reduced specific wear rates (≈11–17 × 10⁻¹⁴ m³/Nm) compared to the 410L coatings (≈150–175 × 10⁻¹⁴ m³/Nm). Post-cladding heat treatment further stabilized friction behaviour and reduced wear in the mixed-alloy system by tempering martensite and alleviating localized stress concentrations. Wear mechanism analysis revealed a transition from severe abrasive wear with fatigue-induced delamination in the 410L coatings to predominantly mild abrasive wear in the mixed-alloy coatings, accompanied by localized plastic deformation. Overall, the results establish clear correlations between microstructure, hardness, and tribological response, demonstrating that mixed-alloy laser cladding is an effective strategy for enhancing the dry sliding performance of EN 42CrMo4 steel in demanding marine applications.

Andreas Fezer, Stefan Weihe, Martin Werz

In resistance spot welding (RSW), the total electrical resistance (dynamic resistance) as the sum of bulk and contact resistance is a key variable. Both of these respective resistances influence the welding result, but the exact ratio to the total resistance of a real existing sheet is not known. Due to the high scatter in the RSW of aluminum alloys compared to steel, it is of interest to be able to explicitly determine the individual resistance components in order to gain a better understanding of the relationship between the initial state and the lower reproducibility of aluminum welding in the future. So far, only the total resistance and the bulk resistance could be determined experimentally. Due to the different sample shapes, it was not possible to consistently determine the contact resistance from the measurements. In order to realize this, a method was developed that contains the following innovations with the aid of simulation: determination of the absolute bulk resistance at room temperature (RT), determination of the absolute contact resistance at RT and determination of the ratio of bulk and contact resistance. This method makes it possible to compare the resistances of the bulk material and the surface in the initial state quantitatively. This now allows the comparison of batches regarding the surface resistance, especially for welding processes. For the aluminum sheets (EN AW-5182-O, EN AW-6014-T4) investigated, the method showed that the contact resistance dominates and the bulk resistance is less than 20%. These data can also be used to make predictions about the weldability of the alloy using artificial intelligence (AI). If experimental data are available, the method can also be applied to higher temperatures.

Christopher Chadwick, Claudia Nannei, Erin Sparrow et al.

<b>Background/Objectives:</b> Local production is a global priority for increasing access to routine, outbreak, and pandemic vaccines and leads to a variety of direct and indirect benefits for countries. This study aimed to characterize the enabling environment for the sustainable production of influenza vaccines, including for epidemic and pandemic preparedness. <b>Methods:</b> National/local vaccine manufacturers were surveyed to capture data on influenza vaccine market contributions, government support for local production, and involvement in national pandemic preparedness activities. Using a conceptual framework for sustainable local production of influenza vaccines for epidemic and pandemic preparedness, manufacturers described 41 global/regional, national, and institutional sustainability factors across policy, health system, research and development (R&D), and regulatory thematic domains. In addition to the survey, key findings from country-level sustainability assessments of vaccine production in Bangladesh, Brazil, Indonesia, Serbia, and Viet Nam were analyzed to complement survey results. <b>Results:</b> This study included 12 participants representing 11 manufacturers from 10 countries. Of the 11 manufacturers, six reported that their countries have policies that support local production, but most manufacturers reported benefiting from some level of direct or indirect support by the government. Manufacturers considered 40/41 factors as important for sustainable production of influenza vaccines, and among the four domains, influenza prevention and control policies, influenza burden data, quality management, and regulatory filing capacity ranked highly. Additionally, manufacturers ranked factors related to cohesive policies for local production promotion and business/strategic planning at the manufacturer level as the top sustainability factors. <b>Conclusions:</b> Manufacturers broadly agreed on the importance of cohesive policies, evidence-based public health priorities, robust R&D and manufacturing investments, and regulatory readiness, though perceptions varied across contexts and company characteristics. Sustainable local production of influenza vaccines should be driven by the alignment of policies, investments, and demand.

Nor Hidayati, Nadia Annisa Maori, Noor Nailie Azzat

Troso weaving is a distinctive craft product from Troso Village Pecangaan District, Jepara Regency that contributes significantly to the local economy. This weaving is traditionally made on a wooden loom and the manufacturing process required a high level of skill from the operator making it a creative and potentially profitable home industry for community benefit. This community service focuses on the Troso Agung Berkah Weaving Communityt. The old wooden loom as call as the gedokan had a daily production capacity of 2-3 pieces of fabric and a monthly production capacity of approximately 60-70 pieces of fabric that still away to fulfill the demand. This community service aims to increase production capacity through technological advancements by modifying the gedokan wooden loom with transfer technology using dynamo and additional wheels to allow the machine to operate automatically and also to improve competitiveness through digital marketing training based on e-commerce platform as marketing strategy. The first result of this community service is fourfold increase in production capacity with the modified gedokan wooden loom compared to the previous manual gedokan wooden loom and strengthen the skills of partners to implement digital marketing based on e-commerce by utiizing website thus supporting the sustainability of the Troso weaving industry amid global competition. Â

Abdelrahman Y. Sherif, Doaa Hasan Alshora, Mohamed A. Ibrahim

<b>Background/Objectives</b>: The inherent low aqueous solubility of lipophilic drugs, belonging to Class II based on Biopharmaceutical classification system, negatively impacts their oral bioavailability. However, the manufacturing of pharmaceutical dosage forms for these drugs faces challenges related to environmental impact and production complexity. Herein, the surfactant-enriched cross-linked scaffold addresses the limitations of conventional approaches, such as the use of organic solvents, energy-intensive processing, and the demand for sophisticated equipment. <b>Methods</b>: Scaffold former (Pluronic F68) and scaffold trigger agent (propylene glycol) were used to prepare cross-linked scaffold loaded with candesartan cilexetil as a model for lipophilic drugs. Moreover, surfactants were selected based on the measured solubility to enhance formulation loading capacity. Design-Expert was used to study the impact of Tween 80, propylene glycol, and Pluronic F68 concentrations on the measured responses. In addition, in vitro dissolution study was implemented to investigate the drug release profile. The current approach was assessed against the limitations of conventional approach in terms of environmental and manufacturing feasibility. <b>Results</b>: The optimized formulation (59.27% Tween 80, 30% propylene glycol, 10.73% Pluronic F68) demonstrated a superior drug loading capacity (19.3 mg/g) and exhibited a solid-to-liquid phase transition at 35.5 °C. Moreover, it exhibited a rapid duration of solid-to-liquid transition within about 3 min. In vitro dissolution study revealed a remarkable enhancement in dissolution with 92.87% dissolution efficiency compared to 1.78% for the raw drug. <b>Conclusions</b>: Surfactant-enriched cross-linked scaffold reduced environmental impact by eliminating organic solvents usage and reducing energy consumption. Moreover, it offers significant manufacturing advantages through simplified production processing.

Alessio Pacini, Francesco Lupi, Michele Lanzetta

Industrial Vision Inspection Systems (VISs) often struggle to adapt to increasing variability of modern manufacturing due to the inherent rigidity of their hardware architectures. Although the Reconfigurable Manufacturing System (RMS) paradigm was introduced in the early 2000s to overcome these limitations, designing such reconfigurable machines remains a complex, expert-dependent, and time-consuming task. This is primarily due to the lack of structured methodologies and the reliance on trial-and-error processes. In this context, this study proposes a novel theoretical framework to facilitate the design of fully reconfigurable handling systems for VISs, with a particular focus on fixture design. The framework is grounded in Model-Based Definition (MBD), embedding semantic information directly into the 3D CAD models of the inspected product. As an additional contribution, a general hardware architecture for the inspection of axisymmetric components is presented. This architecture integrates an anthropomorphic robotic arm, Numerically Controlled (NC) modules, and adaptable software and hardware components to enable automated, software-driven reconfiguration. The proposed framework and architecture were applied in an industrial case study conducted in collaboration with a leading automotive half-shaft manufacturer. The resulting system, implemented across seven automated cells, successfully inspected over 200 part types from 12 part families and detected more than 60 defect types, with a cycle below 30 s per part.

Mostafa Meraj Pasha, Zhijian Pei, Md Shakil Arman et al.

The binder jetting additive manufacturing process offers the ability to create three-dimensional parts layer by layer. However, using any powder that contains particles with different sizes, shapes, or densities can lead to powder segregation during the mixing, dispensing, and spreading steps of the binder jetting additive manufacturing process. Powder segregation can often lead to uneven powder distribution across the powder bed, potentially causing defects in final parts. Therefore, it is important to understand powder segregation in mixing, dispensing, and spreading. Reported studies on powder segregation in mixing were conducted primarily on pharmaceutical or food powder that have different properties compared to metal or ceramic powder used in binder jetting additive manufacturing. There is a need for a deep understanding of how mixing speed and mixing time affect powder segregation in the context of binder jetting additive manufacturing. This paper reports an experimental investigation using a two-variable, two-level full-factorial design to examine the main effects and interaction effect of mixing speed and mixing time on powder segregation in the mixing of Powder A and Powder B for binder jetting additive manufacturing. The results reveal that segregation was more severe at the high level of mixing speed and the high level of mixing time. These findings provide useful insights for selecting mixing variables and controlling segregation, essential for achieving high-quality printed parts in binder jetting additive manufacturing.

Lukas Rauh, Mel-Rick Süner, Daniel Schel et al.

The benefits of adopting artificial intelligence (AI) in manufacturing are undeniable. However, operationalizing AI beyond the prototype, especially when involved with cyber-physical production systems (CPPS), remains a significant challenge due to the technical system complexity, a lack of implementation standards and fragmented organizational processes. To this end, this paper proposes a new process model for the lifecycle management of AI assets designed to address challenges in manufacturing and facilitate effective operationalization throughout the entire AI lifecycle. The process model, as a theoretical contribution, builds on machine learning operations (MLOps) principles and refines three aspects to address the domain-specific requirements from the CPPS context. As a result, the proposed process model aims to support organizations in practice to systematically develop, deploy and manage AI assets across their full lifecycle while aligning with CPPS-specific constraints and regulatory demands.

Nitay Lavi, Igal Sason

We derive exact values and new bounds for the Shannon capacity of two families of graphs: the $q$-Kneser graphs and the tadpole graphs. We also construct a countably infinite family of connected graphs whose Shannon capacity is not attained by the independence number of any finite strong power. Building on recent work of Schrijver, we establish sufficient conditions under which the Shannon capacity of a polynomial in graphs, formed via disjoint unions and strong products, equals the corresponding polynomial of the individual capacities, thereby reducing the evaluation of such capacities to that of their components. Finally, we prove an inequality relating the Shannon capacities of the strong product of graphs and their disjoint union, which yields alternative proofs of several known bounds as well as new tightness conditions. In addition to contributing to the computation of the Shannon capacity of graphs, this paper is intended to serve as an accessible entry point to those wishing to work in this area.

Rongfei Li, Francis Assadian

The use of robotic technology has drastically increased in manufacturing in the 21st century. But by utilizing their sensory cues, humans still outperform machines, especially in the micro scale manufacturing, which requires high-precision robot manipulators. These sensory cues naturally compensate for high level of uncertainties that exist in the manufacturing environment. Uncertainties in performing manufacturing tasks may come from measurement noise, model inaccuracy, joint compliance (e.g., elasticity) etc. Although advanced metrology sensors and high-precision microprocessors, which are utilized in nowadays robots, have compensated for many structural and dynamic errors in robot positioning, but a well-designed control algorithm still works as a comparable and cheaper alternative to reduce uncertainties in automated manufacturing. Our work illustrates that a multi-robot control system can reduce various uncertainties to a great amount.

Amine Asselah, Bruno Schapira, Perla Sousi

We obtain a derivative formula for various notions of capacity. Namely we identify the second order term in the asymptotic expansion of the capacity of a union of two sets, as their distance goes to infinity. Our result applies to the usual Newtonian capacity in the setting of random walks on the Euclidean lattice, to the family of Bessel-Riesz capacities, and to the Branching capacity, which has been introduced recently by Zhu [9] in connection with critical Branching random walks. On the other hand, the result remains open for the notion of capacity in the setting of percolation, which is introduced in a companion paper, but serves as a motivation, as it would have some interesting consequences there.

Fabian Eichler, Nicolae Balc, Sebastian Bremen et al.

The thermal conductivity of components manufactured using Laser Powder Bed Fusion (LPBF), also called Selective Laser Melting (SLM), plays an important role in their processing. Not only does a reduced thermal conductivity cause residual stresses during the process, but it also makes subsequent processes such as the welding of LPBF components more difficult. This article uses 316L stainless steel samples to investigate whether and to what extent the thermal conductivity of specimens can be influenced by different LPBF parameters. To this end, samples are set up using different parameters, orientations, and powder conditions and measured by a heat flow meter using stationary analysis. The heat flow meter set-up used in this study achieves good reproducibility and high measurement accuracy, so that comparative measurements between the various LPBF influencing factors to be tested are possible. In summary, the series of measurements show that the residual porosity of the components has the greatest influence on conductivity. The degradation of the powder due to increased recycling also appears to be detectable. The build-up direction shows no detectable effect in the measurement series.

Muyiwa Seyi Adegbaju, Titilayo Ajose, Ifeoluwa Elizabeth Adegbaju et al.

Many African countries are unable to meet the food demands of their growing population and the situation is worsened by climate change and disease outbreaks. This issue of food insecurity may lead to a crisis of epic proportion if effective measures are not in place to make more food available. Thus, deploying biotechnology towards the improvement of existing crop varieties for tolerance or resistance to both biotic and abiotic stresses is crucial to increasing crop production. In order to optimize crop production, several African countries have implemented strategies to make the most of this innovative technology. For example, Nigerian government has implemented the National Biotechnology Policy to facilitate capacity building, research, bioresource development and commercialization of biotechnology products for over two decades. Several government ministries, research centers, universities, and agencies have worked together to implement the policy, resulting in the release of some genetically modified crops to farmers for cultivation and Commercialization, which is a significant accomplishment. However, the transgenic crops were only brought to Nigeria for confined field trials; the manufacturing of the transgenic crops took place outside the country. This may have contributed to the suspicion of pressure groups and embolden proponents of biotechnology as an alien technology. Likewise, this may also be the underlying issue preventing the adoption of biotechnology products in other African countries. It is therefore necessary that African universities develop capacity in various aspects of biotechnology, to continuously train indigenous scientists who can generate innovative ideas tailored towards solving problems that are peculiar to respective country. Therefore, this study intends to establish the role of genetic engineering and genome editing towards the achievement of food security in Africa while using Nigeria as a case study. In our opinion, biotechnology approaches will not only complement conventional breeding methods in the pursuit of crop improvements, but it remains a viable and sustainable means of tackling specific issues hindering optimal crop production. Furthermore, we suggest that financial institutions should offer low-interest loans to new businesses. In order to promote the growth of biotechnology products, especially through the creation of jobs and revenues through molecular farming.

R. Joey Griffiths, Alexander E. Wilson-Heid, Marissa A. Linne et al.

Additive friction stir deposition (AFSD) is a solid-state metal additive manufacturing technique, which utilizes frictional heating and plastic deformation to create large deposits and parts. Much like its cousin processes, friction stir welding and friction stir processing, AFSD has seen the most compatibility and use with lower-temperature metals, such as aluminum; however, there is growing interest in higher-temperature materials, such as titanium and steel alloys. In this work, we explore the deposition of an ultrahigh-temperature refractory material, specifically, a tantalum–tungsten (TaW) alloy. The solid-state nature of AFSD means refractory process temperatures are significantly lower than those for melt-based additive manufacturing techniques; however, they still pose difficult challenges, especially in regards to AFSD tooling. In this study, we perform initial deposition trials of TaW using twin-rod-style AFSD with a high-temperature tungsten–rhenium-based tool. Many challenges arise because of the high temperatures of the process and high mechanical demand on AFSD machine hardware to process the strong refractory alloy. Despite these challenges, successful deposits of the material were produced and characterized. Mechanical testing of the deposited material shows improved yield strength over that of the annealed reference material, and this strengthening is mostly attributed to the refined recrystallized microstructure typical of AFSD. These findings highlight the opportunities and challenges associated with ultrahigh-temperature AFSD, as well as provide some of the first published insights into twin-rod-style AFSD process behaviors.

Francisco J. G. Silva, Rui P. Martinho, Luís L. Magalhães et al.

Strategies for obtaining deep slots in soft materials can vary significantly. Conventionally, the tool travels along the slot, removing material mainly with the side cutting edges. However, a “plunge milling” strategy is also possible, performing the cut vertically, taking advantage of the tip cutting edges that almost reach the center of the tool. Although both strategies are already commonly used, there is a clear gap in the literature in studies that compare tool wear, surface roughness, and productivity in each case. This paper describes an experimental study comparing the milling of deep slots in AA7050-T7451 aluminum alloy, coated with a novel DLCSiO500W3.5O₂ layer to minimize the aluminum adhesion to the tool, using conventional and plunge milling strategies. The main novelty of this paper is to present a broad study regarding different factors involved in machining operations and comparing two distinct strategies using a novel tool coating in the milling of aeronautical aluminum alloy. Tool wear is correlated with the vibrations of the tools in each situation, the cycle time is compared between the cases studied, and the surface roughness of the machined surfaces is analyzed. This study concludes that the cycle time of plunge milling can be about 20% less than that of conventional milling procedures, favoring economic sustainability and modifying the wear observed on the tools. Plunge milling can increase productivity, does not increase tool tip wear, and avoids damaging the side edges of the tool, which can eventually be used for final finishing operations. Therefore, it can be said that the plunge milling strategy improves economic and environmental sustainability as it uses all the cutting edges of the tools in a more balanced way, with less global wear.

Marcelo Prado Sucena, Marcus Vinicius Quintella Cury

Este artigo busca desenvolver modelagem, baseada no método Fuzzy-SAW, para avaliar a qualidade percebida pelos clientes finais na prestação do serviço logístico do e-commerce. Pretende-se desenvolver estudo de caso para validação e exemplificação, usando-se dados obtidos em enquete para se determinarem o Índice da Qualidade da Logística do E-commerce e outros parciais. Após o processamento de 409 registros obtidos por intermédio de questionário, observou-se que as quatro empresas mais citadas, usadas como alternativas no modelo, registraram quase 80% das observações. Após a análise de sete atributos operacionais e outros quatro relacionados ao atendimento do cliente, considerados no modelo como os critérios, notou-se que nenhuma das empresas atingiu grau 6,0 em escala [0,10], caracterizando potencial para melhoria. A empresa com maior amplitude nacional é a que apresentou a pior qualidade; a segunda mais qualificada é concorrente direta desta empresa; a com melhor grau (5,53) representa, apenas, 4% das citações na enquete.

Josemar Coelho Felix, Camila Silva Peixoto, Camila Aparecida Edwiges

As empresas são mais competitivas, se elas tiverem um controle eficiente dos seus suprimentos. A aplicação da pesquisa operacional, com a utilização de ferramentas computacionais, pode ser uma alternativa de auxílio para evitar problemas no processo ferroviário. Esta pesquisa teve como objetivo, utilizar da mensuração dos parâmetros oriundos da Teoria de Filas e da simulação com o software Arena, além de ter um melhor diagnostico da previsão dos suprimentos na restauração de truques em uma oficina da MRS Logística. Com o estudo de caso aqui descrito, foi possível ter uma reflexão sobre a importância da simulação na produtividade, pois verificou que a variação do tempo de produção da manutenção, pode causar problemas no planejamento orçamentário do processo de manutenção dos truques.

Gustavo Carvalho Santos, Flavio Barboza, Antônio Cláudio Paschoarelli Veiga et al.

Artificial intelligence (AI) models can help investors find portfolios in which the focus is to optimize the risk-return relationship. There are several algorithms and techniques in the literature that allow the application of tests to a set of historical data for the selection and validation of investment portfolios. Based on this, this research intends to examine the contribution of the main machine learning techniques used in portfolio management through a systematic literature review. By using the Methodi Ordinatio for selection and ranking of articles, we classified papers considering object of study, type of AI used, period of analysis, data frequency, balance and cardinality. In addition, we detail the main contributions and trends conceived until the year 2020. Therefore, our findings reveal gaps and suggest future works on the topic.