Production Process Research Articles

Artificial Neural Network For Predictive Modeling of Quinoline Insolubles in Pitch in A Steel Industry: Quality and Sustainability

Objective: The objective of the present work was the development of an intelligent system based on artificial neural networks, supervised and with batch learning, to predict the quinoline insoluble quality (IQ) parameter of tar, using a set of data from a steel industry. Theoretical Framework: Tar, derived from coal tar, is widely used in the production of anodes for the aluminum industry, and its quinoline insoluble (IQ) content is a crucial parameter, influenced by factors such as coal mixing, coking parameters and heat treatment. IQ forecasting is challenging due to the complexity of the processes involved. To address this question, artificial neural networks (ANNs) have been applied to predict the IQ of tar, taking advantage of its ability to handle complex, nonlinear systems. Method: In this study, a feedforward RNA model was used, trained with the Levenberg-Marquardt algorithm. The model has been configured with two hidden layers and the tansig activation function. The training was carried out with real data from polymerization reactors, including variables such as level, temperature, nitrogen rate, feed flow rate of the polymerizers and tar IQ. The network was configured with 2000 interactions and 20 neurons in the hidden layer, obtaining a training error (MSE) of 1x10-20. Results and Discussion: The analysis of the results revealed that temperature and nitrogen flow have the greatest influence on the IQ of the pitch, with higher temperatures and higher flow rates resulting in a higher IQ. Research Implications: ANN modeling is effective in predicting and optimizing industrial processes, especially in the analysis of large volumes of data and complex systems, contributing to quality control in pitch production and the improvement of industrial processes. Originality/Value: The main contribution of this work lies in the demonstration of the ability of artificial neural networks to accurately model the content of Quinoline Insolubles (IQ) of the pitch, even in the face of the significant dispersion observed in the input data. This finding is particularly relevant because the high variability of the data often poses a challenge for traditional predictive models. The precision achieved by the neural network, therefore, proves the feasibility and potential of this approach to overcome the limitations inherent to the complexity of the pitch production process and optimize its control, opening new perspectives for the steel industry

Endpoint carbon content and temperature prediction model in BOF steelmaking based on posterior probability and intra-cluster feature weight online dynamic feature selection

Abstract A posterior probability and intra-cluster feature weight online dynamic feature selection algorithm is proposed to address the issues of high dimensionality and high volatility of data in the basic oxygen furnace (BOF) steelmaking production process. First, a genetic algorithm with fixed feature space dimensions is introduced, which narrows the solution space by predefining the number of selected features, thereby enhancing the stability of feature selection. Second, the posterior probability of samples and intra-cluster feature weights are used to weigh and calculate the feature importance of the current sample, obtaining the optimal features that align with the current operating conditions. Finally, the dynamically selected features are used in a regression model to predict the carbon content and temperature of the BOF steelmaking process data. Simulations of actual BOF steelmaking process data showed that the prediction accuracy was 86% within a carbon content error range of 0.02, and 88% within a temperature error range of 10°C.

Analisis Pengendalian Kualitas Sablon Pada Sandal Jepit Dengan Menggunakan Statistical Process Control (SPC) di PT. XZ

PT. XZ is a company engaged in the manufacture of flip-flops. One of the sandal products produced is Screen-printed flip flops. However, in every production process failure is inseparable in the form of defective products in the production process. The purpose of this research is to minimize defects in Screen printing products. To reduce these defects, it is necessary to analyze the production process using the Statistical Process Control method. The analysis was carried out by using Seven Tools and 5W+1H tools. The results of the analysis show that the types of defects that occur in Screen printing products are the color of the paint is uneven, the paint is smeared and peeled off, and the Screen printing is not precise. Based on the three types of defects, the most dominant defect is uneven paint color with a percentage of 41,8%. Screen printing product defects are caused by human, machine, material, and method. Improvement efforts made to minimize the occurrence of uneven/fading paint color defects, namely conducting briefings and conducting supervision and checking on Screen printing results, checking on the Screen before printing is done, checking paint before printing, and providing training on rework standardization to employees and conducting regular performance evalutions. Keywords: Quality, Statistical Process Control, Seven Tools, 5W+1H

Accelerating Benders Decomposition for sustainable food closed-loop supply chain network under uncertainty: a case study

PurposeThe purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.Design/methodology/approachA robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.FindingsThe proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.Practical implicationsThe study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.Originality/valueThis research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.

Analisis Troubleshooting Belt Scale CV509 pada Proses Pemindahan Batubara dalam Meningkatkan Performa dan Kehandalan Sistem Pengukuran di PT. BT

The Belt Scale is a critical instrument in industries for measuring the flow rate of materials on conveyors. The accuracy of these measurements is crucial as it directly impacts production efficiency, costs, and product quality. This research aims to conduct an in-depth analysis of Belt Scale accuracy under various operational conditions. The methodology employed involves collecting field data, conducting literature reviews, and utilizing computer simulations. The acquired data is then compared against reference data to identify error rates and influencing factors. The anticipated outcome of this study is a deeper understanding of Belt Scale performance, enabling companies to optimize their measurement systems. Furthermore, this research paves the way for the development of more advanced material measurement technologies. The primary objective of this study is to enhance the reliability of Belt Scale measurement systems, thereby providing more accurate data and facilitating better decision-making in production processes. Keywords: Accuracy, Belt Scale, Industrial Conveyor, Material Measurement.

DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification

Varietal purity is a critical quality indicator for seeds, yet various production processes can lead to the mixing of seeds from different varieties. Consequently, seed variety classification is an essential step in seed production. Existing classification algorithms often suffer from limitations such as reliance on single information sources, constrained feature extraction capabilities, time consumption, low accuracy, and the potential to cause irreversible damage to seeds. To address these challenges, this paper proposes a fast and non-destructive classification method for corn seeds, named DualTransAttNet, based on multi-source image information and hybrid feature extraction. High-resolution hyperspectral images of various corn varieties were collected, and a sliding sampling approach was employed to capture feature information across all spectral bands, resulting in the construction of a hyperspectral dataset for corn seed classification. Hyperspectral and RGB image data were then integrated to complement one another’s information and mitigate the insufficient feature diversity caused by single-source data. The proposed method leverages the strengths of convolutional neural networks (CNNs) and transformers to extract both local and global features, effectively capturing spectral and image characteristics. The experimental results demonstrate that the DualTransAttNet model can achieve a compact size of only 1.758 MB and an inference time of 0.019 ms. Compared to typical machine learning and deep learning models, the proposed model exhibits superior performance with an overall accuracy, F1-score, and Kappa coefficient of 90.01%, 88.9%, and 88.4%, respectively. The model’s rapid inference capability and low parameter count make it an excellent technical solution for agricultural automation and intelligent systems, thereby enhancing the efficiency and profitability of agricultural production.

Implementation of Quality of Design for the Development of Bilayer Tablet

Different drug release properties for different drugs contained in each layer of a bilayer tablet are rarely achievable with regular tablets. Additionally, these tablets help avoid physicochemical incompatibilities between medications and excipients. The successful production of such more complicated dosage forms depends on screening the material qualities of APIs and excipients and optimizing the processing parameters of each unit operations of the manufacturing process. In order to meet safety and efficacy regulations, these operations need to be properly monitored and managed to produce a drug product with acceptable quality and performance. Blending, granulation, pre-compression, and main compression are critical stages when formulation qualities and production processes should be tuned to avoid problems like weight variation, segregation, and delamination of particular components. Bilayer tablets, as opposed to ordinary tablets, offer distinct drug release properties for certain medications that are housed in each layer. These tablets also help to avoid physicochemical incompatibilities between drugs and excipients. The successful manufacturing of such more complex dosage forms depends on screening the material attributes of API and excipients and optimizing the processing parameters of individual unit operations of the manufacturing process in order to achieve safon of layers, which is frequently encountered during the production of bilayer tablets. For the quality and performance of the medication product to be acceptable, these processes need to be properly watched over and managed. The main objective of this review is to establish the foundation for implementing the Quality by Design (QbD).

How TV Programs of Home Design Attract the Audience -- Case Studies of Changing Room, New Home, and Design Rules

TV has always played an important role in transmitting information. Three TV programs about home design were selected as case studies to discuss how TV producers attracted the audience to the same subject of TV programs. It is found that, during the process of TV program production, attracting an audience does not mean reducing the useful information in the program or changing the narrative style of the program. Through these three TV programs, it is concluded that the dramatic increase in the narrative means of TV programs has not attracted the audience very well. Today's audience prefers to produce well-equipped TV programs. And now the content of TV programs is more and more diversified, and the positioning of the audience is more and more accurate. This also proves that the role of TV programs is no longer just entertainment, but a kind of information dissemination and cultural output

“A Poor Grinding Machine”: The Process of Juvenile Incarceration and Health Production in Socioeducation(?)

Objective: The objective of this study is to problematize socio-education practices in deprivation of liberty carried out in Brazil, considering aspects of mental health care, especially for adolescents who are compromised by the abusive use of psychoactive substances. Theoretical Framework: In this way, the contemporary socio-educational system is understood as a prison continuum, which controls bodies at a young age without the real production of the process of attention and care based on the redefinition of the act committed, changes in life perspectives, such as resocialization of these adolescents, as the construction of truths about these bodies takes place. Method: The methodology adopted for this research comprises a narrative review based on a survey carried out between 2017 and 2018, being updated through the collection of qualitative content. Results and Discussion: Dessa forma, idenitificou-se que o processo socioeducativo se manifesta diante de práticas excludentes e manicomiais, não superando aspectos propostos pelos próprios princípios estabelecidos através de legislações atuais. Assim, o processo de atenção e cuidado em saúde mental, diante de adolescentes que apresentam tais necessidades ficam restritas às estruturas medicalizantes e judicializantes. Research Implications: The implications that emanate from this study reverberate in the face of different practices that have been constituted daily in front of these adolescents, providing critical support in the face of the results presented for an ethical, political and committed to social sphere, especially considering adolescents. Originality/Value: This study contributes to the literature by emerging critical and contemporary production on the topic. In view of this, the relevance and value of this research is identified, as evidenced by the need to change the panorama of actions.

Inventory Optimization with Several Resources

Inventory optimization is extended with additional constraints that affect production efficiency using estimated inventory. The extension of the inventory problem is in a special formal form with an additional optimization problem. The latter is aimed at minimizing production costs while using optimal volumes of material stocks. Such integration of inventory and production is formalized through a bi-level optimization problem. The case of simultaneous delivery of different types of goods is strongly related to the production process of final goods. A bi-level optimization problem is numerically defined and solved. Delivery costs are minimized for a given production plan. The bi-level problem is applied to prepare feed with the required nutrient content while minimizing the inventory costs of supplying the required raw materials. Empirical results give advantages for the obtained solution of the bi-level optimization problem.

Module-A Sensor Performance Tests Used In Laboratory-Type Silage Production, Data Acquisition and Control System

The primary objective of this study is to investigate the performance of sensors integrated into the laboratory-type silage production, data acquisition, and control system. The system is a PLC-controlled and multi-sensor based system designed to enable numerous studies aimed at improving silage quality. It consists of grinding, weighing, silo, data acquisition, and control units. It provides the capability to apply/change/simulate various parameters during the silage production process. The silo unit is composed of two modules, module-A (compression principle) and module-B (vacuum principle). This research focuses on measurements conducted with plexiglass silos (24,5 cm3) in the module-A unit. This silos were equipped with oxygen sensor (±0-100 %), carbon dioxide sensor (0-5000 ppm), temperature sensor (±0.53 °C, -10 – 80 °C), humidity sensor (0-100 %), pH sensor (2-12), and pressure sensor (± 1000 mbar). The research utilized second-crop silage corn material with a dry matter content (DM) of 32%. Four different compaction forces were applied during the experiments. Sensor measurements were recorded as one data per second by connecting them to the data recording unit using analog sensors. Due to the abundance of data, average values were taken. The data were displayed and monitored on the HMI operator panel programmed with GOP HMI editor software and stored in Excel format. The measurements were carried out during the silage (aerobic) and post-silage (anaerobic) periods. According to the research results, it was observed that the six tested sensors performed accurate readings. However, issues related to the oxygen and carbon dioxide sensors were encountered. Due to the difficulty in reading at points with very low oxygen content, it was decided to be supported by controlling with sensors of different types and specifications. During measurements conducted at the compression stage in module-A, the pressure values varied between 0,34-0,67 bar with increasing compaction force. The temperature ranged from 16-33 °C, humidity from 60-100 %, pH from 5,8-5,6 O2 level from 8,1-0 mmol L-1, and CO2 level from 0-40 mmol L-1. The measured value ranges in silage varied depending on the duration of silage, and accurate measurements were obtained in the desired direction. Sensor placements were updated considering measurement accuracy.

Plasmonic Nanoantennas and Their Utilization for Green Energy

The increasing energy consumption and the effort to reduce dependence on fossil fuels necessitate a transition to clean and renewable energy sources. Photocatalytic and plasmon-assisted water splitting utilize solar energy to produce hydrogen, which represent a promising alternative to conventional methods of energy storage and transmission. These production processes involve complex electrochemical reactions using suitable catalysts. Plasmonic nanostructures, supporting surface plasmon resonances, enhance the efficiency of these reactions. This article focuses on the principles of these technologies, the importance of plasmonic nanostructures, and the use of plasmonic nanoantennas for plasmon-assisted hydrogen and oxygen production.

The intelligent selenium-enriched tea withering control system

This paper addresses the low level of intelligence in tea processing equipment in Enshi Prefecture by designing an intelligent withering control system based on the STMicroelectronics 32-bit Microcontroller (STM32). This control system can achieve real-time monitoring of the withering environment and automate the control of heating and ventilation dehumidification modules. By integrating IoT technology, relevant users can view the tea production process via mobile devices, enabling intelligent and remote production operations. Application results show that the system operates stably, accurately measures temperature and humidity in the withering environment, and achieves a control precision of % through a fuzzy control algorithm. It effectively meets the needs of tea processing in Enshi Prefecture. The system not only optimizes traditional processing workflows, enhancing processing efficiency and tea quality, but also provides new technological means for tea processing enterprises, contributing to the development and upgrading of the local tea industry.

Analisis Kelayakan Investasi Perancangan Alat Pembuat Adonan Mie Ayam

Pak Pon's chicken noodle SME is a business that sells chicken noodles located in Surabaya. This SME operates by selling only one menu item, chicken noodles, with an average of 200 kg of noodles sold per month, and it still purchases its noodle ingredients from suppliers. Therefore, none of the processes in this SME use machines to prepare the ingredients for the chicken noodles. Given this situation, the researcher has an idea to create a tool that can help streamline the production process in this SME with the aim of increasing sales profit. This research uses cost analysis methods to determine the cost of production, followed by the NPV method to assess whether the equipment purchased by the SME is feasible. The results of this research show that there is a comparison between making the ingredients in-house versus purchasing them. The investment in equipment for the SME is considered feasible, as the payback can be achieved in a few months. This study recommends that the SME increase its sales beyond 200 kg per month in order for the project to proceed as planned. Keywords: Cost analysis, Noodle Dough Tool, NPV, Profit

Enhancing Bioactive Cordycepin Production via Precision Fermentation with an Engineered Aspergillus oryzae

An optimal culture medium and highly stable biometabolites are important in industrial production processes. The response surface methodology with a Box–Behnken design was performed to determine the optimal culture medium of an engineered Aspergillus oryzae strain for cordycepin production by submerged fermentation. The influences of glucose, yeast extract, and adenine concentrations on cordycepin production were explored, and their concentrations were used for experimental design. The results reveal that the optimal culture components involved 30.0 g/L of glucose, 9.8 g/L of yeast extract, and 1.5 g/L of adenine. As predicted, the maximum cordycepin concentration (1724.53 ± 18.30 mg/L) was obtained with a short fermentation time (2 days). A significant increase in cordycepin yield (>50% increase) was observed in the culture grown in the optimized culture medium compared to that grown in the basal medium. A xanthine oxidase inhibitory activity assay demonstrated that the cordycepin product had a pharmacological function. It exhibited strong stability under high thermal and acidic conditions, with over 95% product recovery. The findings of this study are valuable for developing cost-effective processes for producing health-benefiting products.

Effect of Carbohydrate Formulas on Instrumental and Sensory Parameters in Dry-Fermented Iberian Pork Sausages

Dry-fermented sausages are appreciated all over the world for their sensory characteristics. Carbohydrates (sugars) are added during the production process, the type and quantity of which directly affect the quality of this product. However, there are few data on the role of sugars on instrumental and sensory parameters of sausages derived from Iberian pork. The objective was to determine the effect of different carbohydrate formulas during the ripening time on the quality of dry-fermented Iberian pork sausages. Five batches were formulated with different combinations and concentrations of carbohydrates (dextrose, dextrin and glucose syrup), making 16 sausages per batch on which to perform repeated measurements throughout the ripening process. Physicochemical characteristics, instrumental colour, textural parameters and sensory attributes were analysed. The C− batch (without any carbohydrate addition) showed unstable pH evolution and high b* values throughout the ripening process and the lowest instrumental texture values (for hardness, springiness and chewiness). The D10d5 batch also presented an unstable pH evolution but low a* values, and it was the highest rated by consumers for sensory texture attributes. This batch, made with dextrose (in higher proportion) and dextrin, differed from the other Iberian pork sausages, suggesting that this carbohydrate formula may be more appreciated by Mediterranean consumers.

Simulation of an allyl chloride production process via the propylene chlorination route in ChemCAD simulator

Allyl chloride is typically used to make intermediates for downstream derivatives such as resins and polymers, and in the production of epichlorohydrin. The present work describes the simulation and conceptual design of an allyl chloride production process via the propylene chlorination route in ChemCADÒ simulator, to know the mass and energy balances of the intermediate and final streams, the operating and design parameters of some equipment, and other results of interest. The production process consists of a fired heater, a fluidized bed reactor, a waste heat boiler, six shell and tube heat exchangers, two compressors, a gas-liquid absorber and four distillation columns. About 1.336,307 kg/h of allyl chloride are produced at the distillate of the last distillation column with a purity of 99,92%, while pure propylene, 2-chloropropene and an aqueous solution of HCl 32,4 wt. % are also obtained as byproducts. A first-of-its-kind simulation model was obtained in ChemCADÒ, which could be employed for further optimization studies and productivity increment analysis.

Peningkatan Produktivitas dan Manajemen Bisnis UMKM Kebab Vrindavan Mbaknyen melalui Teknologi Inovatif

Vrindavan Mbaknyen Kebab MSMEs are one of the business units that have great potential to grow but face challenges in productivity and business management. This service program aims to increase the productivity and business management of these MSMEs through the application of innovative technology. The methods used include needs analysis, training on the use of supporting technology, and assistance in the implementation of technology in daily operations. The results of the program showed an increase in the efficiency of the production process by 30%, as well as improvements in the financial management and inventory system. In addition, MSMEs have succeeded in increasing market reach using digital platforms. In conclusion, the application of innovative technology can improve the productivity and competitiveness of MSMEs effectively. This program is expected to be a model that can be replicated in other MSMEs to support local economic growth.

Sodium alginate/κ-carrageenan films for mupirocin dermal delivery

Aim: The chronicity of injuries is also a public health problem, and it is necessary to develop and apply new materials to promote more satisfactory results in the wound healing. Thus, this study aims to develop natural polymer films based on a combination of κ-carrageenan and sodium alginate, crosslinked with Zn2+, for the controlled delivery of mupirocin (MUP). Methods: Vibrational spectroscopy (Raman and infrared spectroscopies) was used to characterize the chemical structure and crosslinking process. Micro-Raman imaging and scanning electron microscopy were employed to observe the spatial distribution of the polymers and morphology of the samples, respectively. The uniformity (in terms of mass, thickness, and MUP concentration) of the films, MUP release kinetics, and their bactericidal activity were subjected to analysis. Results: The films exhibited good uniformity in terms of thickness, mass, and quantity of MUP. However, the percentage of antibiotics was lower than that added, indicating losses during the film production process. Swelling and release kinetic studies indicated good swelling capacity of the films and controlled drug delivery process. The antibacterial activity of the films was determined against Staphylococcus aureus, Escherichia coli, Staphylococcus epidermidis, and Pseudomonas aeruginosa using the zone of inhibition method. All films produced showed activity against the growth of these bacteria. Conclusions: The results illustrate the potential of employing κ-carrageenan and sodium alginate in the fabrication of polymeric films for the regulated release of MUP, with the aim of developing wound dressings that can improve wound healing outcomes.

Modelling of the gas purification system for flue gas acid production

AbstractEstablishing a gas pressure model of the purification system to accurately estimate the system output pressure is a powerful guarantee to ensure the stable and efficient operation of the acid production process. This paper presents a study on the establishment of gas pressure models for three facilities in the purification system at the Guixi Smelter in China, including a pulse jet fabric filter, an electrostatic precipitator, and a drying tower. Through analysis of the operating mechanisms of these facilities, pressure mechanism models are established for the gas flows. Considering the nonlinearity and time‐varying nature of the model, an improved extended Kalman filter (EKF) algorithm is proposed to perform online identification of the unknown parameters within the model. Compared to the first‐order EKF, the improved algorithm achieves significantly better performance without incurring additional computational overhead. Field experiments on pressure estimation at the acid production site validate the reasonableness of the established models, as well as the efficacy of the proposed identification algorithm.