Abstract The growing needs for quality tobacco products require improvements in quality control in the manufacturing of cigarettes. Standard quality control techniques, including manual inspections and traditional automated means, may not be able to identify minute defects in the production process effectively, causing inefficiencies and inconsistency in the final product. This work suggests a machine learning-based framework that employs U-Net for image segmentation and Mountain Gazelle Optimizer (MGO) for optimization in cigarette production quality control. The proposed framework aims to enhance defect detection, decide optimally, and facilitate real-time adaptability to changing production conditions. In this paper, the Tobacco Leaf Disease Detection Dataset was utilized, which has high-resolution tobacco leaf images classified based on disease classes, covering a range of conditions from tobacco curing. The proposed method outperforms existing methods by a wide margin, with performance metrics indicating 98.12 percentage of accuracy, precision at 98.48 percentage recall at 97.74 percentage, and an F1-score at 98.11 percentage. These findings reflect the high efficiency of the framework in detecting slight defects, promoting consistency of the overall product and operational efficiency. The system also reflects the capacity to dynamically adapt to changes in the production environment for better quality and lower operational costs. Future research will investigate additional optimization methods and additional data sources for integration to enhance scalability and adaptability, further making manufacturing a sustainable and efficient process. The proposed framework is designed for real-time deployment and seamless integration with industrial quality control systems, enabling automated defect detection and adaptive process optimization. This system-level integration enhances production consistency, reduces material waste, and improves overall quality assurance in cigarette manufacturing environments.
Daniel Gomez-Lendinez, Jesus Garcia-Moreno-Caraballo, Sergio Corbera
et al.
Low-carbon steels, such as ER70S-6, are typically considered resistant to phase transformations due to their high critical cooling rate. However, this study investigates how the manufacturing process and specimen geometry influence heat dissipation, potentially leading to localized grain size variations that impact mechanical properties. To analyze these effects, samples were fabricated using Laser Wire-Feed Additive Manufacturing (LWAM) with different geometries, and their hardness and microstructural characteristics were evaluated. Vickers microhardness tests were performed along the specimens to assess local variations, while dilatometry measurements were conducted to determine thermal expansion coefficients for future integration into finite element models (FEMs) of residual stress distribution. The results reveal that differences in heat dissipation during fabrication lead to grain size heterogeneity, affecting hardness at a microscopic scale and overall mechanical performance. These findings highlight the importance of considering thermal history and geometry in LWAM-fabricated components to ensure consistent material properties.
purwono purwono, setyo supratno, Muhammad Amin Bakri
This research aims to implement the Auto Bending Lead Capacitor PCB Control Unit machine in manufacturing processes to improve operational efficiency and production capacity. The study begins with a literature review on the use of bending machines in various manufacturing industries, including integration with polarity inspection using Keyence Fiber Optic sensors. The implementation of this machine is based on kaizen and improvement initiatives for continuous improvement in production efficiency, waste reduction, and product quality enhancement. The findings show significant increases in production capacity with a time efficiency improvement of 2.87 seconds per product and monthly cost savings of Rp. 11,671,647. The Break Event Point (BEP) analysis indicates that the initial machine investment can be recouped within 2.7 months post-implementation. Recommendations for improvement include adding distance sensors for bend result detection and integrating production monitoring systems to enhance overall operational control. This research contributes significantly to improving manufacturing process efficiency through cutting-edge technology in electronic component production.
Rossella Surace, Francesco Modica, Vito Basile
et al.
Ultra-high molecular weight polyethylene (UHMWPE) is widely used in orthopedic and prosthetic applications due to its excellent wear resistance and biocompatibility. However, its high molecular weight presents significant challenges in terms of processing and formability, particularly at the micro scale. This study investigates the flowability characteristics of a new melt-processable UHMWPE in micro-disc geometries to evaluate its suitability for advanced prosthetic applications. Micro-injection molding experiments assessed the material’s behavior under various thermal conditions. The influence of parameters such as temperature, pressure, and disc dimensions has direct effects on the flow behavior of UHMWPE and was analyzed by simulation and experiments. Results indicate that while UHMWPE exhibits limited flow under conventional conditions, optimized processing parameters can enhance discs’ formability without compromising the material’s structural integrity, avoiding defects. These findings provide critical insights for the microfabrication of UHMWPE thin components in next-generation prosthetic devices, enabling improved design precision and functional performance.
Mohammad Sohel, Vishal S. Sharma, Aravinthan Arumugam
This study presents a systematic optimization of GTAW welding parameters to achieve a pipe-to-pipe butt weld with a root height consistently below 2 mm when joining stainless-steel 316L material, employing the Taguchi design of experiments. To the authors’ knowledge, no similar studies have been conducted to explore the optimization of welding parameters specifically aimed at minimizing weld root height under 2 mm in stainless-steel EO pipeline welding applications. This gap in the existing literature highlights the innovative aspect of the current study, which seeks to address these challenges and improve welding precision and joint reliability. Root height, also referred to as weld root reinforcement, is defined as the excess weld metal protruding beyond the inner surface root side of a butt-welded joint. The input parameters considered are the welding current, voltage, speed, and root gap configurations of 1, 1.5, and 2 mm. Welding was performed according to the Taguchi L-09 experimental design. Nine weld samples were evaluated using liquid penetrant testing to detect surface-breaking defects, such as porosity, laps, and cracks; X-ray radiography to identify internal defects; and profile radiography to assess erosion, corrosion, and root height. Among the nine welded plate samples, the optimal root height (less than 2 mm) was selected and further validated through the welding of a one-pipe sample. An additional macro examination was conducted to confirm the root height and assess the overall root weld integrity and quality.
Marcela Fernandes Silva, Eric Willian Correa dos Santos, Claudia Telles Benatti
Qualidade na gestão de laboratórios de instituições públicas é essencial para garantir a confiabilidade dos resultados de pesquisas, assim como da prestação de serviços. O objetivo deste trabalho foi identificar os principais desafios e dificuldades enfrentados por laboratórios de instituições públicas para a obtenção ou manutenção da acreditação na Norma ISO/IEC 17025:2017 da ABNT. Os dados para o desenvolvimento do trabalho foram obtidos por meio de pesquisa bibliográfica a fim de fundamentar a investigação. Com esta pesquisa pode-se aferir que os principais desafios para a acreditação de um laboratório em instituições públicas estão relacionados com os recursos humanos, seguido da falta de recursos financeiros e de materiais, falta de conhecimento ou experiência com a ISO/IEC 17025, e burocracia. Diante desses desafios, o estudo aponta a necessidade de investimentos em capacitação profissional, maior agilidade nos processos internos e alocação de recursos adequados como soluções prioritárias para garantir a qualidade e a confiabilidade dos serviços prestados por esses laboratórios, a fim de garantir a qualidade e confiabilidade dos serviços prestados pelos laboratórios das instituições públicas.
Production management. Operations management, Production capacity. Manufacturing capacity
First, we investigate the trade-off relations of quantum battery capacities in two-qubit system. We find that the sum of subsystem battery capacity is governed by the total system capacity, with this trade-off relation persisting for a class of Hamiltonians, including Ising, XX, XXZ and XXX models. Then building on this relation, we define residual battery capacity for general quantum states and establish coherent/incoherent components of subsystem battery capacity. Furthermore, we introduce the protocol to guide the selection of appropriate incoherent unitary operations for enhancing subsystem battery capacity in specific scenarios, along with a sufficient condition for achieving subsystem capacity gain through unitary operation. Numerical examples validate the feasibility of the incoherent operation protocol. Additionally, for the three-qubit system, we also established a set of theories and results parallel to those for two-qubit case. Finally, we determine the minimum time required to enhance subsystem battery capacity via a single incoherent operation in our protocol. Our findings contribute to the development of quantum battery theory and quantum energy storage systems.
This paper introduces a complete real-time algorithm, where the chatter is detected and eliminated by spindle speed manipulation via the chatter energy feedback calculated from the axis encoder measurement. The proposed method does not require profound knowledge of the machining dynamics; instead, the entire algorithm exploits the fact that milling vibrations consist of forced vibrations at spindle speed harmonics and chatter vibrations that are close to one of the natural modes, with sidebands which are spread at the multiples of spindle speed frequency above and below the chatter frequency. The developed algorithm is able to identify the amplitude, phase and frequency of all the harmonics constituting the periodic forced and chatter vibrations. The key challenge is to select dominant chatter frequencies for the calculation of a robust and accurate chatter energy ratio feedback; this is achieved by utilizing the frequency estimation variance of EKF as a novel chatter indicator. Based on the chatter energy ratio feedback, the controller overrides the spindle speed in order to suppress the chatter energy below a particular threshold value. The varying spindle speed challenge is handled by updating the state transition matrices of the Kalman filters and real-time calculation of the band-pass filter coefficients, based on the derived discrete time transfer functions. The developed algorithm is tested on a Deckel FP5cc CNC which is in-house retrofitted and has a PC-based controller for the real-time application of the proposed algorithm. It is shown that the real-time chatter frequency and amplitude estimates are compatible with off-line FFT analysis, and chatter can be successfully eliminated by energy feedback.
A shape optimization program is developed for the ratio of Riesz capacities $\text{Cap}_q(K)/\text{Cap}_p(K)$, where $K$ ranges over compact sets in $\mathbb{R}^n$. In different regions of the $pq$-parameter plane, maximality is conjectured for the ball, the vertices of a regular simplex, or the endpoints of an interval. These cases are separated by a symmetry-breaking transition region where the shape of maximizers remains unclear. On the boundary of $pq$-parameter space one encounters existing theorems and conjectures, including: Watanabe's theorem minimizing Riesz capacity for given volume, the classical isodiametric theorem that maximizes volume for given diameter, Szegő's isodiametric theorem maximizing Newtonian capacity for given diameter, and the still-open isodiametric conjecture for Riesz capacity. The first quadrant of parameter space contains Pólya and Szegő's conjecture on maximizing Newtonian over logarithmic capacity for planar sets. The maximal shape for each of these scenarios is known or conjectured to be the ball. In the third quadrant, where both $p$ and $q$ are negative, the maximizers are quite different: when one of the parameters is $-\infty$ and the other is suitably negative, maximality is proved for the vertices of a regular simplex or endpoints of an interval. Much more is proved in dimensions $1$ and $2$, where for large regions of the third quadrant, maximizers are shown to consist of the vertices of intervals or equilateral triangles.
The extremely high costs of manufacturing transglutaminase from animal origin (EC 2.3.2.13) have prompted scientists to search for new sources of this enzyme. Interdisciplinary efforts have been aimed at producing enzymes synthesised by microorganisms which may have a wider scope of use. Transglutaminase is an enzyme that catalyses the formation of isopeptide bonds between proteins. Its cross-linking property is widely used in various processes: to manufacture cheese and other dairy products, in meat processing, to produce edible films and to manufacture bakery products. Transglutaminase has considerable potential to improve the firmness, viscosity, elasticity and water-binding capacity of food products. In 1989, microbial transglutaminase was isolated from Streptoverticillium sp. Its characterisation indicated that this isoform could be extremely useful as a biotechnological tool in the food industry. Currently, enzymatic preparations are used in almost all industrial branches because of their wide variety and low costs associated with their biotechnical production processes. This paper presents an overview of the literature addressing the characteristics and applications of transglutaminase.
Ashutosh Sharma, Dikshitkumar Khamar, S. Cullen
et al.
In the past two decades, biopharmaceuticals have been a breakthrough in improving the quality of lives of patients with various cancers, autoimmune, genetic disorders etc. With the growing demand of biopharmaceuticals, the need for reducing manufacturing costs is essential without compromising on the safety, quality, and efficacy of products. Batch Freeze-drying is the primary commercial means of manufacturing solid biopharmaceuticals. However, Freeze-drying is an economically unfriendly means of production with long production cycles, high energy consumption and heavy capital investment, resulting in high overall costs. This review compiles some potential, innovative drying technologies that have not gained popularity for manufacturing parenteral biopharmaceuticals. Some of these technologies such as Spin-freeze-drying, Spray-drying, Lynfinity® Technology etc. offer a paradigm shift towards continuous manufacturing, whereas PRINT® Technology and MicroglassificationTM allow controlled dry particle characteristics. Also, some of these drying technologies can be easily scaled-up with reduced requirement for different validation processes. The inclusion of Process Analytical Technology (PAT) and offline characterization techniques in tandem can provide additional information on the Critical Process Parameters (CPPs) and Critical Quality Attributes (CQAs) during biopharmaceutical processing. These processing technologies can be envisaged to increase the manufacturing capacity for biopharmaceutical products at reduced costs.
Mahmoud Shaban, Abdulrahman I. Alateyah, Mohammed F. Alsharekh
et al.
Several physics-based models have been utilized in material design for the simulation and prediction of material properties. In this study, several machine-learning (ML) approaches were used to construct a prediction model to analyze the influence of equal-channel angular pressing (ECAP) parameters on the microstructural, corrosion and mechanical behavior of the biodegradable magnesium alloy ZK30. The ML approaches employed were linear regression, the Gaussian process, and support vector regression. For the optimization of the alloy’s performance, experiments were conducted on ZK30 billets using different ECAP routes, channel angles, and number of passes. The adopted ML model is an adequate predictive model which agreed with the experimental results. ECAP die angles had an insignificant effect on grain refinement, compared to the route type. ECAP via four passes of route Bc (rotating the sample 90° on its longitudinal axis after each pass in the same direction) was the most effective condition producing homogenous ultrafine grain distribution of 1.92 µm. Processing via 4-Bc and 90° die angle produced the highest hardness (97-HV) coupled with the highest tensile strength (344 MPa). The optimum corrosion rate of 0.140 mils penetration per year (mpy) and the optimum corrosion resistance of 1101 Ω·cm<sup>2</sup> resulted from processing through 1-pass using the 120°-die. Grain refinement resulted in reducing the corrosion rates and increased corrosion resistance, which agreed with the ML findings.
The current energy crisis is a pressing global challenge, with the industrial sector accounting for half of global energy consumption. Scheduling is considered one of the potential methods to reduce energy consumption. This article introduces the Fire Hawk Optimizer (FHO) algorithm to solve the no-idle flow shop scheduling problem to minimize overall energy consumption. FHO organizes the job sequence in no-idle flow shop scheduling for reduce energy consumption. This research investigates the use of different machine speed levels, namely slow, fast, and normal, based on case data of manufacturing industries in Indonesia. The results of this study compare the performance of the FHO algorithm with the Adaptive Integrated Greedy (AIG) heuristic method and compare it with the Grey Wolf Optimizer (GWO) algorithm. The experimental results showed that total energy consumption tends to be high when processed at high speed. Conversely, low-speed results in lower energy consumption but requires longer processing time. The comparison results show that the Fire Hawk Optimizer is more efficient in reducing total energy consumption than the AIG heuristic method. Meanwhile, the FHO algorithm performs comparably to the GWO algorithm and completes enumeration. These findings confirm that the proposed procedure can be an alternative to the scheduling optimization process.
Industrial engineering. Management engineering, Production capacity. Manufacturing capacity
Jean Felipe Leal Silva, Thayane Carpanedo De Morais Nepel, Gustavo Doubek
et al.
The increasing adoption of solar and wind power for electricity production has spurred new projects for the development of cost-competitive energy storage technologies. Among the various promising options, Li-O2 batteries deserve special attention because of their potential high specific energy, which might lead to decreased manufacturing and installation costs. Regarding the manufacturing costs, one of the steps with the most impact on manufacturing time is the wetting process, which might take days to complete. Improving this process has been crucial to reduce manufacturing costs and increase battery performance for lithium-ion batteries. This work provides an assessment of the impact of time of the wetting process on the performance of Li-O2 batteries. Li-O2 batteries were assembled using an O2 electrode based on carbon paper. The separator membrane and the O2 electrode were immersed in the electrolyte solution for 1 h, 3 h, 9 h, 27 h, and 81 h, and deep discharge trials were performed for each case. The capacity of the battery was measured and compared to the standard assembly procedure, in which the battery is assembled with electrolyte and left to rest for 72 h. After discharge, the electrodes were analyzed via scanning electron microscopy to identify the impact of electrolyte filling of the O2 electrode on the distribution of the discharge product over its surface. The results demonstrate the importance of investigating this process step in the manufacturing of batteries to ensure better performance of Li-O2 batteries.
Chemical engineering, Computer engineering. Computer hardware
This work presents a cyber-physical drilling machine that incorporates technologies discovered in the fourth industrial revolution. The machine is designed to realize its state by detecting whether it hits or breaks through the workpiece, without the need for additional sensors apart from the position sensor. Such self-recognition enables the machine to adapt and shift the controllers that handle position, velocity, and force, based on the workpiece and the drilling environment. In the experiment, the machine can detect and switch controls that follow the drilling events (HIT and BREAKHTROUGH) within 0.1 and 0.5 s, respectively. The machine’s high visibility design is beneficial for classification of the workpiece material. By using a support-vector-machine (SVM) on thrust force and feed rate, the authors are seen to achieve 92.86% accuracy for classification of material, such as medium-density fiberboard (MDF), acrylic, and glass.
Abstract Renewable energy investments are expanding across the world at an astonishing rate. The United States and Europe obtained early advantages in renewable energy technologies. However, East Asian late industrializers have now extended substantial support to domestic renewable energy manufacturing firms alongside encouraging increased deployment of renewable energy projects. In the solar energy sector, Chinese companies now dominate global production of solar cells and panels. Other developing countries, in South Asia and Sub-Saharan Africa, have lagged in their support to manufacturing segments of renewable energy sectors. Yet many countries still aim to promote domestic production of solar panels and cells though such priorities are often secondary to increasing deployment of solar power projects. This paper argues that India’s position as a late, late industrializer in the sector, combined with prevailing domestic political economy pressures, have made it extremely difficult to promote the manufacturing of solar panels and cells. The strategy of prioritising increasing installed capacity of solar energy while also attracting lower energy tariffs appears incompatible with the goal of increasing domestic manufacturing capacity. Initially established in 2010 and ramped up after Narendra Modi became Prime Minister in 2014, India’s National Solar Mission (NSM) has received widespread praise for increasing the country’s installed solar energy capacity and for attracting tariffs of Rs. 2.44 per unit (a reduction of 80% within the last six years). However, domestic manufacturing has received limited support, especially after the United States launched a complaint against the NSM’s domestic content requirements, requiring energy developers to procure domestically-produced panels on specific projects. In 2018, the Indian government chose to refocus its attention on supporting manufacturers. However, the government chose a strategy that prioritised retaining a low minimum tariff on projects while increasing protection against imported panels, thereby forcing developers to buy panels at a higher cost. Since then, bidding processes have slowed down, highlighting the incompatibility of these goals. India’s case shows that countries that fail to integrate a strategic focus on manufacturing in their renewable energy expansion strategies from the onset may remain dependent on foreign imports of renewable energy technologies in the long-term. Late late development without adequate attention to industrial policy in renewable energy sectors will inevitably cement a green division of labour, with most of the Global South locked in dependency on American, European and East Asian technologies.
Abstract Hydrogen is an important chemical feedstock for many industrial applications, and today, more than 95% of this feedstock is generated from fossil fuel sources such as reforming of natural gas. In addition, the production of hydrogen from fossil fuels represents most carbon dioxide emissions from large chemical processes such as ammonia generation. Renewable sources of hydrogen such as hydrogen from water electrolysis need to be driven to similar production costs as methane reforming to address global greenhouse gas emission concerns. Water electrolysis has begun to show scalability to relevant capacities to address this need, but materials and manufacturing advancements need to be made to meet the cost targets. This article describes specific needs for one pathway based on proton exchange membrane electrolysis technology.